@conference{hill2024mass,
  author = {Hill, Mark J. and Zaborowski, Rafal},
  title = {Mass Events and Collective Sentiment on Digital Platforms: Football's Impact on Online Fan Discourse},
  booktitle = {International Conference on Social Media \& Society},
  year = {2024},
  month = {June},
  address = {London, UK},
  organization = {Social Media Lab, Toronto Metropolitan University and Digital Cultures and Economies Research Hub, University of the Arts London}
}

@article{kendall_1938,
  author = {Kendall, M. G.},
  title = {A New Measure of Rank Correlation},
  journal = {Biometrika},
  volume = {30},
  number = {1-2},
  pages = {81--93},
  year = {1938},
  month = {June},
  doi = {10.1093/biomet/30.1-2.81}
}

@phdthesis{nuttall_online_2018,
	type = {doctoral},
	title = {Online {Fandom}: exploring community and identity formation within football fan forums},
	copyright = {cc\_by\_nc\_sa\_4},
	shorttitle = {Online {Fandom}},
	url = {https://www.uclan.ac.uk/research/index.php},
	abstract = {There have been recent calls for further academic attention to the online activities of football fans. Despite the growing number of studies that have utilised online interactions between fans as a source of data, none have focused on computer mediated communication (CMC) between fans as the actual subject of enquiry in itself.
The aim of the thesis is to analyse the role that the internet plays in modern football fandom and, more specifically, the way that fans communicate with one another on the internet. Allied to this, it aims to assess whether or not genuine communities of fans are established online as a result of the interaction between fans via CMC. In doing so, the thesis proposes a distinct conceptualisation of an online community in order for the term to retain conceptual and analytical value and, thus, avoid the imprecise and rhetoric use of the broader term of community within the academic study of football fans.
The underpinning research is based on a prolonged ethnographic study of an online community who frequented two internet message boards for the fans of Burnley Football Club. Each is home to several thousand members and discussion posts. This study encompassed a period of participant observation, between 2011 and 2017, and eight semi-structured interviews with significant community members who were identified during the observation process. The qualitative data gleaned from this research was then coded, line-by-line, to distil key and recurring themes.
The findings of the research suggest that CMC is facilitating the maintenance and recreation of traditional fan identities, practises and communities in modern football. The community in question, brought together by a shared interest and identity, is characterised by meaningful relationships, reciprocal behaviours, distinct norms and values, the formation of insider/outsider statuses, and identity to an online space and fellow community members. Whilst those members interact in a variety of ways, CMC has continued to be central to their engagements with one another following the formation of the community.},
	language = {en},
	urldate = {2025-04-13},
	school = {University of Central Lancashire},
	author = {Nuttall, Daniel},
	month = oct,
	year = {2018},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\B3CWDIEI\\Nuttall - 2018 - Online Fandom exploring community and identity formation within football fan forums.pdf:application/pdf;Snapshot:C\:\\Users\\markj\\Zotero\\storage\\FQ5R4JWK\\29184.html:text/html},
}

@article{kaden_i_2023,
	title = {“{I} don’t watch that anymore”: an analysis of online comments by {German} soccer fans on their relationship to their favored clubs},
	shorttitle = {“{I} don’t watch that anymore”},
	url = {https://consensus.app/papers/%E2%80%9C-i-don-%E2%80%99-t-watch-that-anymore-%E2%80%9D-an-analysis-of-online-comments-kaden-brandt/fdfd32f973865c80894d56170c468d8d/},
	doi = {10.3389/fpsyg.2023.1289436},
	abstract = {Soccer fans are important stakeholders of their favored clubs; yet, although there is manifold literature on this subject, there are still open questions concerning supporters’ relationship and loyalty to those clubs, such as potential fan exits, where supporters turn away from their preferred team. Existing literature describes diverging evidence as to whether an exit is possible and whether fans’ loyalty prevents that response. Against this background, it is important to examine how the relationship between fans and soccer clubs presents itself from the fans’ perspective. This study focuses on German soccer fans because an increasing number of media reports note problems for the fans in this regard, reporting eroded loyalty, increasing alienation, or turning away.By means of a qualitative and explorative approach (thematic analysis), this study analyzes online fan comments associated with the mentioned reports. A purposive sample of 17 media reports with 10,902 associated comments written/published between 2020 and 2023 was included in this study.The thematic analysis show that fans reflect their relationship to favored clubs in three ways: negative changes in the emotional relationship, negative behavioral changes in the relationship, and no or positive changes in the relationship. A wide continuum of negative emotional and behavioral changes is identified, ranging from a deterioration of the inner bond with the favored club to different levels of ceasing soccer-related consumption. As explanations for the (potential) dynamics and changes in the relationship, fans reflect a broad and diverse field of developments in the context of German soccer. The differentiated developments are systemized within four categories: commercialization, governance, attractiveness, and the COVID-19 pandemic.The results are discussed and contextualized referring to the Exit-Voice-Loyalty-Framework and thematically relevant literature. Particularly far-reaching is the finding that there are indeed fans in the field of soccer who are capable of permanently abandoning (exiting) formerly supported clubs. The article concludes with theoretical and managerial implications emerging from the results, as well as limitations and areas of interest for further research.},
	urldate = {2025-04-13},
	journal = {Frontiers in Psychology},
	author = {Kaden, Martin and Brandt, Christian and Bauers, S. B. and Bunar, Jonathan and Hovemann, Gregor},
	year = {2023},
	file = {Full Text:C\:\\Users\\markj\\Zotero\\storage\\9GE88FJJ\\Kaden et al. - 2023 - “I don’t watch that anymore” an analysis of online comments by German soccer fans on their relation.pdf:application/pdf;Snapshot:C\:\\Users\\markj\\Zotero\\storage\\KET7YCT4\\fdfd32f973865c80894d56170c468d8d.html:text/html},
}

@article{marques_sports_2018,
	title = {Sports fan relationships with soccer teams},
	volume = {2},
	url = {https://consensus.app/papers/sports-fan-relationships-with-soccer-teams-marques-nobre/3a32ee0bfd72536a895c166520164f0b/},
	doi = {10.1504/IJDCET.2018.10010163},
	abstract = {This paper investigates the relationships sports fans establish with teams. Specifically, it studies the Sporting Clube de Portugal (Sporting CP) case. The purpose of this study is to analyse whether the efforts that Sporting CP managers are investing in marketing strategies and initiatives, grounded on new communication channels and services (for instance, social media presence) impact the bonds that Sporting CP's fans establish with the club. Results indicated, in general, correspondence between club leaders' expectations (gathered through in-depth semi-structured interviews) and fans perceptions (collected through questionnaires). Most of the marketing strategies and initiatives are well received by fans. It seems that Sporting CP brand still has space to grow. The establishment of strategic partnerships, and sport marketing innovative strategies, in line with innovative communication channels, are proposed as recommendations. The study also emphasises the importance of social networks to sports management.},
	urldate = {2025-04-13},
	journal = {International Journal of Digital Culture and Electronic Tourism},
	author = {Marques, Tiago and Nobre, Helena and Gordon, David},
	year = {2018},
	file = {Snapshot:C\:\\Users\\markj\\Zotero\\storage\\SQUVTI6M\\3a32ee0bfd72536a895c166520164f0b.html:text/html},
}

@article{newson_united_2021,
	title = {United in defeat: shared suffering and group bonding among football fans},
	volume = {28},
	shorttitle = {United in defeat},
	url = {https://consensus.app/papers/united-in-defeat-shared-suffering-and-group-bonding-among-newson-buhrmester/45cd6ee4c7a558109a6712daa599d35d/},
	doi = {10.1080/23750472.2020.1866650},
	abstract = {ABSTRACT Purpose Evidence shows that the least successful clubs have the most committed fans – why? Here, we test the “shared-dysphoria-pathway-to-fusion” (SDPF) hypothesis that fans of the least successful clubs become irrevocably “fused” to their club and to each other, as a result of sharing self- and club-defining memories of past defeats. Design To assess the SDPF hypothesis, we calculated the most and least successful clubs from the UK’s top league, the Premier League, over a 10-year period. We then invited fans of these clubs to complete a survey (N = 752), comprising qualitative recollections of football events, quantitative survey measures of identity fusion and psychological kinship, and a trolley dilemma measuring willingness to sacrifice one’s self to save fellow supporters. Findings Our mediation model supported the SDPF hypothesis. Fans of Crystal Palace, Hull, Norwich, Sunderland, and West Bromwich Albion were more bonded and more willing to sacrifice themselves for other fans of their club than were fans of Manchester United, Arsenal, Chelsea, Liverpool or Manchester City. Across clubs, memories of past football defeats formed an essential part of fans’ self-concepts, thus fusing them to their club. Identity fusion in turn predicted a readiness to lay down one’s life to save fellow fans, and this relationship was statistically mediated by psychological kinship. Practical implications Understanding that shared suffering can lead to extreme bonding may help sports clubs and policy makers manage crowd behaviour. Clubs will benefit from tailoring brand management and fan retainment strategies to the SDPF hypothesis. In addition, these findings provide insight into the motivations of oppressed or persecuted groups, and such others fused through shared sufferings, helping us better understand and manage the psychological processes that can lead to extreme self-sacrifice. Research contributions This is the first study to show mediational support for the SDPF hypothesis in relation to football fandom. The psychological mechanism that may have once bonded embattled foraging groups in our ancestral past, now works in the modern world to unite soccer fans, among other kinds of groups, in their millions.},
	urldate = {2025-04-13},
	journal = {Managing Sport and Leisure},
	author = {Newson, M. and Buhrmester, Michael D. and Whitehouse, H.},
	year = {2021},
	pages = {164--181},
	file = {Accepted Version:C\:\\Users\\markj\\Zotero\\storage\\7MGQ42JS\\Newson et al. - 2021 - United in defeat shared suffering and group bonding among football fans.pdf:application/pdf},
}

@article{davidson_automated_2017,
	title = {Automated {Hate} {Speech} {Detection} and the {Problem} of {Offensive} {Language}},
	volume = {11},
	copyright = {Copyright (c) 2021 Proceedings of the International AAAI Conference on Web and Social Media},
	issn = {2334-0770},
	url = {https://ojs.aaai.org/index.php/ICWSM/article/view/14955},
	doi = {10.1609/icwsm.v11i1.14955},
	abstract = {A key challenge for automatic hate-speech detection on social media is the separation of hate speech from other instances of offensive language. Lexical detection methods tend to have low precision because they classify all messages containing particular terms as hate speech and previous work using supervised learning has failed to distinguish between the two categories. We used a crowd-sourced hate speech lexicon to collect tweets containing hate speech keywords. We use crowd-sourcing to label a sample of these tweets into three categories: those containing hate speech, only offensive language, and those with neither. We train a multi-class classifier to distinguish between these different categories. Close analysis of the predictions and the errors shows when we can reliably separate hate speech from other offensive language and when this differentiation is more difficult. We find that racist and homophobic tweets are more likely to be classified as hate speech but that sexist tweets are generally classified as offensive. Tweets without explicit hate keywords are also more difficult to classify.},
	language = {en},
	number = {1},
	urldate = {2025-04-13},
	journal = {Proceedings of the International AAAI Conference on Web and Social Media},
	author = {Davidson, Thomas and Warmsley, Dana and Macy, Michael and Weber, Ingmar},
	month = may,
	year = {2017},
	pages = {512--515},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\KXGI9XV4\\Davidson et al. - 2017 - Automated Hate Speech Detection and the Problem of Offensive Language.pdf:application/pdf},
}

@inproceedings{sap_risk_2019,
	address = {Florence, Italy},
	title = {The {Risk} of {Racial} {Bias} in {Hate} {Speech} {Detection}},
	url = {https://aclanthology.org/P19-1163/},
	doi = {10.18653/v1/P19-1163},
	abstract = {We investigate how annotators' insensitivity to differences in dialect can lead to racial bias in automatic hate speech detection models, potentially amplifying harm against minority populations. We first uncover unexpected correlations between surface markers of African American English (AAE) and ratings of toxicity in several widely-used hate speech datasets. Then, we show that models trained on these corpora acquire and propagate these biases, such that AAE tweets and tweets by self-identified African Americans are up to two times more likely to be labelled as offensive compared to others. Finally, we propose *dialect* and *race priming* as ways to reduce the racial bias in annotation, showing that when annotators are made explicitly aware of an AAE tweet`s dialect they are significantly less likely to label the tweet as offensive.},
	urldate = {2025-04-13},
	booktitle = {Proceedings of the 57th {Annual} {Meeting} of the {Association} for {Computational} {Linguistics}},
	publisher = {Association for Computational Linguistics},
	author = {Sap, Maarten and Card, Dallas and Gabriel, Saadia and Choi, Yejin and Smith, Noah A.},
	editor = {Korhonen, Anna and Traum, David and Màrquez, Lluís},
	month = jul,
	year = {2019},
	pages = {1668--1678},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\KI7RMN42\\Sap et al. - 2019 - The Risk of Racial Bias in Hate Speech Detection.pdf:application/pdf},
}

@article{jahan_systematic_2023,
	title = {A systematic review of hate speech automatic detection using natural language processing},
	volume = {546},
	issn = {0925-2312},
	url = {https://www.sciencedirect.com/science/article/pii/S0925231223003557},
	doi = {10.1016/j.neucom.2023.126232},
	abstract = {With the multiplication of social media platforms, which offer anonymity, easy access and online community formation and online debate, the issue of hate speech detection and tracking becomes a growing challenge to society, individual, policy-makers and researchers. Despite efforts for leveraging automatic techniques for automatic detection and monitoring, their performances are still far from satisfactory, which constantly calls for future research on the issue. This paper provides a systematic review of literature in this field, with a focus on natural language processing and deep learning technologies, highlighting the terminology, processing pipeline, core methods employed, with a focal point on deep learning architecture. From a methodological perspective, we adopt PRISMA guideline of systematic review of the last 10 years literature from ACM Digital Library and Google Scholar. In the sequel, existing surveys, limitations, and future research directions are extensively discussed.},
	urldate = {2025-04-13},
	journal = {Neurocomputing},
	author = {Jahan, Md Saroar and Oussalah, Mourad},
	month = aug,
	year = {2023},
	keywords = {Hate speech detection review, NLP deep learning review, PRISMA hate speech, Systematic review},
	pages = {126232},
	file = {Full Text:C\:\\Users\\markj\\Zotero\\storage\\Z92SEX7D\\Jahan and Oussalah - 2023 - A systematic review of hate speech automatic detection using natural language processing.pdf:application/pdf},
}

@article{vidgen_directions_2020,
	title = {Directions in abusive language training data, a systematic review: {Garbage} in, garbage out},
	volume = {15},
	issn = {1932-6203},
	shorttitle = {Directions in abusive language training data, a systematic review},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0243300},
	doi = {10.1371/journal.pone.0243300},
	abstract = {Data-driven and machine learning based approaches for detecting, categorising and measuring abusive content such as hate speech and harassment have gained traction due to their scalability, robustness and increasingly high performance. Making effective detection systems for abusive content relies on having the right training datasets, reflecting a widely accepted mantra in computer science: Garbage In, Garbage Out. However, creating training datasets which are large, varied, theoretically-informed and that minimize biases is difficult, laborious and requires deep expertise. This paper systematically reviews 63 publicly available training datasets which have been created to train abusive language classifiers. It also reports on creation of a dedicated website for cataloguing abusive language data hatespeechdata.com. We discuss the challenges and opportunities of open science in this field, and argue that although more dataset sharing would bring many benefits it also poses social and ethical risks which need careful consideration. Finally, we provide evidence-based recommendations for practitioners creating new abusive content training datasets.},
	language = {en},
	number = {12},
	urldate = {2025-04-13},
	journal = {PLOS ONE},
	author = {Vidgen, Bertie and Derczynski, Leon},
	month = dec,
	year = {2020},
	keywords = {Internet, Language, Machine learning, Metadata, Social discrimination, Speech, Taxonomy, Twitter},
	pages = {e0243300},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\MKLSJ8GF\\Vidgen and Derczynski - 2020 - Directions in abusive language training data, a systematic review Garbage in, garbage out.pdf:application/pdf},
}

@article{kerr_emotional_2005,
	title = {Emotional dynamics of soccer fans at winning and losing games},
	volume = {38},
	issn = {0191-8869},
	url = {https://www.sciencedirect.com/science/article/pii/S0191886904003642},
	doi = {10.1016/j.paid.2004.10.002},
	abstract = {The purpose of the present study was to investigate the emotional reactions of fans of winning and losing teams at two professional soccer games. The participants were 187 male and 146 female Japanese soccer fans who provided biographical information and responded to a slightly modified state version of the Tension and Effort Stress Inventory (TESI; Svebak, Ursin, Endresen, Hjelmen, \& Apter, 1991) pre-, mid- and post-game. Data from winning and losing fans were analysed using 3×2 independent groups ANOVAs for each of the pleasant emotions, unpleasant emotions, and tension stress/effort stress ratings with Bonferroni adjustment to control Type 1 error rates. When winning and losing fans’ responses were compared, most differences were found post-game, where losing fans scored significantly higher than winning fans on boredom, anger, sullenness, humiliation and resentment, and lower on relaxation. Also, levels of pleasant and unpleasant emotions changed significantly for losing fans, but (except for boredom) not for winning fans.},
	number = {8},
	urldate = {2025-04-13},
	journal = {Personality and Individual Differences},
	author = {Kerr, John H. and Wilson, George V. and Nakamura, Isamu and Sudo, Yoshiko},
	month = jun,
	year = {2005},
	keywords = {Pleasant emotions, Reversal theory, Soccer fans, Unpleasant emotions},
	pages = {1855--1866},
	file = {ScienceDirect Snapshot:C\:\\Users\\markj\\Zotero\\storage\\XDI3P8WI\\S0191886904003642.html:text/html},
}

@inproceedings{camacho-collados_tweetnlp_2022,
	address = {Abu Dhabi, UAE},
	title = {{TweetNLP}: {Cutting}-{Edge} {Natural} {Language} {Processing} for {Social} {Media}},
	shorttitle = {{TweetNLP}},
	url = {https://aclanthology.org/2022.emnlp-demos.5/},
	doi = {10.18653/v1/2022.emnlp-demos.5},
	abstract = {In this paper we present TweetNLP, an integrated platform for Natural Language Processing (NLP) in social media. TweetNLP supports a diverse set of NLP tasks, including generic focus areas such as sentiment analysis and named entity recognition, as well as social media-specific tasks such as emoji prediction and offensive language identification. Task-specific systems are powered by reasonably-sized Transformer-based language models specialized on social media text (in particular, Twitter) which can be run without the need for dedicated hardware or cloud services. The main contributions of TweetNLP are: (1) an integrated Python library for a modern toolkit supporting social media analysis using our various task-specific models adapted to the social domain; (2) an interactive online demo for codeless experimentation using our models; and (3) a tutorial covering a wide variety of typical social media applications.},
	urldate = {2025-04-13},
	booktitle = {Proceedings of the 2022 {Conference} on {Empirical} {Methods} in {Natural} {Language} {Processing}: {System} {Demonstrations}},
	publisher = {Association for Computational Linguistics},
	author = {Camacho-collados, Jose and Rezaee, Kiamehr and Riahi, Talayeh and Ushio, Asahi and Loureiro, Daniel and Antypas, Dimosthenis and Boisson, Joanne and Espinosa Anke, Luis and Liu, Fangyu and Martínez Cámara, Eugenio},
	editor = {Che, Wanxiang and Shutova, Ekaterina},
	month = dec,
	year = {2022},
	pages = {38--49},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\F9LFEZPR\\Camacho-collados et al. - 2022 - TweetNLP Cutting-Edge Natural Language Processing for Social Media.pdf:application/pdf},
}

@article{biscaia_effects_2012,
	title = {The effects of emotions on football spectators' satisfaction and behavioural intentions},
	volume = {12},
	issn = {1618-4742},
	url = {https://doi.org/10.1080/16184742.2012.679949},
	doi = {10.1080/16184742.2012.679949},
	abstract = {The goal of this study was to examine the relationship between spectators' emotions, satisfaction, and behavioural intentions at football games. A survey was conducted among spectators of the top Portuguese professional football league during eight games (n=466). The sport emotion questionnaire was used to assess spectators' emotions and the results gathered from a structural equation model suggest that analysis of specific emotions is crucial to understand spectators' responses. Findings provide evidence that only the emotion of joy has a positive direct effect on satisfaction, as well as an indirect effect on behavioural intentions, via satisfaction. In turn, dejection has a negative direct effect on behavioural intentions, while satisfaction positively influences behavioural intentions. These results suggest managerial implications, such as the need to improve stadium atmosphere and social facilitation in order to provide an enjoyable overall experience to the spectators, and contribute to overall spectator satisfaction and positive behavioural intentions.},
	number = {3},
	urldate = {2025-04-13},
	journal = {European Sport Management Quarterly},
	author = {Rui Biscaia and Abel Correia and António Rosado and João Maroco and Ross, Stephen},
	month = jun,
	year = {2012},
	keywords = {behavioural intentions, clubs, emotions, satisfaction, sporting events},
	pages = {227--242},
    doi = {https://doi.org/10.1080/16184742.2012.679949}
}

@article{edensor_producing_2015,
	title = {Producing atmospheres at the match: {Fan} cultures, commercialisation and mood management in {English} football},
	volume = {15},
	issn = {1755-4586},
	shorttitle = {Producing atmospheres at the match},
	url = {https://www.sciencedirect.com/science/article/pii/S1755458613001175},
	doi = {10.1016/j.emospa.2013.12.010},
	abstract = {By focussing on Premier League club, Manchester City, this paper explores the ways in which a shifting flow of atmosphere is generated inside and outside football stadia, generated by events on the pitch, spatial formations, fan culture, and other factors such as weather, season and light. I argue that such atmospheres are co-productions by fans, who play their part in encouraging their team by suspending emotional and social restraint. I also investigate how with the intensified commercialisation of football, there have been recent concerns about a lack of atmosphere. All-seater stadia, sponsorship and corporate provision and the influx of new middle class fans seems to contrast with the packed terraces of fervent working class spectators of yesteryear, where closely packed bodies and loud collective chanting and singing produced a heady atmosphere. Accordingly, I will explore how clubs and fans have devised a range of strategies to manage atmospheres to inculcate greater intensities on match days.},
	urldate = {2025-04-13},
	journal = {Emotion, Space and Society},
	author = {Edensor, Tim},
	month = may,
	year = {2015},
	keywords = {Atmosphere, Commercialisation, Fan culture, Football, Regulation, Stadium},
	pages = {82--89},
}

@article{parry_game_2012,
	title = {Game of two passions: a football fan's autoethnography},
	volume = {12},
	issn = {1443-9883},
	shorttitle = {Game of two passions},
	url = {https://doi.org/10.1108/14439881211248374},
	doi = {10.1108/14439881211248374},
	abstract = {Purpose – The purpose of this paper is to explore the use of autoethnography within the context of sports fandom. This paper advocates the use of such qualitative methodologies to enable a greater understanding of sports fans. The paper also aims to provide greater understanding of sports fandom. Design/methodology/approach – The research moves away from traditional methodologies of studying sports fandom from an objective viewpoint and uses an evocative autoethnography to provide an account of the lived experience of a sports fan. Findings – By writing himself into his research it has been possible to gain a deeper insight into sports fandom. The subject of passion arises and while the Dualistic Model of Passion was explored as a mechanism for dealing with obsessive passion it is suggested that attempting to move away from a state of obsessive passion may diminish the enjoyment of being a sports fan. Practical implications – This paper highlights the benefits that methodologies such as autoethnography can have for academics studying sports fandom and other disciplines. It encourages academics to overcome the perceived lack of academic acceptance of the method. Originality/value – This paper utilises a qualitative methodology to explore the experience of being a sports fan. This methodological approach is yet to be fully embraced within this field and hence there is a lack of in‐depth data on the experiences of sports fans. This account will allow readers to develop a greater understanding and insight of sports fans.},
	number = {2},
	urldate = {2025-04-13},
	journal = {Qualitative Research Journal},
	author = {Parry, Keith D.},
	month = jan,
	year = {2012},
	keywords = {Autoethnography, Behaviour, Ethnography, Liverpool Football, Passion, Sports fans},
	pages = {238--250},
	file = {Accepted Version:C\:\\Users\\markj\\Zotero\\storage\\6STV8GB2\\Parry - 2012 - Game of two passions a football fan's autoethnography.pdf:application/pdf;Snapshot:C\:\\Users\\markj\\Zotero\\storage\\RRE5JNWQ\\html.html:text/html},
}

@book{sandvoss_game_2004,
	address = {London},
	title = {A {Game} of {Two} {Halves}: {Football} {Fandom}, {Television} and {Globalisation}},
	isbn = {978-0-203-56139-3},
	shorttitle = {A {Game} of {Two} {Halves}},
	abstract = {Professional football is one of the most popular television 'genres' worldwide, attracting the support of millions of fans, and the sponsorship of powerful companies.  In A Game of Two Halves, Sandvoss considers football's relationship with television, its links with transnational capitalism, and the importance of football fandom in forming social and cultural identities around the globe. He presents the phenomenon of football as a reflection postmodern culture and globalization.Through a series of case studies, based in ethnographic audience research, Sandvoss explores the motivations and pleasures of football fans, the intense bond formed between supporters and their clubs, the implications of football consumption on political discourse and citizenship, football as a factor of cultural globalisation, and the pivotal role of football and television in a postmodern cultural order.},
	publisher = {Routledge},
	author = {Sandvoss, Cornel},
	month = mar,
	year = {2004},
	doi = {10.4324/9780203561393},
}

@article{fenton_womens_2024,
	title = {Women’s football subculture of misogyny: the escalation to online gender-based violence},
	volume = {24},
	issn = {1618-4742},
	shorttitle = {Women’s football subculture of misogyny},
	url = {https://doi.org/10.1080/16184742.2023.2270566},
	doi = {10.1080/16184742.2023.2270566},
	abstract = {Given the worldwide growth of women’s football and its presence on social media, it is essential to explore and understand fan attitudes and culture. This article provides the first empirical social media netnography focusing on English women’s football teams (Manchester United and Burnley) and international fan views towards women professional players on TikTok. We extend this discussion by utilising a netnography in which researchers immersed themselves for seven months in women’s football groups on TikTok to gather and analyse new qualitative data in this context. We identify the escalation of gender-based violence on social media against women players. Four key themes emerged from the netnography: 1. Sexism: the place of women in football; 2. Misogyny and hatred of women; 3. Sexualisation of women; 4. Demand for a male-only space. Sexist comments were apparent in all of the TikTok posts containing female football players, with some also containing more aggressive misogynistic comments. Other dominant comments sought to reduce women to objects of sexual desire and belittle their professional skills, whereas others were appalled at the presence of female players on the clubs’ official accounts, demanding them to be a male-only space. The study contributes to the understanding of online fan cultures on complex, video-based platforms such as TikTok. Through literature review and netnography, we identified a problem for football clubs on social media of longstanding, problematic issues of toxic fan comments.},
	number = {6},
	urldate = {2025-04-13},
	journal = {European Sport Management Quarterly},
	author = {Alex Fenton and Wasim Ahmed and Mariann (Maz) Hardey and Rosy Boardman and Emma Kavanagh},
	month = nov,
	year = {2024},
    keywords = {gender-based violence, Netnography, social media, TikTok, women’s football},
	pages = {1215--1237},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\C2FQ8PRH\\Fenton et al. - 2024 - Women’s football subculture of misogyny the escalation to online gender-based violence.pdf:application/pdf},
}

@phdthesis{fenton_field_2018,
	address = {Manchester},
	type = {{PhD}},
	title = {The {Field} behind the {Screen}: {Social} {Capital} and the {Social} {Media} {Communications} of a {Football} {Club} {Brand} - {ProQuest}},
	shorttitle = {The {Field} behind the {Screen}},
	url = {https://www.proquest.com/openview/2d8e81bd109645f35921dbd5cc3b9340/1?pq-origsite=gscholar%26cbl=51922%26diss=y},
	abstract = {Explore millions of resources from scholarly journals, books, newspapers, videos and more, on the ProQuest Platform.},
	language = {en},
	urldate = {2025-04-13},
	school = {University of Salford},
	author = {Fenton, Alex},
	year = {2018},
	file = {Snapshot:C\:\\Users\\markj\\Zotero\\storage\\DKHUGGHZ\\1.html:text/html},
}

@article{rowe_cultures_2010,
	title = {Cultures of {Complaint}: {Online} {Fan} {Message} {Boards} and {Networked} {Digital} {Media} {Sport} {Communities}},
	volume = {16},
	url = {https://doi.org/10.1177/1354856510367622},
	doi = {10.1177/1354856510367622},
	abstract = {Association football fans in the UK often blame the media for ruining the game as an organic community experience. Certainly, this proposition is supported by the substantial levels of complaint that can be found across thousands of online fan message boards. We argue that these complaints embrace online comment and activism as a continuation of football’s traditional culture of communicative exchange between supporters. Yet, online football fan discussion also presents a contradiction, relying upon the same media networks against which fans rail for commodifying ‘the people’s game’. Using cultivation analysis, the case presented is based upon a study of ‘FreeMyFC’ (FMFC), a website ostensibly started to expose the failures of ‘MyFootballClub’ (MFC), the world’s first attempt to manage a football club through a supporter funded and managed website.},
	number = {3},
	journal = {Convergence},
	author = {Rowe, David and Ruddock, Andy and Hutchins, Brett},
	year = {2010},
	pages = {298--315},
}

@book{awan_hate_2023,
	title = {Hate {Crime} in {Football}},
	isbn = {978-1-5292-2718-5},
	url = {https://www.cambridge.org/core/books/hate-crime-in-football/B1797CCDBB7823401611181FC13F3652},
	abstract = {Rates of hate crime within football have been increasing, despite the visibility of anti-racist actions such as 'taking the knee'. With a unique collection of testimonies, this book shows that hostility is a daily occurrence for some professional football players, ranging from online threats to physical intimidation and violence at football matches. Bringing a range of perspectives to this widespread problem, leading academics, practitioners and policy makers shed light on the best strategies to tackle racism, homophobia, transphobia and misogyny in football.},
	urldate = {2025-04-13},
	publisher = {Bristol University Press},
	editor = {Awan, Imran and Zempi, Irene},
	year = {2023},
	doi = {10.46692/9781529227208},
	file = {Snapshot:C\:\\Users\\markj\\Zotero\\storage\\AQLUP3KJ\\B1797CCDBB7823401611181FC13F3652.html:text/html},
}

@misc{londonassembly_police_2023,
	title = {Police record almost 100 football-related hate crimes in a year},
	author = {{London Assembly}},
	url = {https://www.london.gov.uk/who-we-are/what-london-assembly-does/london-assembly-members/unmesh-desai/footballhatecrime2023},
	abstract = {There were 96 football-related hate crimes in London in the year to November 2023, new figures reveal.},
	year = {2023},
	language = {en-gb},
	urldate = {2025-04-13},
	organization = {London City Hall},
}

@article{miranda_hate_2024,
	title = {Hate speech on social media: behaviour of {Portuguese} football fans on {Facebook}},
	volume = {25},
	issn = {1466-0970},
	shorttitle = {Hate speech on social media},
	url = {https://doi.org/10.1080/14660970.2023.2230452},
	doi = {10.1080/14660970.2023.2230452},
	abstract = {This article examines how Facebook is shaping the nature of hate speech. The observation field is the Facebook pages of the 18 Portuguese football clubs of the Portuguese League – the main professional competition in the country. Data extraction was performed automatically via Facebook Graph API in the first three months of the 2020/2021 season. The analysed dataset has 5,192 publications and 276,231 fan comments, which registered over 5 million reactions (like, haha, love, sad, wow, etc.). The findings reveal that the volume of hate speech material on Facebook pages has a low incidence. In any case, the most significant comments are racists, xenophobes, and regional antagonisms. These cases are also the ones that have attracted the most reactions from fans.},
	number = {1},
	urldate = {2025-04-13},
	journal = {Soccer \& Society},
    author={Sandra Miranda and C{\'e}lia Gouveia and Branco Di F{\'a}tima and Ana Cristina Antunes},
	month = jan,
	year = {2024},
	pages = {76--91},
	file = {Full Text:C\:\\Users\\markj\\Zotero\\storage\\INMGMCS5\\Miranda et al. - 2024 - Hate speech on social media behaviour of Portuguese football fans on Facebook.pdf:application/pdf},
}

@article{murray_uks_2021,
	chapter = {UK news},
	title = {{UK}'s first football hate crime officer turns focus on social media},
	issn = {0261-3077},
	url = {https://www.theguardian.com/uk-news/2021/feb/15/uk-first-football-hate-officer-social-media-racist-abuse-stuart-ward},
	abstract = {Stuart Ward of West Midlands police aims to stamp out racist abuse in grounds and online to bring back community spirit},
	language = {en-GB},
	urldate = {2025-04-13},
	journal = {The Guardian},
	author = {Murray, Jessica},
	month = feb,
	year = {2021},
	keywords = {Digital media, Football, Hate crime, Media, Online abuse, Police, Race, Social media, Society, Sport, UK news},
	file = {Snapshot:C\:\\Users\\markj\\Zotero\\storage\\F6XNURUK\\uk-first-football-hate-officer-social-media-racist-abuse-stuart-ward.html:text/html},
}

@article{kassam_four_2024,
	chapter = {Football},
	title = {Four men arrested over online racist hate campaign against {Vinícius} {Júnior}},
	issn = {0261-3077},
	url = {https://www.theguardian.com/football/2024/oct/24/four-men-arrested-over-online-racist-hate-campaign-against-vinicius-junior},
	abstract = {Arrests made after Spanish police investigation into social media posts before Atlético-Real Madrid derby},
	language = {en-GB},
	urldate = {2025-04-13},
	journal = {The Guardian},
	author = {Kassam, Ashifa},
	month = oct,
	year = {2024},
	keywords = {Atlético Madrid, European club football, Football, La Liga, Real Madrid, Spain, Sport, Vinícius Júnior},
	file = {Snapshot:C\:\\Users\\markj\\Zotero\\storage\\MJ5FS2NL\\four-men-arrested-over-online-racist-hate-campaign-against-vinicius-junior.html:text/html},
}

@article{porat_football_2010,
	title = {Football fandom: {A} bounded identification},
	volume = {11},
	issn = {1466-0970},
	shorttitle = {Football fandom},
	url = {http://www.scopus.com/inward/record.url?scp=77951598057&partnerID=8YFLogxK},
	doi = {10.1080/14660971003619594},
	abstract = {Identity as a concept and as a practice differs from what it was assumed in the past. The literature pertaining to this concept and its practices is very sceptical: identity is unstable and undergoing a continuous process of construction and reconstruction, and the modern-postmodern individual must realize and accept this volatile situation. This essay deals with a relatively safer basis for identity: football fandom. Studies on global football fan behaviour conclude that supporting a football club is a life-long project that begins at an early age and ends with the life of the fan. Such studies unequivocally indicate that football fandom is a way of life. The fan's daily and weekly agenda is determined by his relationship with the football club. Most importantly, football fandom is a significant component of identity: it is stable and effective. Using the results of a study of Israeli football fans, this essay suggests that fandom is indeed a critical component in the fan's identity profile. Hence, fans are at least partially 'safe' in a volatile world of unstable identities.},
	number = {3},
	urldate = {2025-04-13},
	journal = {Soccer and Society},
	author = {Porat, Amir Ben},
	month = may,
	year = {2010},
	pages = {277--290},
}

@inproceedings{tsugawa_negative_2015,
	address = {New York, NY, USA},
	series = {{COSN} '15},
	title = {Negative {Messages} {Spread} {Rapidly} and {Widely} on {Social} {Media}},
	isbn = {978-1-4503-3951-3},
	url = {https://doi.org/10.1145/2817946.2817962},
	doi = {10.1145/2817946.2817962},
	abstract = {We investigate the relation between the sentiment of a message on social media and its virality, defined as the volume and the speed of message diffusion. We analyze 4.1 million messages (tweets) obtained from Twitter. Although factors affecting message diffusion on social media have been studied previously, we focus on message sentiment, and reveal how the polarity of message sentiment affects its virality. The virality of a message is measured by the number of message repostings (retweets) and the time elapsed from the original posting of a message to its Nth reposting (N-retweet time). Through extensive analyses, we find that negative messages are likely to be reposted more rapidly and frequently than positive and neutral messages. Specifically, the reposting volume of negative messages is 1.2--1.6-fold that of positive and neutral messages, and negative messages spread at 1.25 times the speed of positive and neutral messages when the diffusion volume is large.},
	urldate = {2025-04-13},
	booktitle = {Proceedings of the 2015 {ACM} on {Conference} on {Online} {Social} {Networks}},
	publisher = {Association for Computing Machinery},
	author = {Tsugawa, Sho and Ohsaki, Hiroyuki},
	month = nov,
	year = {2015},
	pages = {151--160},
	file = {Submitted Version:C\:\\Users\\markj\\Zotero\\storage\\5YRFKKNI\\Tsugawa and Ohsaki - 2015 - Negative Messages Spread Rapidly and Widely on Social Media.pdf:application/pdf},
}

@article{ferrara_measuring_2015,
	title = {Measuring {Emotional} {Contagion} in {Social} {Media}},
	volume = {10},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0142390},
	doi = {10.1371/journal.pone.0142390},
	abstract = {Social media are used as main discussion channels by millions of individuals every day. The content individuals produce in daily social-media-based micro-communications, and the emotions therein expressed, may impact the emotional states of others. A recent experiment performed on Facebook hypothesized that emotions spread online, even in absence of non-verbal cues typical of in-person interactions, and that individuals are more likely to adopt positive or negative emotions if these are over-expressed in their social network. Experiments of this type, however, raise ethical concerns, as they require massive-scale content manipulation with unknown consequences for the individuals therein involved. Here, we study the dynamics of emotional contagion using a random sample of Twitter users, whose activity (and the stimuli they were exposed to) was observed during a week of September 2014. Rather than manipulating content, we devise a null model that discounts some confounding factors (including the effect of emotional contagion). We measure the emotional valence of content the users are exposed to before posting their own tweets. We determine that on average a negative post follows an over-exposure to 4.34\% more negative content than baseline, while positive posts occur after an average over-exposure to 4.50\% more positive contents. We highlight the presence of a linear relationship between the average emotional valence of the stimuli users are exposed to, and that of the responses they produce. We also identify two different classes of individuals: highly and scarcely susceptible to emotional contagion. Highly susceptible users are significantly less inclined to adopt negative emotions than the scarcely susceptible ones, but equally likely to adopt positive emotions. In general, the likelihood of adopting positive emotions is much greater than that of negative emotions.},
	language = {en},
	number = {11},
	urldate = {2025-04-13},
	journal = {PLOS ONE},
	author = {Ferrara, Emilio and Yang, Zeyao},
	month = nov,
	year = {2015},
	keywords = {Algorithms, Emotions, Facebook, Mathematical models, Social media, Social networks, Social systems, Twitter},
	pages = {e0142390},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\J9HGUZS8\\Ferrara and Yang - 2015 - Measuring Emotional Contagion in Social Media.pdf:application/pdf},
}

@inproceedings{wang_making_2023,
	address = {New York, NY, USA},
	series = {{CHI} '23},
	title = {Making {Sense} of {Post}-match {Fan} {Behaviors} in the {Online} {Football} {Communities}},
	isbn = {978-1-4503-9421-5},
	url = {https://doi.org/10.1145/3544548.3581310},
	doi = {10.1145/3544548.3581310},
	abstract = {Professional sports have large fan bases that congregate in online sports fan communities. The sports community is suitable to be a sandbox for studying offline context’s effects on online community behavior. By now, prior works did not present a detailed study on the offline-online connection by examining detailed community discussion content. To fill this gap, this work presents a comprehensive study of online communities’ comments about football (soccer) matches, grounded in the data from Premier League teams’ Reddit online communities during the 2020-2021 season. We propose a metric “gap score” to quantify offline events’ effects by measuring the gap between fans’ prematch expectations and actual match results. Using this metric, we investigated how team performance impacted comments’ sentiment, discussion topics, and the pattern of comments’ votes. The findings highlight the close connection that exists between offline events and online discussions and reveals both theoretical and practical implications for online communities.},
	urldate = {2025-04-13},
	booktitle = {Proceedings of the 2023 {CHI} {Conference} on {Human} {Factors} in {Computing} {Systems}},
	publisher = {Association for Computing Machinery},
	author = {Wang, Yucheng and Lu, Zhicong},
	month = apr,
	year = {2023},
	pages = {1--17},
}

@article{braghieri_social_2022,
	title = {Social {Media} and {Mental} {Health}},
	volume = {112},
	issn = {0002-8282},
	url = {https://www.aeaweb.org/articles?id=10.1257/aer.20211218},
	doi = {10.1257/aer.20211218},
	abstract = {We provide quasi-experimental estimates of the impact of social media on mental health by leveraging a unique natural experiment: the staggered introduction of Facebook across US colleges. Our analysis couples data on student mental health around the years of Facebook's expansion with a generalized difference-in-differences empirical strategy. We find that the rollout of Facebook at a college had a negative impact on student mental health. It also increased the likelihood with which students reported experiencing impairments to academic performance due to poor mental health. Additional evidence on mechanisms suggests the results are due to Facebook fostering unfavorable social comparisons.},
	language = {en},
	number = {11},
	urldate = {2025-04-13},
	journal = {American Economic Review},
	author = {Braghieri, Luca and Levy, Ro'ee and Makarin, Alexey},
	month = nov,
	year = {2022},
	keywords = {Media, Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making, Health Behavior, Higher Education, Research Institutions, Entertainment},
	pages = {3660--3693},
	file = {Submitted Version:C\:\\Users\\markj\\Zotero\\storage\\QUBE8M55\\Braghieri et al. - 2022 - Social Media and Mental Health.pdf:application/pdf},
}

@article{allcott_welfare_2020,
	title = {The {Welfare} {Effects} of {Social} {Media}},
	volume = {110},
	issn = {0002-8282},
	url = {https://www.aeaweb.org/articles?id=10.1257/aer.20190658},
	doi = {10.1257/aer.20190658},
	abstract = {The rise of social media has provoked both optimism about potential societal benefits and concern about harms such as addiction, depression, and political polarization. In a randomized experiment, we find that deactivating Facebook for the four weeks before the 2018 US midterm election (i) reduced online activity, while increasing offline activities such as watching TV alone and socializing with family and friends; (ii) reduced both factual news knowledge and political polarization; (iii) increased subjective well-being; and (iv) caused a large persistent reduction in post-experiment Facebook use. Deactivation reduced post-experiment valuations of Facebook, suggesting that traditional metrics may overstate consumer surplus.},
	language = {en},
	number = {3},
	urldate = {2025-04-13},
	journal = {American Economic Review},
	author = {Allcott, Hunt and Braghieri, Luca and Eichmeyer, Sarah and Gentzkow, Matthew},
	month = mar,
	year = {2020},
	keywords = {Computer Software, Economic Sociology, Consumer Economics: Empirical Analysis, Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior, Micro-Based Behavioral Economics: General, General Welfare, Economic Anthropology, Language, Media, Information and Internet Services, Social and Economic Stratification, Well-Being, Entertainment},
	pages = {629--676},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\AU77FQE3\\Allcott et al. - 2020 - The Welfare Effects of Social Media.pdf:application/pdf},
}

@misc{hanscom_toxicity_2024,
	title = {The {Toxicity} {Phenomenon} {Across} {Social} {Media}},
	url = {http://arxiv.org/abs/2410.21589},
	doi = {10.48550/arXiv.2410.21589},
	abstract = {Social media platforms have evolved rapidly in modernity without strong regulation. One clear obstacle faced by current users is that of toxicity. Toxicity on social media manifests through a number of forms, including harassment, negativity, misinformation or other means of divisiveness. In this paper, we characterize literature surrounding toxicity, formalize a definition of toxicity, propose a novel cycle of internet extremism, list current approaches to toxicity detection, outline future directions to minimize toxicity in future social media endeavors, and identify current gaps in research space. We present a novel perspective of the negative impacts of social media platforms and fill a gap in literature to help improve the future of social media platforms.},
	urldate = {2025-04-13},
	publisher = {arXiv},
	author = {Hanscom, Rhett and Lehman, Tamara Silbergleit and Lv, Qin and Mishra, Shivakant},
	month = oct,
	year = {2024},
	note = {arXiv:2410.21589 [cs]
version: 1},
	keywords = {Computer Science - Computers and Society, Computer Science - Social and Information Networks},
	annote = {Comment: 12 pages, 2 figures, 2 tables, Cycle of Internet Extremism},
	file = {Preprint PDF:C\:\\Users\\markj\\Zotero\\storage\\Z9VPFSQI\\Hanscom et al. - 2024 - The Toxicity Phenomenon Across Social Media.pdf:application/pdf;Snapshot:C\:\\Users\\markj\\Zotero\\storage\\IC5QRGUU\\2410.html:text/html},
}

@article{recuero_platformization_2024,
	title = {The {Platformization} of {Violence}: {Toward} a {Concept} of {Discursive} {Toxicity} on {Social} {Media}},
	volume = {10},
	issn = {2056-3051},
	shorttitle = {The {Platformization} of {Violence}},
	url = {https://doi.org/10.1177/20563051231224264},
	doi = {10.1177/20563051231224264},
	abstract = {Discourse has long been recognized as a source of symbolic violence, perpetuating power relations and reinforcing existing social hierarchies. With the rise of social media platforms, the influence of discourse on society has gained renewed attention. These platforms, while enabling social interactions, also serve as catalysts for violent behaviors, reinforcing and legitimizing forms of oppression and symbolic violence, particularly the violence of language. While the concept of toxicity is frequently used to describe this phenomenon, its meaning and connection to language often remain unexplored. This article aims to address this gap by examining the significance of toxicity in discourse and how the infrastructure of social media platforms facilitates the emergence of toxic discourses. It argues that while toxicity and violence are related, they are distinct phenomena. Toxicity, as a dimension of symbolic violence, contaminates debates and discourses, and is enabled by the characteristics of platformization in online interactions. Thus, toxicity is an effect of platforms mediating social interactions.},
	language = {EN},
	number = {1},
	urldate = {2025-04-13},
	journal = {Social Media + Society},
	author = {Recuero, Raquel},
	month = jan,
	year = {2024},
	pages = {20563051231224264},
	file = {SAGE PDF Full Text:C\:\\Users\\markj\\Zotero\\storage\\V3JBIJPG\\Recuero - 2024 - The Platformization of Violence Toward a Concept of Discursive Toxicity on Social Media.pdf:application/pdf},
}

@article{anderson_social_2017,
	title = {Social {Media}, {Science}, and {Attack} {Discourse}: {How} {Twitter} {Discussions} of {Climate} {Change} {Use} {Sarcasm} and {Incivility}},
	volume = {39},
	issn = {1075-5470},
	shorttitle = {Social {Media}, {Science}, and {Attack} {Discourse}},
	url = {https://doi.org/10.1177/1075547017735113},
	doi = {10.1177/1075547017735113},
	abstract = {Conflict in online discussions of science has the potential to polarize individuals’ perceptions of science, yet science communication scholarship has paid little attention to systematic study of how verbal attacks play out in online discussions of science. This study analyzes sarcasm and incivility in Twitter discussions of climate change during an extreme weather event (n = 4,094). We found instances of incivility and sarcasm were low overall. Incivility was used in association with political topics, and both incivility and sarcasm were used alongside skeptical perspectives of climate change and by those who mention right-leaning politics in their profiles.},
	language = {EN},
	number = {5},
	urldate = {2025-04-13},
	journal = {Science Communication},
	author = {Anderson, Ashley A. and Huntington, Heidi E.},
	month = oct,
	year = {2017},
	pages = {598--620},
}

@article{antoci_civility_2016,
	title = {Civility vs. {Incivility} in {Online} {Social} {Interactions}: {An} {Evolutionary} {Approach}},
	volume = {11},
	issn = {1932-6203},
	shorttitle = {Civility vs. {Incivility} in {Online} {Social} {Interactions}},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0164286},
	doi = {10.1371/journal.pone.0164286},
	abstract = {Evidence is growing that forms of incivility–e.g. aggressive and disrespectful behaviors, harassment, hate speech and outrageous claims–are spreading in the population of social networking sites’ (SNS) users. Online social networks such as Facebook allow users to regularly interact with known and unknown others, who can behave either politely or rudely. This leads individuals not only to learn and adopt successful strategies for using the site, but also to condition their own behavior on that of others. Using a mean field approach, we define anevolutionary game framework to analyse the dynamics of civil and uncivil ways of interaction in online social networks and their consequences for collective welfare. Agents can choose to interact with others–politely or rudely–in SNS, or to opt out from online social networks to protect themselves from incivility. We find that, when the initial share of the population of polite users reaches a critical level, civility becomes generalized if its payoff increases more than that of incivility with the spreading of politeness in online interactions. Otherwise, the spreading of self-protective behaviors to cope with online incivility can lead the economyto non-socially optimal stationary states. JEL Codes: C61, C73, D85, O33, Z13. PsycINFO Codes: 2240, 2750.},
	language = {en},
	number = {11},
	urldate = {2025-04-13},
	journal = {PLOS ONE},
	author = {Antoci, Angelo and Delfino, Alexia and Paglieri, Fabio and Panebianco, Fabrizio and Sabatini, Fabio},
	month = nov,
	year = {2016},
	keywords = {Facebook, Facial expressions, Game theory, Human mobility, Internet, Social communication, Social networks, Social welfare},
	pages = {e0164286},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\MEMRGPPL\\Antoci et al. - 2016 - Civility vs. Incivility in Online Social Interactions An Evolutionary Approach.pdf:application/pdf},
}

@article{matamoros-fernandez_racism_2021,
	title = {Racism, {Hate} {Speech}, and {Social} {Media}: {A} {Systematic} {Review} and {Critique}},
	volume = {22},
	issn = {1527-4764},
	shorttitle = {Racism, {Hate} {Speech}, and {Social} {Media}},
	url = {https://doi.org/10.1177/1527476420982230},
	doi = {10.1177/1527476420982230},
	abstract = {Departing from Jessie Daniels’s 2013 review of scholarship on race and racism online, this article maps and discusses recent developments in the study of racism and hate speech in the subfield of social media research. Systematically examining 104 articles, we address three research questions: Which geographical contexts, platforms, and methods do researchers engage with in studies of racism and hate speech on social media? To what extent does scholarship draw on critical race perspectives to interrogate how systemic racism is (re)produced on social media? What are the primary methodological and ethical challenges of the field? The article finds a lack of geographical and platform diversity, an absence of researchers’ reflexive dialogue with their object of study, and little engagement with critical race perspectives to unpack racism on social media. There is a need for more thorough interrogations of how user practices and platform politics co-shape contemporary racisms.},
	language = {EN},
	number = {2},
	urldate = {2025-04-13},
	journal = {Television \& New Media},
	author = {Matamoros-Fernández, Ariadna and Farkas, Johan},
	month = feb,
	year = {2021},
	pages = {205--224},
	file = {SAGE PDF Full Text:C\:\\Users\\markj\\Zotero\\storage\\W33S49DX\\Matamoros-Fernández and Farkas - 2021 - Racism, Hate Speech, and Social Media A Systematic Review and Critique.pdf:application/pdf},
}

@article{goldenberg_digital_2020,
	title = {Digital {Emotion} {Contagion}},
	volume = {24},
	issn = {1364-6613, 1879-307X},
	url = {https://www.cell.com/trends/cognitive-sciences/abstract/S1364-6613(20)30027-9},
	doi = {10.1016/j.tics.2020.01.009},
	language = {English},
	number = {4},
	urldate = {2025-04-13},
	journal = {Trends in Cognitive Sciences},
	author = {Goldenberg, Amit and Gross, James J.},
	month = apr,
	year = {2020},
	pmid = {32160568},
	keywords = {digital media, emotion, emotion contagion, social media},
	pages = {316--328},
}

@book{papacharissi_affective_2014,
	title = {Affective {Publics}: {Sentiment}, {Technology}, and {Politics}},
	isbn = {978-0-19-999973-6},
	url = {https://doi.org/10.1093/acprof:oso/9780199999736.001.0001},
	abstract = {The past few decades have witnessed the growth of movements that use digital means to connect with broader publics and express their point of view. Social media facilitate feelings of engagement, in ways that frequently make people feel reenergized about what it means to be political. In doing so, media do not make or break revolutions but they do lend emerging, storytelling publics their own means for feeling their way into the developing event, frequently by making them a part of the developing story. Digital technologies network us but it is our stories that connect us to each other, making us feel close to some and distancing us from others. Affective Publics explores how storytelling practices on Twitter facilitate affective engagement for publics tuning into a current issue or event by employing three case studies: Arab Spring movements, various iterations of Occupy, and everyday casual political expressions as traced through the archives of trending topics on Twitter.},
	publisher = {Oxford University Press},
	author = {Papacharissi, Zizi},
	month = dec,
	year = {2014},
	doi = {10.1093/acprof:oso/9780199999736.001.0001},
}

@misc{saleem_web_2017,
	title = {A {Web} of {Hate}: {Tackling} {Hateful} {Speech} in {Online} {Social} {Spaces}},
	shorttitle = {A {Web} of {Hate}},
	url = {http://arxiv.org/abs/1709.10159},
	doi = {10.48550/arXiv.1709.10159},
	abstract = {Online social platforms are beset with hateful speech - content that expresses hatred for a person or group of people. Such content can frighten, intimidate, or silence platform users, and some of it can inspire other users to commit violence. Despite widespread recognition of the problems posed by such content, reliable solutions even for detecting hateful speech are lacking. In the present work, we establish why keyword-based methods are insufficient for detection. We then propose an approach to detecting hateful speech that uses content produced by self-identifying hateful communities as training data. Our approach bypasses the expensive annotation process often required to train keyword systems and performs well across several established platforms, making substantial improvements over current state-of-the-art approaches.},
	urldate = {2025-04-13},
	publisher = {arXiv},
	author = {Saleem, Haji Mohammad and Dillon, Kelly P. and Benesch, Susan and Ruths, Derek},
	month = sep,
	year = {2017},
	note = {arXiv:1709.10159 [cs]},
	keywords = {Computer Science - Computation and Language},
	annote = {Comment: 9 pages, presented at the first workshop on Text Analytics for Cybersecurity and Online Safety (TA-COS), collocated with LREC 2016},
	file = {Preprint PDF:C\:\\Users\\markj\\Zotero\\storage\\HANVGXF5\\Saleem et al. - 2017 - A Web of Hate Tackling Hateful Speech in Online Social Spaces.pdf:application/pdf;Snapshot:C\:\\Users\\markj\\Zotero\\storage\\27U2QAAA\\1709.html:text/html},
}

@misc{wulczyn_ex_2017,
	title = {Ex {Machina}: {Personal} {Attacks} {Seen} at {Scale}},
	shorttitle = {Ex {Machina}},
	url = {http://arxiv.org/abs/1610.08914},
	doi = {10.48550/arXiv.1610.08914},
	abstract = {The damage personal attacks cause to online discourse motivates many platforms to try to curb the phenomenon. However, understanding the prevalence and impact of personal attacks in online platforms at scale remains surprisingly difficult. The contribution of this paper is to develop and illustrate a method that combines crowdsourcing and machine learning to analyze personal attacks at scale. We show an evaluation method for a classifier in terms of the aggregated number of crowd-workers it can approximate. We apply our methodology to English Wikipedia, generating a corpus of over 100k high quality human-labeled comments and 63M machine-labeled ones from a classifier that is as good as the aggregate of 3 crowd-workers, as measured by the area under the ROC curve and Spearman correlation. Using this corpus of machine-labeled scores, our methodology allows us to explore some of the open questions about the nature of online personal attacks. This reveals that the majority of personal attacks on Wikipedia are not the result of a few malicious users, nor primarily the consequence of allowing anonymous contributions from unregistered users.},
	urldate = {2025-04-13},
	publisher = {arXiv},
	author = {Wulczyn, Ellery and Thain, Nithum and Dixon, Lucas},
	month = feb,
	year = {2017},
	note = {arXiv:1610.08914 [cs]},
	keywords = {Computer Science - Computation and Language},
	file = {Preprint PDF:C\:\\Users\\markj\\Zotero\\storage\\KGG7G5LK\\Wulczyn et al. - 2017 - Ex Machina Personal Attacks Seen at Scale.pdf:application/pdf;Snapshot:C\:\\Users\\markj\\Zotero\\storage\\XTPY254F\\1610.html:text/html},
}

@misc{noauthor_home_nodate,
	title = {Home {Page} {\textbar} {Kick} {It} {Out}},
	url = {https://www.kickitout.org/},
	urldate = {2025-04-13},
	file = {Home Page | Kick It Out:C\:\\Users\\markj\\Zotero\\storage\\QL8J73Q2\\www.kickitout.org.html:text/html},
}

@misc{noauthor_rainbow_nodate,
	title = {Rainbow {Laces}},
	url = {https://www.stonewall.org.uk/get-involved/support-us/rainbow-laces},
	abstract = {Rainbow Laces – the leading way to show support for LGBTQ+ inclusion in sport.},
	language = {en-GB},
	urldate = {2025-04-13},
	journal = {Stonewall},
	file = {Snapshot:C\:\\Users\\markj\\Zotero\\storage\\U7VX58Q2\\rainbow-laces.html:text/html},
}

@misc{beknazar-yuzbashev_toxic_2022,
	address = {Rochester, NY},
	type = {{SSRN} {Scholarly} {Paper}},
	title = {Toxic {Content} and {User} {Engagement} on {Social} {Media}: {Evidence} from a {Field} {Experiment}},
	shorttitle = {Toxic {Content} and {User} {Engagement} on {Social} {Media}},
	url = {https://papers.ssrn.com/abstract=4307346},
	doi = {10.2139/ssrn.4307346},
	abstract = {Most social media users have encountered harassment online, but there is scarce evidence of how this type of toxic content impacts engagement. In a pre-registered browser extension field experiment, we randomly hid toxic content for six weeks on Facebook, Twitter, and YouTube. Lowering exposure to toxicity reduced advertising impressions, time spent, and other measures of engagement, and reduced the toxicity of user-generated content. A survey experiment provides evidence that toxicity triggers curiosity and that engagement and welfare are not necessarily aligned. Taken together, our results suggest that platforms face a trade-off between curbing toxicity and increasing engagement.},
	language = {en},
	urldate = {2025-04-13},
	publisher = {Social Science Research Network},
	author = {Beknazar-Yuzbashev, George and Jiménez Durán, Rafael and McCrosky, Jesse and Stalinski, Mateusz},
	month = nov,
	year = {2022},
	keywords = {field experiment, hate speech, moderation, social media, toxic content, user engagement},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\RDTCIPCA\\Beknazar-Yuzbashev et al. - 2022 - Toxic Content and User Engagement on Social Media Evidence from a Field Experiment.pdf:application/pdf},
}

@article{milli_engagement_2025,
	title = {Engagement, user satisfaction, and the amplification of divisive content on social media},
	volume = {4},
	issn = {2752-6542},
	url = {https://doi.org/10.1093/pnasnexus/pgaf062},
	doi = {10.1093/pnasnexus/pgaf062},
	abstract = {Social media ranking algorithms typically optimize for users’ revealed preferences, i.e. user engagement such as clicks, shares, and likes. Many have hypothesized that by focusing on users’ revealed preferences, these algorithms may exacerbate human behavioral biases. In a preregistered algorithmic audit, we found that, relative to a reverse-chronological baseline, Twitter’s engagement-based ranking algorithm amplifies emotionally charged, out-group hostile content that users say makes them feel worse about their political out-group. Furthermore, we find that users do not prefer the political tweets selected by the algorithm, suggesting that the engagement-based algorithm underperforms in satisfying users’ stated preferences. Finally, we explore the implications of an alternative approach that ranks content based on users’ stated preferences and find a reduction in angry, partisan, and out-group hostile content, but also a potential reinforcement of proattitudinal content. Overall, our findings suggest that greater integration of stated preferences into social media ranking algorithms could promote better online discourse, though potential trade-offs also warrant further investigation.},
	number = {3},
	urldate = {2025-04-13},
	journal = {PNAS Nexus},
	author = {Milli, Smitha and Carroll, Micah and Wang, Yike and Pandey, Sashrika and Zhao, Sebastian and Dragan, Anca D},
	month = mar,
	year = {2025},
	pages = {pgaf062},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\TEJ93MFW\\Milli et al. - 2025 - Engagement, user satisfaction, and the amplification of divisive content on social media.pdf:application/pdf;Snapshot:C\:\\Users\\markj\\Zotero\\storage\\MQIWIY5P\\8052060.html:text/html},
}

@article{kramer_experimental_2014,
	title = {Experimental evidence of massive-scale emotional contagion through social networks},
	volume = {111},
	issn = {1091-6490},
	doi = {10.1073/pnas.1320040111},
	abstract = {Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. Emotional contagion is well established in laboratory experiments, with people transferring positive and negative emotions to others. Data from a large real-world social network, collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks [Fowler JH, Christakis NA (2008) BMJ 337:a2338], although the results are controversial. In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others' positive experiences constitutes a positive experience for people.},
	language = {eng},
	number = {24},
	journal = {Proceedings of the National Academy of Sciences of the United States of America},
	author = {Kramer, Adam D. I. and Guillory, Jamie E. and Hancock, Jeffrey T.},
	month = jun,
	year = {2014},
	pmid = {24889601},
	pmcid = {PMC4066473},
	keywords = {Affect, big data, computer-mediated communication, Emotions, Humans, Imitative Behavior, Internet, Social Behavior, Social Facilitation, social media, Social Support, Software, User-Computer Interface},
	pages = {8788--8790},
	file = {Full Text:C\:\\Users\\markj\\Zotero\\storage\\QJSVUQET\\Kramer et al. - 2014 - Experimental evidence of massive-scale emotional contagion through social networks.pdf:application/pdf},
}

@inproceedings{schmidt_survey_2017,
	address = {Valencia, Spain},
	title = {A {Survey} on {Hate} {Speech} {Detection} using {Natural} {Language} {Processing}},
	url = {https://aclanthology.org/W17-1101/},
	doi = {10.18653/v1/W17-1101},
	abstract = {This paper presents a survey on hate speech detection. Given the steadily growing body of social media content, the amount of online hate speech is also increasing. Due to the massive scale of the web, methods that automatically detect hate speech are required. Our survey describes key areas that have been explored to automatically recognize these types of utterances using natural language processing. We also discuss limits of those approaches.},
	urldate = {2025-04-13},
	booktitle = {Proceedings of the {Fifth} {International} {Workshop} on {Natural} {Language} {Processing} for {Social} {Media}},
	publisher = {Association for Computational Linguistics},
	author = {Schmidt, Anna and Wiegand, Michael},
	editor = {Ku, Lun-Wei and Li, Cheng-Te},
	month = apr,
	year = {2017},
	pages = {1--10},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\4V9H7TAT\\Schmidt and Wiegand - 2017 - A Survey on Hate Speech Detection using Natural Language Processing.pdf:application/pdf},
}

@article{torregrosa_survey_2023,
	title = {A survey on extremism analysis using natural language processing: definitions, literature review, trends and challenges},
	volume = {14},
	issn = {1868-5145},
	shorttitle = {A survey on extremism analysis using natural language processing},
	url = {https://doi.org/10.1007/s12652-021-03658-z},
	doi = {10.1007/s12652-021-03658-z},
	abstract = {Extremism has grown as a global problem for society in recent years, especially after the apparition of movements such as jihadism. This and other extremist groups have taken advantage of different approaches, such as the use of Social Media, to spread their ideology, promote their acts and recruit followers. The extremist discourse, therefore, is reflected on the language used by these groups. Natural language processing (NLP) provides a way of detecting this type of content, and several authors make use of it to describe and discriminate the discourse held by these groups, with the final objective of detecting and preventing its spread. Following this approach, this survey aims to review the contributions of NLP to the field of extremism research, providing the reader with a comprehensive picture of the state of the art of this research area. The content includes a first conceptualization of the term extremism, the elements that compose an extremist discourse and the differences with other terms. After that, a review description and comparison of the frequently used NLP techniques is presented, including how they were applied, the insights they provided, the most frequently used NLP software tools, descriptive and classification applications, and the availability of datasets and data sources for research. Finally, research questions are approached and answered with highlights from the review, while future trends, challenges and directions derived from these highlights are suggested towards stimulating further research in this exciting research area.},
	language = {en},
	number = {8},
	urldate = {2025-04-13},
	journal = {Journal of Ambient Intelligence and Humanized Computing},
	author = {Torregrosa, Javier and Bello-Orgaz, Gema and Martínez-Cámara, Eugenio and Ser, Javier Del and Camacho, David},
	month = aug,
	year = {2023},
	keywords = {Artificial Intelligence, Deep learning, Extremism, Machine learning, Natural language processing, Radicalization},
	pages = {9869--9905},
	file = {Full Text PDF:C\:\\Users\\markj\\Zotero\\storage\\32QVGNL7\\Torregrosa et al. - 2023 - A survey on extremism analysis using natural language processing definitions, literature review, tr.pdf:application/pdf},
}

@article{ayo_machine_2020,
	title = {Machine learning techniques for hate speech classification of twitter data: {State}-of-the-art, future challenges and research directions},
	volume = {38},
	issn = {1574-0137},
	shorttitle = {Machine learning techniques for hate speech classification of twitter data},
	url = {https://www.sciencedirect.com/science/article/pii/S1574013720304111},
	doi = {10.1016/j.cosrev.2020.100311},
	abstract = {Twitter is a microblogging tool that allow the creation of big data through short digital contents. This study provides a survey of machine learning techniques for hate speech classification from Twitter data streams. Hate speech classification in Twitter data streams has remain a vibrant research focus, but little research efforts have been devoted to the design of a generic metadata architecture, threshold settings and fragmentation issues. Hate speech classification techniques presented in literature address some of the challenges inherent in Twitter data streams but limited in the aforementioned issues. This study presented collection of hate speech benchmarks datasets suitable for testing the efficiency of classification models. This study also presented the pros and cons for single and hybrid machine learning methods in hate speech classification. The summary of performance evaluation for the surveyed machine learning methods was also presented. The study also presented a generic metadata architecture for hate speech classification in Twitter to tackle issues with Twitter data streams. The developed generic metadata architecture was observed to performed better across all evaluation metrics for hate speech detection having 0.95, 0.93, 0.92 and 0.93 for accuracy, precision, recall and F1-score respectively, when compared to similar methods. Similarly, the developed generic metadata architecture for hate speech sentiment classification performed better with F1-score of 91.5\% compared to related methods. The developed generic metadata architecture also indicates a more perfect test having an AUC of 0.97, when compared to similar methods. The statistical validation of results points out the efficiency of the developed system. Finally, the results also showed that the developed system is very good for automatic topic detection and categorization.},
	urldate = {2025-04-13},
	journal = {Computer Science Review},
	author = {Ayo, Femi Emmanuel and Folorunso, Olusegun and Ibharalu, Friday Thomas and Osinuga, Idowu Ademola},
	month = nov,
	year = {2020},
	keywords = {Bayesian network, Combinatorial algorithm, Detection, Fuzzy logic, Hate speech, Twitter data stream},
	pages = {100311},
	file = {ScienceDirect Snapshot:C\:\\Users\\markj\\Zotero\\storage\\722SGLIS\\S1574013720304111.html:text/html},
}

@misc{lees_new_2022,
	title = {A {New} {Generation} of {Perspective} {API}: {Efficient} {Multilingual} {Character}-level {Transformers}},
	shorttitle = {A {New} {Generation} of {Perspective} {API}},
	url = {http://arxiv.org/abs/2202.11176},
	doi = {10.48550/arXiv.2202.11176},
	abstract = {On the world wide web, toxic content detectors are a crucial line of defense against potentially hateful and offensive messages. As such, building highly effective classifiers that enable a safer internet is an important research area. Moreover, the web is a highly multilingual, cross-cultural community that develops its own lingo over time. As such, it is crucial to develop models that are effective across a diverse range of languages, usages, and styles. In this paper, we present the fundamentals behind the next version of the Perspective API from Google Jigsaw. At the heart of the approach is a single multilingual token-free Charformer model that is applicable across a range of languages, domains, and tasks. We demonstrate that by forgoing static vocabularies, we gain flexibility across a variety of settings. We additionally outline the techniques employed to make such a byte-level model efficient and feasible for productionization. Through extensive experiments on multilingual toxic comment classification benchmarks derived from real API traffic and evaluation on an array of code-switching, covert toxicity, emoji-based hate, human-readable obfuscation, distribution shift, and bias evaluation settings, we show that our proposed approach outperforms strong baselines. Finally, we present our findings from deploying this system in production.},
	urldate = {2025-04-13},
	publisher = {arXiv},
	author = {Lees, Alyssa and Tran, Vinh Q. and Tay, Yi and Sorensen, Jeffrey and Gupta, Jai and Metzler, Donald and Vasserman, Lucy},
	month = feb,
	year = {2022},
	note = {arXiv:2202.11176 [cs]},
	keywords = {Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computers and Society, Computer Science - Machine Learning},
	file = {Preprint PDF:C\:\\Users\\markj\\Zotero\\storage\\IKLD65ZC\\Lees et al. - 2022 - A New Generation of Perspective API Efficient Multilingual Character-level Transformers.pdf:application/pdf;Snapshot:C\:\\Users\\markj\\Zotero\\storage\\7L4WSVN8\\2202.html:text/html},
}

@misc{pavlopoulos_toxicity_2020,
	title = {Toxicity {Detection}: {Does} {Context} {Really} {Matter}?},
	shorttitle = {Toxicity {Detection}},
	url = {http://arxiv.org/abs/2006.00998},
	doi = {10.48550/arXiv.2006.00998},
	abstract = {Moderation is crucial to promoting healthy on-line discussions. Although several `toxicity' detection datasets and models have been published, most of them ignore the context of the posts, implicitly assuming that comments maybe judged independently. We investigate this assumption by focusing on two questions: (a) does context affect the human judgement, and (b) does conditioning on context improve performance of toxicity detection systems? We experiment with Wikipedia conversations, limiting the notion of context to the previous post in the thread and the discussion title. We find that context can both amplify or mitigate the perceived toxicity of posts. Moreover, a small but significant subset of manually labeled posts (5\% in one of our experiments) end up having the opposite toxicity labels if the annotators are not provided with context. Surprisingly, we also find no evidence that context actually improves the performance of toxicity classifiers, having tried a range of classifiers and mechanisms to make them context aware. This points to the need for larger datasets of comments annotated in context. We make our code and data publicly available.},
	urldate = {2025-04-13},
	publisher = {arXiv},
	author = {Pavlopoulos, John and Sorensen, Jeffrey and Dixon, Lucas and Thain, Nithum and Androutsopoulos, Ion},
	month = jun,
	year = {2020},
	note = {arXiv:2006.00998 [cs]},
	keywords = {Computer Science - Computation and Language},
	file = {Preprint PDF:C\:\\Users\\markj\\Zotero\\storage\\NY5Z5QPE\\Pavlopoulos et al. - 2020 - Toxicity Detection Does Context Really Matter.pdf:application/pdf;Snapshot:C\:\\Users\\markj\\Zotero\\storage\\SL3GLDJW\\2006.html:text/html},
}

@misc{LDNOOBW2025,
  author = {{LDNOOBW}},
  title = {List of Dirty, Naughty, Obscene, and Otherwise Bad Words},
  year = {2025},
  note = {GitHub repository},
  url = {https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words},
  urldate = {2025-04-13}
}

@misc{nicholas22aira,
  doi = {10.5281/zenodo.6989727},
  url = {https://github.com/Nkluge-correa/Aira},
  author = {Nicholas Kluge Corrêa},
  title = {Aira},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
}

@article{onwe2016involuntary,
  title={Involuntary emotions: Exploring the experiences of winning and losing on sport fans},
  author={Onwe, John Obinna},
  journal={International Journal of Sport Studies},
  volume={6},
  pages={136--146},
  year={2016}
}

@article{Roy_2001,
author = {Roy F. Baumeister and Ellen Bratslavsky and Catrin Finkenauer and Kathleen D. Vohs},
title ={Bad is Stronger than Good},

journal = {Review of General Psychology},
volume = {5},
number = {4},
pages = {323-370},
year = {2001},
doi = {10.1037/1089-2680.5.4.323},

URL = { 
    
        https://doi.org/10.1037/1089-2680.5.4.323

},
eprint = { 
    
        https://doi.org/10.1037/1089-2680.5.4.323

}
,
    abstract = { The greater power of bad events over good ones is found in everyday events, major life events (e.g., trauma), close relationship outcomes, social network patterns, interpersonal interactions, and learning processes. Bad emotions, bad parents, and bad feedback have more impact than good ones, and bad information is processed more thoroughly than good. The self is more motivated to avoid bad self-definitions than to pursue good ones. Bad impressions and bad stereotypes are quicker to form and more resistant to disconfirmation than good ones. Various explanations such as diagnosticity and salience help explain some findings, but the greater power of bad events is still found when such variables are controlled. Hardly any exceptions (indicating greater power of good) can be found. Taken together, these findings suggest that bad is stronger than good, as a general principle across a broad range of psychological phenomena. }
}

@article{Brady_2017,
author = {William J. Brady  and Julian A. Wills  and John T. Jost  and Joshua A. Tucker  and Jay J. Van Bavel },
title = {Emotion shapes the diffusion of moralized content in social networks},
journal = {Proceedings of the National Academy of Sciences},
volume = {114},
number = {28},
pages = {7313-7318},
year = {2017},
doi = {10.1073/pnas.1618923114},
URL = {https://www.pnas.org/doi/abs/10.1073/pnas.1618923114},
eprint = {https://www.pnas.org/doi/pdf/10.1073/pnas.1618923114},
abstract = {Twitter and other social media platforms are believed to have altered the course of numerous historical events, from the Arab Spring to the US presidential election. Online social networks have become a ubiquitous medium for discussing moral and political ideas. Nevertheless, the field of moral psychology has yet to investigate why some moral and political ideas spread more widely than others. Using a large sample of social media communications concerning polarizing issues in public policy debates (gun control, same-sex marriage, climate change), we found that the presence of moral-emotional language in political messages substantially increases their diffusion within (and less so between) ideological group boundaries. These findings offer insights into how moral ideas spread within networks during real political discussion. Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call “moral contagion.” Using a large sample of social media communications about three polarizing moral/political issues (n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20\% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks.}}

@article{Woods_2022,
author = {James Woods and Jan Andre Lee Ludvigsen},
title = {The changing faces of fandom? Exploring emerging ‘online’ and ‘offline’ fandom spaces in the English Premier League},
journal = {Sport in Society},
volume = {25},
number = {11},
pages = {2234--2249},
year = {2022},
publisher = {Routledge},
doi = {10.1080/17430437.2021.1904902},


URL = { 
    
        https://doi.org/10.1080/17430437.2021.1904902
    
    

},
eprint = { 
    
        https://doi.org/10.1080/17430437.2021.1904902
    
    

}

}


@book{cleland_collective_2018,
	address = {Cham},
	title = {Collective {Action} and {Football} {Fandom}},
	copyright = {http://www.springer.com/tdm},
	isbn = {978-3-319-73140-7 978-3-319-73141-4},
	url = {http://link.springer.com/10.1007/978-3-319-73141-4},
	language = {en},
	urldate = {2025-04-15},
	publisher = {Springer International Publishing},
	author = {Cleland, Jamie and Doidge, Mark and Millward, Peter and Widdop, Paul},
	year = {2018},
	doi = {10.1007/978-3-319-73141-4},
	keywords = {Activism, English football, Social movement, Social network, Sport studies},
	file = {Submitted Version:C\:\\Users\\markj\\Zotero\\storage\\U7RXZPNA\\Cleland et al. - 2018 - Collective Action and Football Fandom.pdf:application/pdf},
}
