% Use this file for citations not found in the ACL Anthology (contained in "anthology.bib").

 @article{Greenberg_1956, title={The Measurement of Linguistic Diversity}, volume={32}, ISSN={0097-8507}, DOI={10.2307/410659}, number={1}, journal={Language}, publisher={Linguistic Society of America}, author={Greenberg, Joseph H.}, year={1956}, pages={109–115} }

 @article{Grin_Fürst_2022, title={Measuring Linguistic Diversity: A Multi-level Metric}, volume={164}, ISSN={1573-0921}, DOI={10.1007/s11205-022-02934-5}, abstractNote={This paper proposes a novel approach to the measurement of linguistic diversity. Drawing on the ecological literature, it proposes an adaptation to languages of the classic distinction between “alpha” (intra-setting), “beta” (inter-setting) and “gamma” (system-level) diversity. We begin by discussing some of the general challenges raised by the measurement of diversity. We review received approaches to the measurement of diversity resting on the concepts of richness and evenness, highlighting some limitations that come to the fore when comparing the respective diversity of different settings and systems. In order to overcome some of these limitations, we adapt the concept of “numbers equivalent” to linguistic diversity measurement indices. On this basis, we derive a multi-level approach to diversity measurement. We provide numerical examples to highlight the properties of this model before discussing its application to language policy issues.}, number={2}, journal={Social Indicators Research}, author={Grin, François and Fürst, Guillaume}, year={2022}, month=nov, pages={601–621}, language={en} }


 @article{Civico, title={Measuring Linguistic Diversity: Limits and Extensions of the Greenberg Index}, volume={0}, ISSN={0929-6174}, DOI={10.1080/09296174.2025.2567699}, abstractNote={This theoretical paper proposes a refined framework for measuring linguistic diversity in multilingual societies, with a focus on the Greenberg Diversity Index (GDI), a widely used indicator based on the probability that two randomly selected individuals speak different languages. After deriving exact upper and lower bounds for GDI under varying language distributions, the paper introduces several theoretical extensions that capture more realistic sociolinguistic configurations. These include competence-weighted indices to account for individual multilingualism, co-competence matrices to model overlapping language repertoires, distance-weighted formulations based on interlinguistic similarity, and entropy-based metrics that reflect the unpredictability of language identity. Each index is analysed in terms of its mathematical structure, interpretability, and alignment with different types of linguistic data. A comparative framework is proposed to support the selection and interpretation of these metrics across research and policy applications. Together, these contributions advance the quantitative modelling of linguistic diversity and offer tools for more nuanced sociolinguistic analysis.}, number={0}, journal={Journal of Quantitative Linguistics}, publisher={Routledge}, author={Civico, Marco}, pages={1–28}, year = {2025} }


 @article{Ginsburgh_Weber_2020, title={The Economics of Language}, volume={58}, ISSN={0022-0515}, abstractNote={This paper brings together methodological, theoretical, and empirical analysis into the framework of linguistic diversity. It reflects both historical and contemporary research by economists and other social scientists on the impact of language on economic outcomes and public policies. We examine whether and how language influences human thinking (including emotions) and behavior, and analyze the effects of linguistic distances on trade, migrations, financial markets, language learning, and its returns. The quantitative foundations of linguistic diversity, which rely on group identification, linguistic distances as well as fractionalization, polarization, and disenfranchisement indices are discussed in terms of their empirical challenges and uses. We conclude with an analysis of linguistic policies and examine the trade-offs between the development of labor markets and the social costs that they generate in various countries.}, number={2}, journal={Journal of Economic Literature}, publisher={American Economic Association}, author={Ginsburgh, Victor and Weber, Shlomo}, year={2020}, pages={348–404} }



 @article{Bromham_2023, title={Language endangerment: Using analytical methods from conservation biology to illuminate loss of linguistic diversity}, volume={1}, rights={http://creativecommons.org/licenses/by/4.0}, ISSN={2755-0958}, DOI={10.1017/ext.2022.3}, abstractNote={Abstract
            Language diversity is under threat, with between a third to a half of all languages considered endangered, and predicted rates of loss equivalent to one language per month for the rest of the century. Rather than reviewing the extensive body of linguistic research on endangered languages, this review focuses specifically on the interdisciplinary transfer of methods developed in conservation biology, macroecology and macroevolution to the study of language endangerment and loss. While the causes of language endangerment and loss are different to those for species, studying patterns of diversity of species and languages involves similar analytical challenges, associated with testing hypotheses and identifying causal relationships. Solutions developed in biology can be adapted to illuminate patterns in language endangerment, such as statistical methods that explicitly model phylogenetic nonindependence, spatial autocorrelation and covariation between variables, which may otherwise derail the search for meaningful predictors of language endangerment. However, other tools from conservation biology may be much less use in understanding or predicting language endangerment, such as metrics based on International Union for Conservation of Nature (IUCN) criteria, population viability analysis or niche modelling. This review highlights both the similarities and the differences in approaches to understanding the concurrent crises in loss of both linguistic diversity and biodiversity.}, journal={Cambridge Prisms: Extinction}, author={Bromham, Lindell}, year={2023}, pages={e3}, language={en} }


 @article{Marsh_Vallejos_Spence_2022, title={The digital workplace and its dark side: An integrative review}, volume={128}, ISSN={0747-5632}, DOI={10.1016/j.chb.2021.107118}, abstractNote={An intensification of digital working driven by Covid-19 has brought into sharp focus both the beneficial nature of digital workplace technologies and their potential dark side. Research has burgeoned in this area in recent years, but an integrated view across fields, technologies, dark side effects and outcomes is lacking. There are potential insights to be gained from compiling and comparing results and theoretical approaches. Following integrative review procedures, 194 studies were analysed to understand unintended negative consequences of a range of workplace technologies across disciplines and methodologies. The results demonstrate that considerable insight has been uncovered regarding certain dark side effects, stress in particular, in relation to e-mail and smartphones. However, a broader view of how they might manifest in relation to employees’ holistic digital experience of work beyond certain information and communication technologies (ICTs) is lacking, including a clear picture of objective demands of the technology with which these effects are associated. Much remains to be understood across the full range of dark side effects in relation to the digital workplace including the associations between them and how they relate to cognitive and affective outcomes. The importance of both theoretical rigour and diversity is highlighted.}, journal={Computers in Human Behavior}, author={Marsh, Elizabeth and Vallejos, Elvira Perez and Spence, Alexa}, year={2022}, month=mar, pages={107118} }


 @inproceedings{Benson_Zeh_Essfors_Fellner_Neidhardt_Baumann_2025, address={Berlin, Heidelberg}, title={Linguistic Diversity and Digitalization: An Ambivalent Relationship}, ISBN={978-3-032-11107-4}, url={https://doi.org/10.1007/978-3-032-11108-1_26}, DOI={10.1007/978-3-032-11108-1_26}, abstractNote={In this position paper, we argue that while digitalization amplifies biases towards only few languages dominating the linguistic landscape, modern language technology can help to mitigate language loss. We first elaborate on how the linguistic landscape in the digital and the non-digital sphere are distributionally different from each other in that the latter is strongly biased towards English, at the same time under-representing thousands of languages and the cultural knowledge that they encode. In a second step, we present results of qualitative interviews on individual linguistic experiences in the digital and the non-digital sphere that we have conducted in Québec, one of the provinces of Canada known for its linguistic diversity. These interviews highlight the potential that modern language technology have for safeguarding linguistic diversity. We conclude that the study of the impact of digitalization on the global linguistic landscape not only requires differential ways of measuring linguistic diversity but also a nuanced operationalization of digitalization.}, booktitle={Digital Humanism: First Interdisciplinary Science and Research Conference, DIGHUM 2025, Vienna, Austria, November 20–21, 2025, Proceedings}, publisher={Springer-Verlag}, author={Benson, Juliane and Zeh, Katharina and Essfors, Hannes and Fellner, Hannes and Neidhardt, Julia and Baumann, Andreas}, year={2025}, month=nov, pages={358–365} }


@misc{statista2025digitalpopulation,
  author       = {{Statista}},
  title        = {Internet and social media users in the world 2025},
  howpublished = {\url{https://www.statista.com/statistics/617136/digital-population-worldwide/}},
  year         = {2025},
  note         = {Accessed: 2025-12-17},
  month        = feb,
}

 @article{Hiippala_Hausmann_Tenkanen_Toivonen_2019, title={Exploring the linguistic landscape of geotagged social media content in urban environments}, volume={34}, ISSN={2055-7671}, DOI={10.1093/llc/fqy049}, abstractNote={This article explores the linguistic landscape of social media posts associated with specific geographic locations using computational methods. Because physical and virtual spaces have become increasingly intertwined due to location-aware mobile devices, we propose extending the concept of linguistic landscape to cover both physical and virtual environments. To cope with the high volume of social media data, we adopt computational methods for studying the richness and diversity of the virtual linguistic landscape, namely, automatic language identification and topic modelling, together with diversity indices commonly used in ecology and information sciences. We illustrate the proposed approach in a case study covering nearly 120,000 posts uploaded on Instagram over 4.5 years at the Senate Square in Helsinki, Finland. Our analysis reveals the richness and diversity of the virtual linguistic landscape, which is also shown to be susceptible to continuous change.}, number={2}, journal={Digital Scholarship in the Humanities}, author={Hiippala, Tuomo and Hausmann, Anna and Tenkanen, Henrikki and Toivonen, Tuuli}, year={2019}, month=june, pages={290–309} }

 @inproceedings{Gaspari_Gallagher_Rehm_Giagkou_Piperidis_Dunne_Way_2022, address={Marseille, France}, title={Introducing the Digital Language Equality Metric: Technological Factors}, url={https://aclanthology.org/2022.tdle-1.1/}, abstractNote={This paper introduces the concept of Digital Language Equality (DLE) developed by the EU-funded European Language Equality (ELE) project, and describes the associated DLE Metric with a focus on its technological factors (TFs), which are complemented by situational contextual factors. This work aims at objectively describing the level of technological support of all European languages and lays the foundation to implement a large-scale EU-wide programme to ensure that these languages can continue to exist and prosper in the digital age, to serve the present and future needs of their speakers. The paper situates this ongoing work with a strong European focus in the broader context of related efforts, and explains how the DLE Metric can help track the progress towards DLE for all languages of Europe, focusing in particular on the role played by the TFs. These are derived from the European Language Grid (ELG) Catalogue, that provides the empirical basis to measure the level of digital readiness of all European languages. The DLE Metric scores can be consulted through an online interactive dashboard to show the level of technological support of each European language and track the overall progress toward DLE.}, booktitle={Proceedings of the Workshop Towards Digital Language Equality within the 13th Language Resources and Evaluation Conference}, publisher={European Language Resources Association}, author={Gaspari, Federico and Gallagher, Owen and Rehm, Georg and Giagkou, Maria and Piperidis, Stelios and Dunne, Jane and Way, Andy}, editor={Aldabe, Itziar and Altuna, Begoña and Farwell, Aritz and Rigau, German}, year={2022}, month=june, pages={1–12} }

 @inproceedings{Grutzner-Zahn_Rehm_2022, address={Marseille, France}, title={Introducing the Digital Language Equality Metric: Contextual Factors}, url={https://aclanthology.org/2022.tdle-1.2/}, abstractNote={In our digital age, digital language equality is an important goal to enable participation in society for all citizens, independent of the language they speak. To assess the current state of play with regard to Europe’s languages, we developed, in the project European Language Equality, a metric for digital language equality that consists of two parts, technological and contextual (i.e., non-technological) factors. We present a metric for calculating the contextual factors for over 80 European languages. For each language, a score is calculated that reflects the broader context or socio-economic ecosystem of a language, which has, for a given language, a direct impact for technology and resource development; it is important to note, though, that Language Technologies and Resources related aspects are reflected by the technological factors. To reduce the vast number of potential contextual factors to an adequate number, five different configurations were calculated and evaluated with a panel of experts. The best results were achieved by a configuration in which 12 manually curated factors were included. In the factor selection process, attention was paid to data quality, automatic updatability, inclusion of data from different domains, and a balance between different data types. The evaluation shows that this specific configuration is stable for the official EU languages; while for regional and minority languages, as well as national non-official EU languages, there is room for improvement.}, booktitle={Proceedings of the Workshop Towards Digital Language Equality within the 13th Language Resources and Evaluation Conference}, publisher={European Language Resources Association}, author={Grützner-Zahn, Annika and Rehm, Georg}, editor={Aldabe, Itziar and Altuna, Begoña and Farwell, Aritz and Rigau, German}, year={2022}, month=june, pages={13–26} }


 @article{Hiippala_Väisänen_Toivonen_Järv_2020, title={Mapping the languages of Twitter in Finland:: Richness and diversity in space and time}, volume={121}, rights={Copyright (c) 2021 The Modern Language Society, Helsinki}, ISSN={2736-9714}, DOI={10.51814/nm.99996}, abstractNote={Twitter is a popular social media platform for scholarly research, because the user-generated content on the platform can also include geographic and temporal information. We collect a corpus of 38 million Twitter messages with two million geographical coordinates to map the languages used across Finland at the level of regions and municipalities. To cope with the high volume of social media data, we use automatic language identiﬁcation and place of residence detection. We estimate the linguistic richness and diversity of users and locations using measures developed within ecology and information sciences. The analyses reveal a rich, multilingual environment that varies geographically and temporally, particularly between coastal, rural and urban areas. The results, which underline the mutual beneﬁts of collaboration between linguists and geographers, provide a more ﬁne-grained, accurate and comprehensive view of the languages used on Twitter in Finland than previously available.}, number={11}, journal={Neuphilologische Mitteilungen}, author={Hiippala, Tuomo and Väisänen, Tuomas and Toivonen, Tuuli and Järv, Olle}, year={2020}, month=nov, pages={12–44}, language={en} }

 @article{Väisänen_Järv_Toivonen_Hiippala_2022, title={Mapping urban linguistic diversity with social media and population register data}, volume={97}, ISSN={0198-9715}, DOI={10.1016/j.compenvurbsys.2022.101857}, abstractNote={Globalization, urbanization and international mobility have led to increasingly diverse urban populations. Compared to traditional traits for measuring urban diversity, such as ethnicity and country of origin, the role of language remains underexplored in understanding diversity, interactions between different groups and socio-spatial segregation. In this article, we analyse language use in the Helsinki Metropolitan Area by combining individual-level register data, socio-economic grid database, mobile phone and social media data to understand spatio-temporal patterns of linguistic diversity better. We measured linguistic diversity using metrics developed in the fields of ecology and information theory, and performed spatial clustering and regression analyses to explore the spatio-temporal patterns of linguistic diversity. We found spatial and temporal differences between register and social media data, show that linguistic diversity is influenced by the physical and socio-economic environment, and identified areas where different linguistic groups are likely to interact. Our results provide insights for urban planning and understanding urban diversity through linguistic information. As global urbanization, international migration and refugee flows and climate change drive diverse populations into cities, understanding urban diversity and its implications for urban planning and sustainability become increasingly important.}, journal={Computers, Environment and Urban Systems}, author={Väisänen, Tuomas and Järv, Olle and Toivonen, Tuuli and Hiippala, Tuomo}, year={2022}, month=oct, pages={101857} }

 @article{Alshaabi_Dewhurst_Minot_Arnold_Adams_Danforth_Dodds_2021, title={The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009–2020}, volume={10}, rights={2021 The Author(s)}, ISSN={2193-1127}, DOI={10.1140/epjds/s13688-021-00271-0}, abstractNote={Working from a dataset of 118 billion messages running from the start of 2009 to the end of 2019, we identify and explore the relative daily use of over 150 languages on Twitter. We find that eight languages comprise 80% of all tweets, with English, Japanese, Spanish, Arabic, and Portuguese being the most dominant. To quantify social spreading in each language over time, we compute the ‘contagion ratio’: The balance of retweets to organic messages. We find that for the most common languages on Twitter there is a growing tendency, though not universal, to retweet rather than share new content. By the end of 2019, the contagion ratios for half of the top 30 languages, including English and Spanish, had reached above 1—the naive contagion threshold. In 2019, the top 5 languages with the highest average daily ratios were, in order, Thai (7.3), Hindi, Tamil, Urdu, and Catalan, while the bottom 5 were Russian, Swedish, Esperanto, Cebuano, and Finnish (0.26). Further, we show that over time, the contagion ratios for most common languages are growing more strongly than those of rare languages.}, number={1}, journal={EPJ Data Science}, publisher={SpringerOpen}, author={Alshaabi, Thayer and Dewhurst, David Rushing and Minot, Joshua R. and Arnold, Michael V. and Adams, Jane L. and Danforth, Christopher M. and Dodds, Peter Sheridan}, year={2021}, month=dec, pages={1–28}, language={en} }


 @article{Couldry_Meijas_2019, 
 author  = {Mejias, Ulises A. and Couldry, Nick},
  title   = {Datafication},
  journal = {Internet Policy Review},
  year    = {2019},
  volume  = {8},
  number  = {4},
  doi     = {10.14763/2019.4.1428},
  url     = {https://doi.org/10.14763/2019.4.1428}
}


 @inbook{Flyverbom_2019, address={Cambridge}, title={Digital and Datafied Spaces}, ISBN={978-1-107-13081-4}, url={https://www.cambridge.org/core/books/digital-prism/digital-and-datafied-spaces/DC0E9CBC81386B9E65918C8BD3417F2A}, DOI={10.1017/9781316442692.002}, abstractNote={Promises of technological progress have always intrigued humankind. Throughout history, people have imagined what they could accomplish with stronger tools, faster machines and more advanced technologies. Such hopes about technological transformations continue to shape most domains of life, from economies and production over social relations to politics and knowledge. The hopes associated with contemporary digital transformations are no exception. The internet and mobile technologies make it easier than ever to find information and communicate. Big data gives us direct, precise insights into all aspects of human life. Right around the corner, artificial intelligence may lead to faster and smarter decision-making. While we often experience that the reality of such developments is more complicated, most technological revolutions are welcomed with the same kind of enthusiasm (Marvin, 1988). Likewise, many companies and other organizations scramble to stay up to speed and fear falling behind the pace of technology while they are busy attending to the core of their work. As a result, most organizations contain departments and people who are on completely different pages when it comes to understanding and working with digital transformations. That is, organizations are simultaneously doing some things in very handheld ways, relying on digital technologies for a wide range of activities and experimenting with big data or artificial intelligence in some parts.}, booktitle={The Digital Prism: Transparency and Managed Visibilities in a Datafied World}, publisher={Cambridge University Press}, year={2019}, pages={25–38}, author = {Flyverbom, Mikkel} }


 @article{Blakey_2024, title={The Day Data Transparency Died: How Twitter/X Cut Off Access for Social Research}, volume={23}, ISSN={1536-5042}, DOI={10.1177/15365042241252125}, abstractNote={For 17 years, Twitter/X provided free academic access—not by law, but by social contract—to its data for researchers examining elections, hate speech, and other crucial public issues. It took just six months under Elon Musk to rescind this unfettered access and upend global scholarship.}, number={2}, journal={Contexts}, publisher={SAGE Publications}, author={Blakey, Elizabeth}, year={2024}, month=may, pages={30–35}, language={EN} }


 @article{Jauhiainen_Lui_Zampieri_Baldwin_Lindén_2019, title={Automatic Language Identification in Texts: A Survey}, volume={65}, rights={Copyright (c)}, ISSN={1076-9757}, DOI={10.1613/jair.1.11675}, abstractNote={Language identification (“LI”) is the problem of determining the natural language that a document or part thereof is written in. Automatic LI has been extensively researched for over fifty years. Today, LI is a key part of many text processing pipelines, as text processing techniques generally assume that the language of the input text is known. Research in this area has recently been especially active. This article provides a brief history of LI research, and an extensive survey of the features and methods used in the LI literature. We describe the features and methods using a unified notation, to make the relationships between methods clearer. We discuss evaluation methods, applications of LI, as well as off-the-shelfLI systems that do not require training by the end user. Finally, we identify open issues, survey the work to date on each issue, and propose future directions for research in LI.}, journal={Journal of Artificial Intelligence Research}, author={Jauhiainen, Tommi and Lui, Marco and Zampieri, Marcos and Baldwin, Timothy and Lindén, Krister}, year={2019}, month=aug, pages={675–782}, language={en} }


@inproceedings{pfeffer2023justdaytwittercomplete,
  author    = {Pfeffer, Jeffrey and Matter, Daniel and Jaidka, Kokil and Varol, Onur and Mashhadi, Anahita and Lasser, Jonas and Assenmacher, Dominik and Wu, Shuhan and Yang, Dejing and Brantner, Christoph and Romero, Daniel M. and Otterbacher, Jan and Schwemmer, Christian and Joseph, Kiran and Garcia, David and Morstatter, Fred},
  title     = {Just Another Day on Twitter: A Complete 24 Hours of Twitter Data},
  booktitle = {Proceedings of the International AAAI Conference on Web and Social Media},
  year      = {2023},
  volume    = {17},
  number    = {1},
  pages     = {1073--1081},
  doi       = {10.1609/icwsm.v17i1.22215},
  url       = {https://doi.org/10.1609/icwsm.v17i1.22215}
}


 @inproceedings{Magdy_Ghanem_Musleh_Mokbel_2014, address={New York, NY, USA}, series={GeoRich’14}, title={Exploiting Geo-tagged Tweets to Understand Localized Language Diversity}, ISBN={978-1-4503-2978-1}, url={https://dl.acm.org/doi/10.1145/2619112.2619114}, DOI={10.1145/2619112.2619114}, abstractNote={Social media services are the top-growing online communities in the last few years. Among those, Twitter becomes the de facto of microblogging services with millions of tweets posted everyday. In this paper, we present an analytical study for localized language usage and diversity in Twitter data using a half billion geotagged tweets. We first identify local Twitter communities on a country-level. For the identified communities, we examine (1) the language diversity, (2) the language dominance within the community and how this differs from local to global views, (3) demographics representativeness of tweets for real population demographics, and (4) the spatial distribution of different cultural groups within the countries. To this end, we group the tweets on two levels. First, we group tweets per country to identify the local communities. Second, we group tweets within each local community based on the tweet language. Our study shows useful insights about language usage on Twitter which provide important information for language-based applications on top of Twitter data, e.g., lingual analysis and disaster management. In addition, we present an interactive exploration tool for the spatial distribution of cultural groups, which provides a low-effort and high-precision localization of different cultural groups inside a certain country.}, booktitle={Proceedings of Workshop on Managing and Mining Enriched Geo-Spatial Data}, publisher={Association for Computing Machinery}, author={Magdy, Amr and Ghanem, Thanaa M. and Musleh, Mashaal and Mokbel, Mohamed},
year = {2014}}


@misc{statista2025_mostvisited,
  title        = {Most visited websites worldwide},
  author       = {{Statista}},
  year         = {2025},
  howpublished = {https://www.statista.com/statistics/1201880/most-visited-websites-worldwide/},
  note         = {Statistic on global website visits, based on data from November 2024; accessed 2025-20-12},
}


@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2025},
    url = {https://www.R-project.org/},
  }


@Manual{httr,
    title = {httr: Tools for Working with URLs and HTTP},
    author = {Hadley Wickham},
    year = {2023},
    note = {R package version 1.4.7},
    url = {https://CRAN.R-project.org/package=httr},
    doi = {10.32614/CRAN.package.httr},
  }

@misc{wikitechAQSPageviewsPerProject2024,
  title        = {Data Platform/AQS/Pageviews/Pageviews per project},
  author       = {{Wikimedia Foundation}},
  year         = {2024},
  url = {https://wikitech.wikimedia.org/wiki/Data_Platform/AQS/Pageviews/Pageviews_per_project},
  note         = {Accessed: 2025-12-18},
}

@misc{glottolog5_2_2025,
  title        = {Glottolog 5.2},
  author       = {Hammarstr{\"o}m, Harald and Forkel, Robert and Haspelmath, Martin and Bank, Sebastian},
  year         = {2025},
  publisher    = {Max Planck Institute for Evolutionary Anthropology},
  address      = {Leipzig},
  doi          = {10.5281/zenodo.15525265},
  url          = {https://doi.org/10.5281/zenodo.15525265},
  note         = {Available online at http://glottolog.org. Accessed: 2025-12-18},
}

@article{LeinsterCobbold2012,
  author  = {Leinster, Tom and Cobbold, Christina A.},
  title   = {Measuring diversity: the importance of species similarity},
  journal = {Ecology},
  year    = {2012},
  volume  = {93},
  number  = {3},
  pages   = {477--489},
  doi     = {10.1890/10-2402.1}
}


@misc{ethnologue28_2025_online,
  title        = {Ethnologue: Languages of the World},
  Author       = {Eberhard, David M. and Simons, Gary F. and Fennig, Charles D.},
  year         = {2025},
  edition      = {28th},
  organization = {SIL International},
  location     = {Dallas, Texas},
  url          = {https://www.ethnologue.com/},
  urldate      = {2025-12-18},
}

@standard{ISO639_2023,
  title        = {ISO\,639:2023 — Code for individual languages and language groups},
  organization = {International Organization for Standardization},
  year         = {2023},
  number       = {ISO\,639:2023, 74575},
  url          = {https://www.iso.org/standard/74575.html},
  note         = {Accessed: 2025-12-18},
}

@Manual{rnaturalearth,
    title = {rnaturalearthdata: World Vector Map Data from Natural Earth Used in 'rnaturalearth'},
    author = {Andy South and Schramm Michael and Philippe Massicotte},
    year = {2024},
    note = {R package version 1.0.0},
    url = {https://CRAN.R-project.org/package=rnaturalearthdata},
    doi = {10.32614/CRAN.package.rnaturalearthdata},
  }


@misc{wikimedia-list-of-wikipedias,
  title        = {List of Wikipedias},
  author       = {{Wikimedia Foundation, Inc.}},
  url = {https://meta.wikimedia.org/wiki/List_of_Wikipedias},
  note         = {Meta-Wiki page, accessed 20 Dec 2025},
  year         = {2025}
}

@misc{wikimedia_country_territory_protection_list_2025,
  title        = {Legal: Wikimedia Foundation Country and Territory Protection List},
  author       = {{Wikimedia Foundation}},
  year         = {2025},
  url = {https://foundation.wikimedia.org/wiki/Legal:Wikimedia_Foundation_Country_and_Territory_Protection_List},
  note         = {Last edited 19 May 2025; accessed 23 December 2025},
}

@inproceedings{Essfors2025GlobalLinguisticDiversity,
  author    = {Essfors, Hannes},
  title     = {Global Linguistic Diversity: Adapting the Leinster--Cobbold Framework from Ecology for Humanities Research},
  booktitle = {Anthology of Computers and the Humanities},
  volume    = {3},
  year      = {2025},
  publisher = {Association for Computers and the Humanities},
  doi       = {10.63744/srhQaCwGo5mj},
  url       = {https://doi.org/10.63744/srhQaCwGo5mj},
  address   = {Austin, Texas, U.S.A.}
}


@inproceedings{khan-etal-2025-uriel,
    title = "{URIEL}+: Enhancing Linguistic Inclusion and Usability in a Typological and Multilingual Knowledge Base",
    author = {Khan, Aditya  and
      Shipton, Mason  and
      Anugraha, David  and
      Duan, Kaiyao  and
      Hoang, Phuong H.  and
      Khiu, Eric  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Lee, En-Shiun Annie},
    editor = "Rambow, Owen  and
      Wanner, Leo  and
      Apidianaki, Marianna  and
      Al-Khalifa, Hend  and
      Eugenio, Barbara Di  and
      Schockaert, Steven",
    booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
    month = jan,
    year = "2025",
    address = "Abu Dhabi, UAE",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.coling-main.463/",
    pages = "6937--6952",
    abstract = "URIEL is a knowledge base offering geographical, phylogenetic, and typological vector representations for 7970 languages. It includes distance measures between these vectors for 4005 languages, which are accessible via the lang2vec tool. Despite being frequently cited, URIEL is limited in terms of linguistic inclusion and overall usability. To tackle these challenges, we introduce URIEL+, an enhanced version of URIEL and lang2vec that addresses these limitations. In addition to expanding typological feature coverage for 2898 languages, URIEL+ improves the user experience with robust, customizable distance calculations to better suit the needs of users. These upgrades also offer competitive performance on downstream tasks and provide distances that better align with linguistic distance studies."
}

@article{kornai2013digital,
  author  = {Kornai, András},
  title   = {Digital Language Death},
  journal = {PLOS ONE},
  year    = {2013},
  volume  = {8},
  number  = {10},
  doi     = {10.1371/journal.pone.0077056},
  url     = {https://doi.org/10.1371/journal.pone.0077056}
}

@inproceedings{simons2022assessingdigitallanguagesupport,
    title = "Assessing Digital Language Support on a Global Scale",
    author = "Simons, Gary F.  and
      Thomas, Abbey L. L.  and
      White, Chad K. K.",
    editor = "Calzolari, Nicoletta  and
      Huang, Chu-Ren  and
      Kim, Hansaem  and
      Pustejovsky, James  and
      Wanner, Leo  and
      Choi, Key-Sun  and
      Ryu, Pum-Mo  and
      Chen, Hsin-Hsi  and
      Donatelli, Lucia  and
      Ji, Heng  and
      Kurohashi, Sadao  and
      Paggio, Patrizia  and
      Xue, Nianwen  and
      Kim, Seokhwan  and
      Hahm, Younggyun  and
      He, Zhong  and
      Lee, Tony Kyungil  and
      Santus, Enrico  and
      Bond, Francis  and
      Na, Seung-Hoon",
    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2022.coling-1.379/",
    pages = "4299--4305",
    abstract = "The users of endangered languages struggle to thrive in a digitally-mediated world. We have developed an automated method for assessing how well every language recognized by ISO 639 is faring in terms of digital language support. The assessment is based on scraping the names of supported languages from the websites of 143 digital tools selected to represent a full range of ways that digital technology can support languages. The method uses Mokken scale analysis to produce an explainable model for quantifying digital language support and monitoring it on a global scale."
}

@misc{EF_EPI_2025,
  author       = {{EF Education First}},
  title        = {EF English Proficiency Index 2025},
  year         = {2025},
  howpublished = {EF English Proficiency Index report},
  note         = {Published by EF Education First},
  url          = {https://www.ef.com/wwru/epi/},
}

 @article{Johnson_Lemmerich_Saez-Trumper_West_Strohmaier_Zia_2021, title={Global Gender Differences in Wikipedia Readership}, volume={15}, rights={Copyright (c) 2021 Association for the Advancement of Artificial Intelligence}, ISSN={2334-0770}, DOI={10.1609/icwsm.v15i1.18058}, abstractNote={Wikipedia represents the largest and most popular source of encyclopedic knowledge in the world, aiming to provide equal access to information worldwide. From a global online survey of 65,031 readers of Wikipedia and their corresponding reading logs, we present first evidence of gender differences in Wikipedia readership and how they manifest in records of user behavior. More specifically we report that (1) women are underrepresented among readers of Wikipedia, (2) women view fewer pages per reading session than men do, (3) men and women visit Wikipedia for similar reasons, and (4) men and women exhibit specific topical preferences. Our findings lay the foundation for identifying pathways toward knowledge equity in the usage of online encyclopedic knowledge.}, journal={Proceedings of the International AAAI Conference on Web and Social Media}, author={Johnson, Isaac and Lemmerich, Florian and Sáez-Trumper, Diego and West, Robert and Strohmaier, Markus and Zia, Leila}, year={2021}, month=may, pages={254–265}, language={en} }


 @article{Zhang_Livneh_Budak_Robert_Romero_2017, title={Shocking the Crowd: The Effect of Censorship Shocks on Chinese Wikipedia}, volume={11}, rights={Copyright (c) 2021 Proceedings of the International AAAI Conference on Web and Social Media}, ISSN={2334-0770}, DOI={10.1609/icwsm.v11i1.14895}, abstractNote={Collaborative crowdsourcing has become a popular approach to organizing work across the globe. Being global also means being vulnerable to shocks — unforeseen events that disrupt crowds — that originate from any country. In this study, we examine changes in collaborative behavior of editors of Chinese Wikipedia that arise due to the 2005 government censorship in mainland China. Using the exogenous variation in the fraction of editors blocked across different articles due to the censorship, we examine the impact of reduction in group size, which we denote as the shock level, on three collaborative behavior measures: volume of activity, centralization, and conflict. We find that activity and conflict drop on articles that face a shock, whereas centralization increases. The impact of a shock on activity increases with shock level, whereas the impact on centralization and conflict is higher for moderate shock levels than for very small or very high shock levels. These findings provide support for threat rigidity theory — originally introduced in the organizational theory literature — in the context of large-scale collaborative crowds.}, number={1}, journal={Proceedings of the International AAAI Conference on Web and Social Media}, author={Zhang, Ark Fangzhou and Livneh, Danielle and Budak, Ceren and Robert, Lionel and Romero, Daniel}, year={2017}, month=may, pages={367–376}, language={en} }


 @inproceedings{Yang_Roberts_2021, address={New York, NY, USA}, series={FAccT ’21}, title={Censorship of Online Encyclopedias: Implications for NLP Models}, ISBN={978-1-4503-8309-7}, url={https://dl.acm.org/doi/10.1145/3442188.3445916}, DOI={10.1145/3442188.3445916}, abstractNote={While artificial intelligence provides the backbone for many tools people use around the world, recent work has brought to attention that the algorithms powering AI are not free of politics, stereotypes, and bias. While most work in this area has focused on the ways in which AI can exacerbate existing inequalities and discrimination, very little work has studied how governments actively shape training data. We describe how censorship has affected the development of Wikipedia corpuses, text data which are regularly used for pre-trained inputs into NLP algorithms. We show that word embeddings trained on Baidu Baike, an online Chinese encyclopedia, have very different associations between adjectives and a range of concepts about democracy, freedom, collective action, equality, and people and historical events in China than its regularly blocked but uncensored counterpart - Chinese language Wikipedia. We examine the implications of these discrepancies by studying their use in downstream AI applications. Our paper shows how government repression, censorship, and self-censorship may impact training data and the applications that draw from them.}, booktitle={Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency}, publisher={Association for Computing Machinery}, author={Yang, Eddie and Roberts, Margaret E.}, year={2021}, month=mar, pages={537–548}, collection={FAccT ’21} }


 @article{Pan_Roberts_2020,
  author  = {Pan, Jennifer and Roberts, Margaret E.},
  title   = {Censorship’s Effect on Incidental Exposure to Information: Evidence From Wikipedia},
  journal = {SAGE Open},
  year    = {2020},
  volume  = {10},
  number  = {1},
  doi     = {10.1177/2158244019894068},
  url     = {https://doi.org/10.1177/2158244019894068}
}



@misc{ITU2024UrbanRuralInternet,
  author       = {{International Telecommunication Union}},
  title        = {Internet use in urban and rural areas},
  year         = {2024},
  url = {https://www.itu.int/itu-d/reports/statistics/2024/11/10/\nff24-internet-use-in-urban-and-rural-areas/},
  note         = {Facts and Figures 2024. Accessed: 9 February 2026}
}

@article{harmon2010indexhdl,
  title={The Index of Linguistic Diversity: A New Quantitative Measure of Trends in the Status of the World’s Languages},
  author={Harmon, David and Loh, Jonathan},
  journal={Language Documentation \& Conservation},
  volume={4},
  pages={97--151},
  year={2010},
  url={https://hdl.handle.net/10125/4474},
  note={Retrieved from ScholarSpace, University of Hawaiʻi at Mānoa} 
}
