Assessing socioeconomic status of Twitter users: A survey

Dhouha Ghazouani, Luigi Lancieri, Habib Ounelli, Chaker Jebari


Abstract
Every day, the emotion and opinion of different people across the world are reflected in the form of short messages using microblogging platforms. Despite the existence of enormous potential introduced by this data source, the Twitter community is still ambiguous and is not fully explored yet. While there are a huge number of studies examining the possibilities of inferring gender and age, there exist hardly researches on socioeconomic status (SES) inference of Twitter users. As socioeconomic status is essential to treating diverse questions linked to human behavior in several fields (sociology, demography, public health, etc.), we conducted a comprehensive literature review of SES studies, inference methods, and metrics. With reference to the research on literature’s results, we came to outline the most critical challenges for researchers. To the best of our knowledge, this paper is the first review that introduces the different aspects of SES inference. Indeed, this article provides the benefits for practitioners who aim to process and explore Twitter SES inference.
Anthology ID:
R19-1046
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
Month:
September
Year:
2019
Address:
Varna, Bulgaria
Editors:
Ruslan Mitkov, Galia Angelova
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
388–398
Language:
URL:
https://aclanthology.org/R19-1046
DOI:
10.26615/978-954-452-056-4_046
Bibkey:
Cite (ACL):
Dhouha Ghazouani, Luigi Lancieri, Habib Ounelli, and Chaker Jebari. 2019. Assessing socioeconomic status of Twitter users: A survey. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 388–398, Varna, Bulgaria. INCOMA Ltd..
Cite (Informal):
Assessing socioeconomic status of Twitter users: A survey (Ghazouani et al., RANLP 2019)
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PDF:
https://preview.aclanthology.org/improve-issue-templates/R19-1046.pdf