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A Machine Learning Approach to Twitter User Classification
Open accessAbstract
This paper addresses the task of user classification in social media, with an application to Twitter. We automatically infer the values of user attributes such as political orientation or ethnicity by leveraging observable information such as the user behavior, network structure and the linguistic content of the user’s Twitter feed. We employ a machine learning approach which relies on a comprehensive set of features derived from such user information. We report encouraging experimental results on 3 tasks with different characteristics: political affiliation detection, ethnicity identification and detecting affinity for a particular business. Finally, our analysis shows that rich linguistic features prove consistently valuable across the 3 tasks and show great promise for additional user classification needs.
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Cites
Greedy function approximation: A gradient boosting machine
Friedman, J. H. (2001) · The Annals of Statistics · doi:10.1214/aos/1013203451 · Cited by 30,731
Cited by
Birds of the Same Feather Tweet Together. Bayesian Ideal Point Estimation Using Twitter Data
Barbera, P. (2012) · doi:10.2139/ssrn.2108098 · Cited by 983
Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data
Barberá, P. (2015) · Political Analysis · doi:10.1093/pan/mpu011 · Cited by 982
” How old do you think I am?” A study of language and age in Twitter
Nguyen, D., Gravel, R., Trieschnigg, D., & Meder, T. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v7i1.14381 · Cited by 287
Studying user income through language, behaviour and affect in social media
Preoţiuc-Pietro, D., Volkova, S., Lampos, V., Bachrach, Y., & Aletras, N. (2015) · PLOS ONE · doi:10.1371/journal.pone.0138717 · Cited by 219
Zhang, Y., Wells, C., Wang, S., & Rohe, K. (2018) · New Media & Society · doi:10.1177/1461444817744390 · Cited by 155
Metadata
- Authors
- Pennacchiotti, M., & Popescu, A.-M.
- Venue
- Proceedings of the International AAAI Conference on Web and Social Media
- Published
- 2021-08-03
- Volume
- 5
- Issue
- 1
- Pages
- 281-288
- ISSN
- 2162-3449 (ISSN-L)
- 2334-0770
- OpenAlex
- W184758014
- Cited by
- 548
- References
- 1
- FWCI
- 11.11
- Type
- conference paper
- Language
- en
- Open access
- diamond
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- Pennacchiotti, M., & Popescu, A.-M. (2021). A Machine Learning Approach to Twitter User Classification. Proceedings of the International AAAI Conference on Web and Social Media. https://doi.org/10.1609/icwsm.v5i1.14139
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