Better targeting of consumers: Modeling multifactorial gender and biological sex from Instagram posts

Author:

Jeon Youngseung,Jeon Seung Gon,Han KyungsikORCID

Funder

National Research Foundation of Korea

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Human-Computer Interaction,Education

Reference103 articles.

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3. Al Zamal, F., Liu, W., Ruths, D.: Homophily and latent attribute inference: inferring latent attributes of Twitter users from neighbors. In: Proceedings of the International Conference on Web and Social Media, AAAI (2012)

4. Argamon, S., Koppel, M., Fine, J., Shimoni, A.R.: Gender, genre, and writing style in formal written texts. Text-The Hague Then Amsterdam Then Berlin 23(3), 321–346 (2003)

5. Argamon-Engelson, S., Koppel, M., Avneri, G.: Style-based text categorization: what newspaper am i reading. In: Proceedings of the AAAI Workshop on Text Categorization, pp. 1–4 (1998)

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