Demographic Inference on Twitter using Recursive Neural Networks

Sunghwan Mac Kim, Qiongkai Xu, Lizhen Qu, Stephen Wan, Cécile Paris


Abstract
In social media, demographic inference is a critical task in order to gain a better understanding of a cohort and to facilitate interacting with one’s audience. Most previous work has made independence assumptions over topological, textual and label information on social networks. In this work, we employ recursive neural networks to break down these independence assumptions to obtain inference about demographic characteristics on Twitter. We show that our model performs better than existing models including the state-of-the-art.
Anthology ID:
P17-2075
Volume:
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
July
Year:
2017
Address:
Vancouver, Canada
Editors:
Regina Barzilay, Min-Yen Kan
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
471–477
Language:
URL:
https://aclanthology.org/P17-2075
DOI:
10.18653/v1/P17-2075
Bibkey:
Cite (ACL):
Sunghwan Mac Kim, Qiongkai Xu, Lizhen Qu, Stephen Wan, and Cécile Paris. 2017. Demographic Inference on Twitter using Recursive Neural Networks. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 471–477, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
Demographic Inference on Twitter using Recursive Neural Networks (Kim et al., ACL 2017)
Copy Citation:
PDF:
https://aclanthology.org/P17-2075.pdf