Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
5-2016
Abstract
Demographics, in particular, gender, age, and race, are a key predictor of human behavior. Despite the significant effect that demographics plays, most scientific studies using online social media do not consider this factor, mainly due to the lack of such information. In this work, we use state-of-the-art face analysis software to infer gender, age, and race from profile images of 350K Twitter users from New York. For the period from November 1, 2014 to October 31, 2015, we study which hashtags are used by different demographic groups. Though we find considerable overlap for the most popular hashtags, there are also many group-specific hashtags.
Keywords
Hashtags, social media, Twitter, human behaviors, demographics, New York
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media
Research Areas
Data Science and Engineering
Publication
Proceedings of the 10th International AAAI Conference on Web and Social Media ICWSM 2016: Cologne, May 17-20
Volume
10
First Page
523
Last Page
526
ISBN
9781577357582
Publisher
AAAI Press
City or Country
Palo Alto, CA
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://ojs.aaai.org/index.php/ICWSM/article/view/14767
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons, Social Media Commons