@inproceedings{wood-doughty-etal-2017-twitter,
title = "How Does {T}witter User Behavior Vary Across Demographic Groups?",
author = "Wood-Doughty, Zach and
Smith, Michael and
Broniatowski, David and
Dredze, Mark",
booktitle = "Proceedings of the Second Workshop on {NLP} and Computational Social Science",
month = aug,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-2912",
doi = "10.18653/v1/W17-2912",
pages = "83--89",
abstract = "Demographically-tagged social media messages are a common source of data for computational social science. While these messages can indicate differences in beliefs and behaviors between demographic groups, we do not have a clear understanding of how different demographic groups use platforms such as Twitter. This paper presents a preliminary analysis of how groups{'} differing behaviors may confound analyses of the groups themselves. We analyzed one million Twitter users by first inferring demographic attributes, and then measuring several indicators of Twitter behavior. We find differences in these indicators across demographic groups, suggesting that there may be underlying differences in how different demographic groups use Twitter.",
}
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<abstract>Demographically-tagged social media messages are a common source of data for computational social science. While these messages can indicate differences in beliefs and behaviors between demographic groups, we do not have a clear understanding of how different demographic groups use platforms such as Twitter. This paper presents a preliminary analysis of how groups’ differing behaviors may confound analyses of the groups themselves. We analyzed one million Twitter users by first inferring demographic attributes, and then measuring several indicators of Twitter behavior. We find differences in these indicators across demographic groups, suggesting that there may be underlying differences in how different demographic groups use Twitter.</abstract>
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%0 Conference Proceedings
%T How Does Twitter User Behavior Vary Across Demographic Groups?
%A Wood-Doughty, Zach
%A Smith, Michael
%A Broniatowski, David
%A Dredze, Mark
%S Proceedings of the Second Workshop on NLP and Computational Social Science
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F wood-doughty-etal-2017-twitter
%X Demographically-tagged social media messages are a common source of data for computational social science. While these messages can indicate differences in beliefs and behaviors between demographic groups, we do not have a clear understanding of how different demographic groups use platforms such as Twitter. This paper presents a preliminary analysis of how groups’ differing behaviors may confound analyses of the groups themselves. We analyzed one million Twitter users by first inferring demographic attributes, and then measuring several indicators of Twitter behavior. We find differences in these indicators across demographic groups, suggesting that there may be underlying differences in how different demographic groups use Twitter.
%R 10.18653/v1/W17-2912
%U https://aclanthology.org/W17-2912
%U https://doi.org/10.18653/v1/W17-2912
%P 83-89
Markdown (Informal)
[How Does Twitter User Behavior Vary Across Demographic Groups?](https://aclanthology.org/W17-2912) (Wood-Doughty et al., NLP+CSS 2017)
ACL