How Does Twitter User Behavior Vary Across Demographic Groups?

Zach Wood-Doughty; Michael Smith; David Broniatowski; Mark Dredze

doi:10.18653/v1/W17-2912

How Does Twitter User Behavior Vary Across Demographic Groups?

Zach Wood-Doughty, Michael Smith, David Broniatowski, Mark Dredze

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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.

Anthology ID:: W17-2912
Volume:: Proceedings of the Second Workshop on NLP and Computational Social Science
Month:: August
Year:: 2017
Address:: Vancouver, Canada
Editors:: Dirk Hovy, Svitlana Volkova, David Bamman, David Jurgens, Brendan O’Connor, Oren Tsur, A. Seza Doğruöz
Venue:: NLP+CSS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 83–89
Language:
URL:: https://aclanthology.org/W17-2912/
DOI:: 10.18653/v1/W17-2912
Bibkey:
Cite (ACL):: Zach Wood-Doughty, Michael Smith, David Broniatowski, and Mark Dredze. 2017. How Does Twitter User Behavior Vary Across Demographic Groups?. In Proceedings of the Second Workshop on NLP and Computational Social Science, pages 83–89, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):: How Does Twitter User Behavior Vary Across Demographic Groups? (Wood-Doughty et al., NLP+CSS 2017)
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PDF:: https://aclanthology.org/W17-2912.pdf

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@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",
    editor = {Hovy, Dirk  and
      Volkova, Svitlana  and
      Bamman, David  and
      Jurgens, David  and
      O{'}Connor, Brendan  and
      Tsur, Oren  and
      Do{\u{g}}ru{\"o}z, A. Seza},
    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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%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
%Y Hovy, Dirk
%Y Volkova, Svitlana
%Y Bamman, David
%Y Jurgens, David
%Y O’Connor, Brendan
%Y Tsur, Oren
%Y Doğruöz, A. Seza
%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

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Markdown (Informal)

[How Does Twitter User Behavior Vary Across Demographic Groups?](https://aclanthology.org/W17-2912/) (Wood-Doughty et al., NLP+CSS 2017)

How Does Twitter User Behavior Vary Across Demographic Groups? (Wood-Doughty et al., NLP+CSS 2017)

ACL

Zach Wood-Doughty, Michael Smith, David Broniatowski, and Mark Dredze. 2017. How Does Twitter User Behavior Vary Across Demographic Groups?. In Proceedings of the Second Workshop on NLP and Computational Social Science, pages 83–89, Vancouver, Canada. Association for Computational Linguistics.