<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="wood-doughty-etal-2017-twitter">
    <titleInfo>
        <title>How Does Twitter User Behavior Vary Across Demographic Groups?</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Zach</namePart>
        <namePart type="family">Wood-Doughty</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Michael</namePart>
        <namePart type="family">Smith</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">David</namePart>
        <namePart type="family">Broniatowski</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Mark</namePart>
        <namePart type="family">Dredze</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2017-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Second Workshop on NLP and Computational Social Science</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Dirk</namePart>
            <namePart type="family">Hovy</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Svitlana</namePart>
            <namePart type="family">Volkova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">David</namePart>
            <namePart type="family">Bamman</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">David</namePart>
            <namePart type="family">Jurgens</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Brendan</namePart>
            <namePart type="family">O’Connor</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Oren</namePart>
            <namePart type="family">Tsur</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">A</namePart>
            <namePart type="given">Seza</namePart>
            <namePart type="family">Doğruöz</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Vancouver, Canada</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <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>
    <identifier type="citekey">wood-doughty-etal-2017-twitter</identifier>
    <identifier type="doi">10.18653/v1/W17-2912</identifier>
    <location>
        <url>https://aclanthology.org/W17-2912</url>
    </location>
    <part>
        <date>2017-08</date>
        <extent unit="page">
            <start>83</start>
            <end>89</end>
        </extent>
    </part>
</mods>
</modsCollection>

%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

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.