Literature DB >> 35295189

Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement.

Aaron Mueller1, Zach Wood-Doughty1, Silvio Amir1, Mark Dredze1, Alicia Lynn Nobles2.   

Abstract

The #MeToo movement on Twitter has drawn attention to the pervasive nature of sexual harassment and violence. While #MeToo has been praised for providing support for self-disclosures of harassment or violence and shifting societal response, it has also been criticized for exemplifying how women of color have been discounted for their historical contributions to and excluded from feminist movements. Through an analysis of over 600,000 tweets from over 256,000 unique users, we examine online #MeToo conversations across gender and racial/ethnic identities and the topics that each demographic emphasized. We found that tweets authored by white women were overrepresented in the movement compared to other demographics, aligning with criticism of unequal representation. We found that intersected identities contributed differing narratives to frame the movement, co-opted the movement to raise visibility in parallel ongoing movements, employed the same hashtags both critically and supportively, and revived and created new hashtags in response to pivotal moments. Notably, tweets authored by black women often expressed emotional support and were critical about differential treatment in the justice system and by police. In comparison, tweets authored by white women and men often highlighted sexual harassment and violence by public figures and weaved in more general political discussions. We discuss the implications of this work for digital activism research and design, including suggestions to raise visibility by those who were under-represented in this hashtag activism movement. Content warning: this article discusses issues of sexual harassment and violence.

Entities:  

Keywords:  demographic inference; metoo; topic modeling

Year:  2021        PMID: 35295189      PMCID: PMC8920314          DOI: 10.1145/3449181

Source DB:  PubMed          Journal:  Proc ACM Hum Comput Interact


  16 in total

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Journal:  Psychol Bull       Date:  2008-07       Impact factor: 17.737

Review 3.  Twitter as a Tool for Health Research: A Systematic Review.

Authors:  Lauren Sinnenberg; Alison M Buttenheim; Kevin Padrez; Christina Mancheno; Lyle Ungar; Raina M Merchant
Journal:  Am J Public Health       Date:  2016-11-17       Impact factor: 9.308

4.  #Diversity: Conversations on Twitter about Women and Black Men in Medicine.

Authors:  Ranit Mishori; Lisa Singh; Kenneth W Lin; Yifang Wei
Journal:  J Am Board Fam Med       Date:  2019 Jan-Feb       Impact factor: 2.657

5.  Could behavioral medicine lead the web data revolution?

Authors:  John W Ayers; Benjamin M Althouse; Mark Dredze
Journal:  JAMA       Date:  2014-04-09       Impact factor: 56.272

Review 6.  Sexual violence against women: the scope of the problem.

Authors:  Elizabeth Dartnall; Rachel Jewkes
Journal:  Best Pract Res Clin Obstet Gynaecol       Date:  2012-08-29       Impact factor: 5.237

7.  Discovering health topics in social media using topic models.

Authors:  Michael J Paul; Mark Dredze
Journal:  PLoS One       Date:  2014-08-01       Impact factor: 3.240

8.  Don't quote me: reverse identification of research participants in social media studies.

Authors:  John W Ayers; Theodore L Caputi; Camille Nebeker; Mark Dredze
Journal:  NPJ Digit Med       Date:  2018-08-02

9.  The geography of happiness: connecting twitter sentiment and expression, demographics, and objective characteristics of place.

Authors:  Lewis Mitchell; Morgan R Frank; Kameron Decker Harris; Peter Sheridan Dodds; Christopher M Danforth
Journal:  PLoS One       Date:  2013-05-29       Impact factor: 3.240

10.  Can online self-reports assist in real-time identification of influenza vaccination uptake? A cross-sectional study of influenza vaccine-related tweets in the USA, 2013-2017.

Authors:  Xiaolei Huang; Michael C Smith; Amelia M Jamison; David A Broniatowski; Mark Dredze; Sandra Crouse Quinn; Justin Cai; Michael J Paul
Journal:  BMJ Open       Date:  2019-01-15       Impact factor: 2.692

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  1 in total

Review 1.  Methods to Establish Race or Ethnicity of Twitter Users: Scoping Review.

Authors:  Su Golder; Robin Stevens; Karen O'Connor; Richard James; Graciela Gonzalez-Hernandez
Journal:  J Med Internet Res       Date:  2022-04-29       Impact factor: 7.076

  1 in total

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