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Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations
11 references·11 citing·44 second hop
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this work references cited by second hop

References

  • 1968Identity : Youth and Crisis. 196815,133 cited
  • 1969Identity—Youth and Crisis2,520 cited
  • 2001The Glass Ceiling Effect889 cited
  • 2021Understanding the Demographics of Twitter Users760 cited
  • 2013Teens, social media, and privacy701 cited
  • 2005Racism Without Racists: Colorblind Racism and the Persistence of Racial Inequality in the United States611 cited
  • 2014Inferring international and internal migration patterns from Twitter data224 cited
  • 2015Jane, John … Leslie? A Historical Method for Algorithmic Gender Prediction109 cited
  • 2016Women through the glass ceiling: gender asymmetries in Wikipedia92 cited
  • 2015Learning Fair Classifiers75 cited
  • 2021#greysanatomy vs. #yankees: Demographics and Hashtag Use on Twitter54 cited

Cited by

  • 2022Mitigating Bias in Algorithmic Systems—A Fish-eye View53 cited
  • 2021Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement50 cited
  • 2019Fairness in Proprietary Image Tagging Algorithms: A Cross-Platform Audit on People Images40 cited
  • 2019Summarizing User-generated Textual Content: Motivation and Methods for Fairness in Algorithmic Summaries

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34 cited
  • 2021When the Umpire is also a Player32 cited
  • 2020Automated image analysis of instagram posts: Implications for risk perception and communication in public health using a case study of #HIV27 cited
  • 2022Methods to Establish Race or Ethnicity of Twitter Users: Scoping Review21 cited
  • 2017White, Man, and Highly Followed: Gender and Race Inequalities in Twitter21 cited
  • 2017A large-scale study of cultural differences using urban data about eating and drinking preferences19 cited
  • 2019On the Impact of Choice Architectures on Inequality in Online Donation Platforms10 cited
  • 2021An Analysis of Twitter Users From The Perspective of Their Behavior, Language, Region and Development Indices -- A Study of 80 Million Tweets3 cited