#MeToo on Campus: Studying College Sexual Assault at Scale Using Data Reported on Social Media

• URL: http://arxiv.org/abs/2001.05970v1
• Date: Thu, 16 Jan 2020 18:05:46 GMT
• Title: #MeToo on Campus: Studying College Sexual Assault at Scale Using Data Reported on Social Media
• Authors: Viet Duong, Phu Pham, Ritwik Bose, Jiebo Luo
• Abstract summary: We analyze the influence of the # trend on a pool of college followers. The results show that the majority of topics embedded in those # tweets detail sexual harassment stories. There exists a significant correlation between the prevalence of this trend and official reports on several major geographical regions.
• Score: 71.74529365205053
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recently, the emergence of the #MeToo trend on social media has empowered thousands of people to share their own sexual harassment experiences. This viral trend, in conjunction with the massive personal information and content available on Twitter, presents a promising opportunity to extract data driven insights to complement the ongoing survey based studies about sexual harassment in college. In this paper, we analyze the influence of the #MeToo trend on a pool of college followers. The results show that the majority of topics embedded in those #MeToo tweets detail sexual harassment stories, and there exists a significant correlation between the prevalence of this trend and official reports on several major geographical regions. Furthermore, we discover the outstanding sentiments of the #MeToo tweets using deep semantic meaning representations and their implications on the affected users experiencing different types of sexual harassment. We hope this study can raise further awareness regarding sexual misconduct in academia.

Related papers

• Exploring Gender-Based Toxic Speech on Twitter in Context of the #MeToo movement: A Mixed Methods Approach [2.454909090258064]
  The # movement has catalyzed widespread public discourse surrounding sexual harassment and assault, empowering survivors to share their stories and holding perpetrators accountable. While the movement has had a substantial and largely positive influence, this study aims to examine the potential negative consequences in the form of increased hostility against women and men on the social media platform Twitter. By analyzing tweets shared between October 2017 and January 2020 by more than 47.1k individuals who had either disclosed their own sexual abuse experiences on Twitter or engaged in discussions about the movement, we identify the overall increase in gender-based hostility towards both women and men since the start of the movement.
  arXiv  Detail & Related papers  (2023-08-24T20:45:12Z)
• A deep dive into the consistently toxic 1% of Twitter [9.669275987983447]
  This study spans 14 years of tweets from 122K Twitter profiles and more than 293M tweets. We selected the most extreme profiles in terms of consistency of toxic content and examined their tweet texts, and the domains, hashtags, and URLs they shared. We found that these selected profiles keep to a narrow theme with lower diversity in hashtags, URLs, and domains, they are thematically similar to each other, and have a high likelihood of bot-like behavior.
  arXiv  Detail & Related papers  (2022-02-16T04:21:48Z)
• What goes on inside rumour and non-rumour tweets and their reactions: A Psycholinguistic Analyses [58.75684238003408]
  psycho-linguistics analyses of social media text are vital for drawing meaningful conclusions to mitigate misinformation. This research contributes by performing an in-depth psycholinguistic analysis of rumours related to various kinds of events.
  arXiv  Detail & Related papers  (2021-11-09T07:45:11Z)
• Know it to Defeat it: Exploring Health Rumor Characteristics and Debunking Efforts on Chinese Social Media during COVID-19 Crisis [65.74516068984232]
  We conduct a comprehensive analysis of four months of rumor-related online discussion during COVID-19 on Weibo, a Chinese microblogging site. Results suggest that the dread (cause fear) type of health rumors provoked significantly more discussions and lasted longer than the wish (raise hope) type. We show the efficacy of debunking in suppressing rumor discussions, which is time-sensitive and varies across rumor types and debunkers.
  arXiv  Detail & Related papers  (2021-09-25T14:02:29Z)
• News consumption and social media regulations policy [70.31753171707005]
  We analyze two social media that enforced opposite moderation methods, Twitter and Gab, to assess the interplay between news consumption and content regulation. Our results show that the presence of moderation pursued by Twitter produces a significant reduction of questionable content. The lack of clear regulation on Gab results in the tendency of the user to engage with both types of content, showing a slight preference for the questionable ones which may account for a dissing/endorsement behavior.
  arXiv  Detail & Related papers  (2021-06-07T19:26:32Z)
• Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement [17.672730162091526]
  The # movement on Twitter has drawn attention to the pervasive nature of sexual harassment and violence. We examine online # conversations across gender and racial/ethnic identities. We find that tweets authored by white women were overrepresented in the movement compared to other demographics.
  arXiv  Detail & Related papers  (2020-10-13T15:25:33Z)
• Hate is the New Infodemic: A Topic-aware Modeling of Hate Speech Diffusion on Twitter [24.94135874070525]
  We focus on exploring user behaviour, which triggers the genesis of hate speech on Twitter. We crawl a large-scale dataset of tweets, retweets, user activity history, and follower networks. We characterize different signals of information that govern these dynamics.
  arXiv  Detail & Related papers  (2020-10-09T05:43:08Z)
• ALONE: A Dataset for Toxic Behavior among Adolescents on Twitter [5.723363140737726]
  This paper provides a dataset of toxic social media interactions between confirmed high school students, called ALONE (AdoLescents ON twittEr) Nearly 66% of internet users have observed online harassment, and 41% claim personal experience, with 18% facing severe forms of online harassment. Our observations show that individual tweets do not provide sufficient evidence for toxic behavior, and meaningful use of context in interactions can enable highlighting or exonerating tweets with purported toxicity.
  arXiv  Detail & Related papers  (2020-08-14T17:02:55Z)
• Detecting Perceived Emotions in Hurricane Disasters [62.760131661847986]
  We introduce HurricaneEmo, an emotion dataset of 15,000 English tweets spanning three hurricanes: Harvey, Irma, and Maria. We present a comprehensive study of fine-grained emotions and propose classification tasks to discriminate between coarse-grained emotion groups.
  arXiv  Detail & Related papers  (2020-04-29T16:17:49Z)
• Echo Chambers on Social Media: A comparative analysis [64.2256216637683]
  We introduce an operational definition of echo chambers and perform a massive comparative analysis on 1B pieces of contents produced by 1M users on four social media platforms. We infer the leaning of users about controversial topics and reconstruct their interaction networks by analyzing different features. We find support for the hypothesis that platforms implementing news feed algorithms like Facebook may elicit the emergence of echo-chambers.
  arXiv  Detail & Related papers  (2020-04-20T20:00:27Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.