Gender-based violence in 140 characters or fewer: A #BigData case study of Twitter

  • Hemant Purohit George Mason University
  • Tanvi Banerjee Wright State University
  • Andrew Hampton Wright State University
  • Valerie L. Shalin Wright State University
  • Nayanesh Bhandutia United Nations Population Fund
  • Amit Sheth Wright State University
Keywords: computational social science, gender-based violence, social media, quantitative analysis, qualitative analysis, citizen sensing, public awareness, public attitude, policy, intervention campaign

Abstract

Public institutions are increasingly reliant on data from social media sites to measure public attitude and provide timely public engagement. Such reliance includes the exploration of public views on important social issues such as gender-based violence (GBV). In this study, we examine big (social) data consisting of nearly 14 million tweets collected from Twitter over a period of 10 months to analyze public opinion regarding GBV, highlighting the nature of tweeting practices by geographical location and gender. We demonstrate the utility of computational social science to mine insight from the corpus while accounting for the influence of both transient events and sociocultural factors. We reveal public awareness regarding GBV tolerance and suggest opportunities for intervention and the measurement of intervention effectiveness assisting both governmental and non-governmental organizations in policy development.

Author Biographies

Hemant Purohit, George Mason University

Assistant Professor, Department of Information Sciences & Technology 

Tanvi Banerjee, Wright State University
Research Assistant Professor, Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis) and Department of Computer Science & Engineering
Andrew Hampton, Wright State University
PhD Student, Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis), and Department of Psychology
Valerie L. Shalin, Wright State University
Associate Professor, Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis), and Department of Psychology
Nayanesh Bhandutia, United Nations Population Fund

Application Manager, Department of MIS

Amit Sheth, Wright State University
Executive Director, Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis), and Professor, Department of Computer Science & Engineering
Published
2016-01-10
How to Cite
Purohit, H., Banerjee, T., Hampton, A., Shalin, V. L., Bhandutia, N., & Sheth, A. (2016). Gender-based violence in 140 characters or fewer: A #BigData case study of Twitter. First Monday, 21(1). https://doi.org/10.5210/fm.v21i1.6148