1 Gender-Based Violence in 140 Characters Or Fewer
Gender-Based Violence in 140 Characters or Fewer: A #BigData Case Study of Twitter Hemant Purohit1,2, Tanvi Banerjee1,2, Andrew Hampton1,3, Valerie L. Shalin1,3, Nayanesh Bhandutia4 & Amit P. Sheth1,2 1Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis), Dayton, OH, USA 2Department of Computer Science and Engineering, Wright State University, Dayton, OH, USA 3Department of Psychology, Wright State University, Dayton, OH, USA 4United Nations Population Fund Headquarters, NYC, NY, USA Corresponding Authors: Hemant Purohit, Amit Sheth, Valerie Shalin: {hemant, amit, valerie}@knoesis.org 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 fourteen million tweets collected from Twitter over a period of ten 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. Keywords: computational social science, gender-based violence, social media, citizen sensing, public awareness, public attitude, policy, intervention campaign 1 [1.] INTRODUCTION Gender-based violence (GBV), primarily against women, is a pervasive, global phenomenon affecting both developed and developing countries.
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