2015/03/06 by Hemant Purohit, Tanvi Banerjee, Purohit, Hemant +10 · 1 citation
Computer Science · Social Sciences · #Computers and Society (cs.CY) #FOS: Computer and information sciences #Gender, Feminism, and Media #H.1.2 #Hate Speech and Cyberbullying Detection #J.4 #Social Media and Politics #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1503.02086
openalex publication_date 2015/03/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Public institutions are increasingly reliant on data from social media sites\nto measure public attitude and provide timely public engagement. Such reliance\nincludes the exploration of public views on important social issues such as\ngender-based violence (GBV). In this study, we examine big (social) data\nconsisting of nearly fourteen million tweets collected from Twitter over a\nperiod of ten months to analyze public opinion regarding GBV, highlighting the\nnature of tweeting practices by geographical location and gender. We\ndemonstrate the utility of Computational Social Science to mine insight from\nthe corpus while accounting for the influence of both transient events and\nsociocultural factors. We reveal public awareness regarding GBV tolerance and\nsuggest opportunities for intervention and the measurement of intervention\neffectiveness assisting both governmental and non-governmental organizations in\npolicy development.\n