Is gender-based violence a confluence of culture? empirical evidence from social media
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Authors
Rimjhim
Dandapat, Sourav
Issue Date
2022-07-29
Type
Article
Language
en_US
Keywords
Computational Social Science , Social Computing , Ethnography , Gender Based Violence , Twitter , Correlation , Hofstede Cultural Dimension , Culture , Sexual Violence , Physical Violence
Alternative Title
Abstract
Gender-based violence (GBV) has been plaguing our society for long back. The severity of GBV has spurred research around understanding the causes and factors leading to GBV. Understanding factors and causes leading to GBV is helpful in planning and executing efficient policies to curb GBV. Past researches have claimed a country’s culture to be one of the driving reasons behind GBV. The culture of a country consists of cultural norms, societal rules, gender-based stereotypes, and social taboos which provoke GBV. These claims are supported by theoretical or small-scale survey-based research that suffers from under-representation and biases. With the advent of social media and, more importantly, location-tagged social media, huge ethnographic data are available, creating a platform for many sociological research. In this article, we also utilize huge social media data to verify the claim of confluence between GBV and the culture of a country. We first curate GBV content from different countries by collecting a large amount of data from Twitter. In order to explore the relationship between a country’s culture and GBV content, we performed correlation analyses between a country’s culture and its GBV content. The correlation results are further re-validated using graph-based methods. Through the findings of this research, we observed that countries with similar cultures also show similarity in GBV content, thus reconfirming the relationship between GBV and culture.
Description
Citation
Rimjhim, & Dandapat, S. (2022). Is gender-based violence a confluence of culture? Empirical evidence from social media. PeerJ. Computer science, 8, e1051. https://doi.org/10.7717/peerj-cs.1051
Publisher
Computer Science