Discovering Conversation Spaces in the Public Discourse of Gender Violence: a Comparative Between Two Different Contexts

A huge factor in gender-based violence is perception and stigma, revealed by public discourse. Topic modelling is useful for discourse analysis and reveals prevalent topics and actors. This study aims to find and compare examples of collectivist and individualist conversation spaces of gendered violence by applying Principal Component Analysis, NGram analysis and word association in two gender violence cases which occured in the different contexts of the Philippines and the United States. The data from the Philippines consist of 2010-2011 articles on the 1991 Vizconde Massacre and the data from the United States consist of 2016-2017 articles from the 2015 Stanford Rape Case. Results show that in both cases’ conversation space there is a focus on institutions involved in the cases that does not really change over time, and a time-dependent conversation space for victims. Even in two different contexts of gender violence, patterns in conversation space appear simila

Using Social Network Analysis in Understanding The Public Discourse on Gender Violence: an Agent-Based Modelling Approach

There are many representations attributed to gender-based violence. Public discourse provides useful datasets that can be studied in order to study such representations. Social network modelling is a way to study that public discourse, by looking at how opinions in a discourse interact and repeat themselves on a large scale and over time. This study aims to construct a social network model using an agent-based approach to measure whether the conversation space of certain gender violence discourses are more centered on victims, perpetrators, institutions, or society. It will use network measures of centrality, immediate impact analysis, and centrality changes over time to compare the context of two cultures: Philippines and the United States. The data set from the Philippines consists of articles on the Vizconde Massacre and the data set from the United States consists of articles on the Stanford Rape Case. Results show that both datasets feature an institution-centric discourse that is consistent over time, and that society has the lowest role-centrality in both events. Perpetrators appear more central than victims, but comparatively more so in the Stanford Rape dataset compared to the Vizconde Massacre one