Title

Using social network analysis in understanding the public discourse on gender violence : an agent-based modelling approach

Date of Award

2017

Document Type

Thesis

Degree Name

Master of Science in Computer Science, Straight

Department

Information Systems & Computer Science

First Advisor

Estuar, Ma. Regina Justina E., Ph.D.

Abstract

This study aimed to find the conversation space of gendered violence and constructed a social network model using an agent-based approach. This study looked into measures of centrality, density and changes over time in the context of two cultures: Philippines and the United States. The data set from the Philippines consisted of articles on the Vizconde Massacre and the data set from the United States consisted of articles on the Stanford Rape Case. Results showed 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. However, despite being institution-centric, beliefs attached to victims and perpetrators are more central - with victims being labelled by their victimhood and perpetrators being labelled by other aspects besides their involvement in the crime.

Comments

The C7.D455 2017

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