Combining Traditional News Sources and Social Media Data for Conflict Prediction and Analysis: A Rohingya Conflict Case Study

Abstract

For the longest time, traditional mass media has always had quasi-monopolistic power over information exchange. The fall of Soviet communism paved the way for the neoliberal order to supersede as the superior economic model for the world to abide by. In paper, the neoliberal globalisation was advertised as the purveyor of peace and reconciliation across the globe, but the reality on the ground is different. Intra-state conflicts in the Global South defined the post-Cold War era, but international coverage of these conflicts have been erratic paving way for mediatised conflicts and stealth conflicts. Studies in mediatised and stealth conflicts mostly focused on the role of the traditional mainstream media in reporting conflicts. This thesis specifically looks at what has changed in the digital post-truth era. Audience trust in traditional media is rapidly fading; thus, people have started to seek for alternatives. This situation has left a gap in the media-audience duo; and it is in this gap where social media finds itself in the middle as it offers new opportunities for news exposure. This research intends to analyse the alignment and divergence of frames produced in social media and by traditional press and how they correlate with political trends surrounding the conflict in spectator countries. Furthermore, not only do media frames vary from one medium and one phase to another, research has shown that it also changes based on the geopolitical proximity of a foreign country to the conflict zone.

Presenters

Jean Dinco
Doctorate Candidate, University of New South Wales, Australia

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

2021 Special Focus—The Data Galaxy: The Un-Making of Typographic Man?

KEYWORDS

MEDIATISATION, CONFLICT ANALYSIS, GATEKEEPING, MACHINE LEARNING