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Online Social Media in the Syria Conflict: Encompassing the Extremes and the In-Betweens
O'Callaghan, Derek; Prucha, Nico; Greene, Derek; Conway, Maura; Carthy, Joe; Cunningham, Pádraig
The 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'14), 17-20 August, Beijing, China The Syria conflict has been described as the most socially mediated in history, with online social media playing a particularly important role. At the same time, the ever-changing landscape of the conflict leads to difficulties in applying analysis approaches taken by other studies of online political activism. In this paper, we propose an approach motivated by the Grounded Theory method, which is used within the social sciences to perform analysis in situations where key prior assumptions or the proposal of an advance hypothesis may not be possible. We apply this method to analyze Twitter and YouTube activity of a range of protagonists to the conflict in an attempt to reveal additional insights into the relationships between them. By means of a network representation that combines multiple data views, we uncover communities of accounts falling into four categories that broadly reflect the situation on the ground in Syria. A detailed analysis of selected communities within the anti-regime categories is provided, focusing on their central actors, preferred online platforms, and activity surrounding real world events. Our findings indicate that social media activity in Syria is considerably more convoluted than reported in many other studies of online political activism, suggesting that alternative analysis approaches can play an important role in this type of scenario. Science Foundation Ireland 2CENTRE, the EU Cybercrime Centres of Excellence Network
Keyword(s): Machine learning; Statistics; Topic modeling; Topic coherence; LDA; NMF
Publication Date:
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: University College Dublin
First Indexed: 2015-07-30 05:15:24 Last Updated: 2018-10-11 15:33:00