Online Social Media in the Syria Conflict: Encompassing the Extremes and the In-Betweens

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Title: Online Social Media in the Syria Conflict: Encompassing the Extremes and the In-Betweens
Authors: O'Callaghan, DerekPrucha, NicoGreene, DerekConway, MauraCarthy, JoeCunningham, Pádraig
Permanent link: http://hdl.handle.net/10197/6684
Date: 20-Aug-2014
Online since: 2015-07-28T16:58:34Z
Abstract: 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.
Funding Details: Science Foundation Ireland
2CENTRE, the EU Cybercrime Centres of Excellence Network
Type of material: Conference Publication
Keywords: Machine learningStatisticsTopic modelingTopic coherenceLDANMF
DOI: 10.1109/ASONAM.2014.6921619
Other versions: http://www.asonam2014.org/
Language: en
Status of Item: Peer reviewed
Is part of: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2014
Conference Details: The 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'14), 17-20 August, Beijing, China
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Insight Research Collection

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