STORYTELLING WITH NETWORK DATA VISUALIZATION HASHTAG #PRAYFORTURKEY ON TWITTER

Abstract

The characteristics of Twitter allow people to create messages of social movements that can distribute throughout the network without having to have friendly relations between Twitter users. In the context of this paper, data visualization uses graph theory and network analysis methods to facilitate the identification and analysis of the distribution of the #PrayForTurkey hashtag message network. This paper tries to analyze the pattern of communication networks and the role of the centrality of actors in hashtags #PrayForTurkey as a disaster mitigation effort in finding the network to reach all actors and identify Key Players in Twitter effectively. This paper provides information on each actor's role in a social network with a social network analysis approach that focuses on the value of the relations between actors. These relations build various #PrayForTurkey network structures. Through network visualization with storytelling technique, the role of key players had identified. At the actor level, the analysis carried out is the centrality of the actors involved connected in the #PrayForTurkey network. Actor centrality analysis to find out the role of key players in distributing the digital solidarity message.