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Dynamic Analysis of Communication Processes using Twitter Data

Authors:
Ingo J. Timm
Jan Ole Berndt
Fabian Lorig
Christof Barth
Hans-Jürgen Bucher

Keywords: Social Network Analysis; Conversation Detection; Networks of Communication; Data Collection and Handling; Simulation Methodology

Abstract:
Due to the omnipresence of information technology and the increasing popularity of online social networks (OSN), communication behavior has changed. While companies benefit from, i.e., viral marketing campaigns, they are challenged by negative phenomena, like Twitterstorms (shitstorms). Using existing empirical approaches and theories for analyzing the dynamics of social media communication processes and for predicting the success of a campaign is challenging as the circumstances and the access to communication processes have changed. Agent-based social simulation (ABSS) provides approaches to overcome existing restrictions, e.g., privacy settings, and to develop a framework for the dynamic analysis of communication processes, e.g., for evaluating or testing OSN marketing strategies. This requires both a valid simulation model and a set of real world data serving as input for the model. In this paper, a procedure model for the creation of a simulation model is developed and the steps are demonstrated by examples.

Pages: 14 to 22

Copyright: Copyright (c) IARIA, 2016

Publication date: November 13, 2016

Published in: conference

ISSN: 2519-8351

ISBN: 978-1-61208-519-7

Location: Barcelona, Spain

Dates: from November 13, 2016 to November 17, 2016