Exploring and Evaluating the Patterns of How Iranian Twitter Users Are Affected by the Political Attitudes of Influencers

Abstract

In this research, through identifying the components of what is called “Iranian Twitter", we tried to identify and evaluate the patterns of how Iranian Twitter users are affected by the political attitudes of the Iranian Twitter Influencers. For this purpose, Influencers and Followers including 917,318 Iranian users of Twitter were categorized based on their political attitudes; then, patterns of how Followers were affected by Influencers were identified and evaluated for various political attitudes. To categorize Influencers and Followers, we used data mining techniques, and to analyze network data, we applied Gephi software. The results showed that although none of the political attitudes in Iranian Twitter have significant superiority to others, a significant proportion of users who favored a political attitude, displayed little tendency to be exposed to different political messages.