Decoding networked publics on Persian Twitter: Tweet type, tone and orientation to characters in Iran 2017 presidential election

This research sheds light on networked publics’ activism on Persian Twitter. Networked publics is a phenomena to understand dynamics and practices of social media users. Based on this concept and networked framing theory, we investigated tweet types, tweet tones and the ways of framing characters (and tweet orientation toward them) by networked publics on Persian Twitter during Iran 2017 presidential election. We combined social network analysis, ethnographic content analysis and social media critical discourse study approach. First, we collected 2596284 tweets during the election period. Then, we focused on retweet (RT) network as the information diffusion network, and discovered networked publics by applying cluster analysis on this corpus. Afterwards, we identified 50 top influential users in each cluster based on their PageRanks. Finally, we collected all tweets of these users in the whole network and analyzed them. We used 3 coders to code the selected sample of 10416 tweets in 3 rounds. Results showed that commentary, quotation and news are the most frequent tweet types. Furthermore, Iranian users mostly tweeted using serious and sarcastic tones. Finally, our finding showed that Rouhani was the first name in framed characters.