Abstract

The fallacy of premature designations such as “Iran's Twitter Revolution” can be attributed to the empirical gap in our knowledge about such sociotechnical phenomena in non-Western societies. To fill this gap, we need in-depth analyses of social media use in those contexts and to create detailed maps of online public environments in such societies. This paper aims to present such cartography of the political landscape of Persian Twitter by studying the case of Iran's 2013 presidential election. The objective of this study is twofold: first, to fill the empirical gap in our knowledge about Twitter use in Iran, and second, to develop computational methods for studying Persian Twitter and identify the best methods for addressing different issues. During Iran's 2013 presidential election, three million tweets were collected and analyzed using social network analysis and machine learning. The findings provide a more nuanced view of the political landscape of Persian Twitter and identify patterns in accordance with or in contrast to those identified in the English-speaking Twittersphere around the 2013 presidential election. Persian Twitter was dominated by micro-celebrities, whereas institutional elites dominated English discourse about Iran on Twitter. The results also illustrate that Persian Twitter in 2013 was predominantly in favor of reformists. Finally, this study demonstrates that sentiment analysis toward political name entities can be used efficiently for mapping the political landscape of conversation on Twitter.