This paper investigates the manipulation strategies by the Iranian regime in suppressing and dismantling the #MahsaAmini movement on Iranian Twittersphere (Persian Twitter). #MahsaAmini movement started in the middle on September 2022 in protests against the murder of a young girl by the Iranian regime’s ‘morality police.’ It soon became a massive online protest with more than 500 million and counting tweets against the regime’s brutality, mismanagement, and incapability. In response, the regime took several strategies to suppress this movement on Twitter. I will draw on the existing literature on computational propaganda to investigate the networks and strategies through which the Iranian regime manipulated #MahsaAmini on Twitter.
The research data is collected from 15 September 2022 to 15 November 2022 from Twitter Academic API. I identified the most popular tweets with more than 1k likes per day (N= 105,000). Then, I identified the tweets’ authors (N= 9,857). Next, I collected all tweets from those users in the first two months of the movement (N=8,178,950). I will combine computational methods with qualitative interpretations to identify the user type, bot probability, identity, and political affiliation. Also, a team of human coders will code a random sample of tweets to explore the regime’s suppressive strategies. Finally, I will combine the qualitative results with supervised machine learning (automated text analysis) to investigate the suppression on a big scale. The findings will contribute to the growing body of literature on computational propaganda in contemporary societies, particularly by focusing on an understudied context: Iran.