In the months after the contested Iranian presidential election in June 2009, Iranians used Twitter-a social media service that allows users to send short text messages, called tweets, with relative anonymity-to speak out about the election and the protests and other events that followed it. The authors of this report used an automated content analysis program called Linguistic Inquiry and Word Count 2007 (LIWC) to analyze more than 2.5 million tweets discussing the Iran election that were sent in the nine months following it. The authors (1) identify patterns in word usage over the nine-month period and (2) examine whether these patterns coincided with political events, to gain insight into how people may have felt before, during, and after those events. For example, they compare how the frequencies with which negative sentiments were directed toward President Mahmoud Ahmadinejad, his election opponents, and President Barack Obama changed over time, and they track the way in which the use of swear words sharply increased in the days leading up to specific protests. Particularly in countries where freedom of expression is limited, automated analysis of social media appears to hold promise for such policy uses as assessing public opinion or outreach efforts and forecasting events such as large-scale protests. .

"National Security Research Division"--T.p.

Preface / Introduction. Analysis of Social Media Can Help Gauge Public Opinion and Mood in Closed Societies -- A New Computer-Based Tool Offers a Promising Means of Tapping into Politically Oriented Content in Social Media -- This Type of Analysis Can Have Important Policy Uses -- Organization of This Report / Methodology. The Precedent for Our Approach: Previous Research Using LIWC and Word-Usage Analysis -- LIWC Has Been Shown to Accurately Represent Verbal Expression -- The Real Potential of Exploring Word Usage Lies in Its Links with Behaviors and Outcomes -- Word Usage Is Now Being Studied in Politically Oriented Contexts -- Our Research Process -- Planning Tasks: Understanding the Sphere of Relevant Social Media -- Selecting Twitter Texts -- Selecting Iran-Relevant Political Topics -- Selecting the LIWC Word Categories to Use in Our Analysis and Defining How We Would Interpret Them / Background on Social Media Use in Iran and Events Surrounding the 2009 Election. Social Media Use in Contemporary Iran -- The Scale of Internet and Social Media Usage in Contemporary Iran -- Who Is Using Social Media in Iran? -- The Anonymity Factor -- The Iranian Information Environment Prior to the 2009 Presidential Election -- The Use of Social Media During the 2009 Presidential Election in Iran -- The Role of Social Media in Iran's Internal Politics Grew Rapidly After the 2009 Presidential Election -- Major Events in Iran During the Post-Election Period -- The Rise of Mass Protests -- June 19: Khamenei's Friday Prayer Speech -- June 20: Neda Agha-Soltan's Death -- July 9: Anniversary of the 1999 Student Uprisings -- August 5: Ahmadinejad's Inauguration -- September 18: Quds Day -- Late December: Ashura Day Protests -- February 11, 2010: 31st Anniversary of the Islamic Revolution / Overall Trends in Public Mood in Iran After the 2009 Presidential Election. Public Mood Throughout the Nine Months After the Election -- Twitter's Clearest Indicator of Mood and Forecaster of Action: Swear Words -- Use of Pronouns on Twitter After the Election -- Summary / Iranian Public Opinion About Specific Topics in the Aftermath of the 2009 Election. Public Opinion Leading Domestic Political Figures: Ahmadinejad, Khamenei, Mousavi, and Karroubi -- Summary -- Background -- Comparing Trends in Public Opinion About Political Figures -- Around the Quds Day Protest, Twitter Users Wrote More Negatively About Khamenei Than About Ahmadinejad -- At Certain Points, Twitter Users Wrote More Positively and Less Negatively About Karroubi Than About Mousavi -- Initially, Twitter Users Swore More About Ahmadinejad Than About Mousavi, but the Opposite Became True -- Policy Implications -- Pro-Government and Opposition Groups: The Green Movement, the Revolutionary Guards, and the Basij -- Summary -- Background -- Comparing Trends in Public Opinion About Political Groups -- The Green Movement Was Viewed More Positively Than the Revolutionary Guards or Basij -- Twitter Users Swore More About the Basij Than About the Revolutionary Guards -- Public Opinion About the United States, President Obama, and the CIA -- Summary -- Usage of Swear Words Suggests Early Frustration with the United States and President Obama, as Well as a Strong Desire for U.S. Action -- Usage of First-Person Singular Pronouns Regarding the United States and President Obama Generally Paralleled Usage of Swear Words -- Pronoun Use When Writing About Obama as Compared with Iranian Figures -- Twitter Users Expressed Less Negative Emotion When Writing About Obama as Compared with Iranian Figures -- Positive Emotions in Tweets About Obama Showed Several Pronounced Spikes Compared with Tweets About the United States -- Some Twitter Users Pointed to Foreign Influence, Particularly Intelligence Agencies, as the Driving Force Behind Protests -- Public Opinion About Specific Countries: Israel, the United States, and Iran -- Summary -- Twitter Users Only Infrequently Swore Regarding Israel or the United States -- Twitter Users Swore More When Referring to the "Islamic Republic" Than to "Iran" -- Twitter Users Expressed Positive Emotions Toward Israelis Who May Have Aided the Protest Movement / Methodological Considerations. Additional Demonstration of the Methodology: Sadness Words -- Linguistic Indicators That Did Not Work as Expected on Twitter -- Differences in Phrasing May Reflect Differing Intentions and Writing Styles -- Limitations of Automated Analysis Suggest That It Is a Complementary Approach to Manual Analysis / Next Steps: A Design for a Second Phase of This Program of Research. Looking Ahead Toward the 2013 Iranian Presidential Elections -- Validating the Methodology -- Improving Current Aspects of the Methodology -- Expanding the Scope of the Current Work / Appendix. Additional Details Regarding Methodology: Data Collection and Analysis.