This paper asks whether US economic sanctions during the Trump presidency reduced support for Iran’s government or instead produced a "rally-around-the-flag" effect among Iranian influencers and their audiences. Using a large-scale supervised machine-learning analysis of nearly two million tweets from more than 1,000 Iranian influencers, the authors compare reactions to comprehensive versus targeted sanctions and examine variation by political faction and by which entity was targeted.
Supervised machine learning, Nearly two million tweets, Comparing comprehensive and targeted sanctions
Data and methods
The study analyzes nearly two million tweets from over 1,000 Iranian influencers collected during Donald Trump’s presidency. The authors apply supervised machine-learning and text-analysis techniques to measure expressed sentiment toward the Iranian government in response to sanctions events; the abstract reports attention to different sanction types (comprehensive vs. targeted) and to variation across political factions.
Main findings
According to the abstract, the authors find that comprehensive sanctions tended to improve sentiments toward the Iranian government, including among moderate opposition accounts, aligning them more with the state’s position. Targeted sanctions produced a weaker rally effect, and the size of that reaction depended on which entity was targeted.
- Comprehensive sanctions are reported to have generally increased pro-government sentiment.
- Targeted sanctions produced milder effects, with variation tied to the identity of the target.
