Unsupervised Machine Learning Reveals How the Twitter Topic Patterns of the Russian-Backed Internet Research Agency (IRA) Evolved Over Time (Presentation)
Abstract
Information Operations (IO) are a key component of our adversaries' strategy to undermine U.S. military power without escalating to more traditional (and more easily identifiable) military strikes. Social media activity is one method of IO. In 2017 and 2018, Twitter suspended thousands of accounts likely belonging to the Kremlin-backed Internet Research Agency (IRA). Clemson University archived a large subset of these tweets (2.9M tweets posted by over 2800 IRA accounts), tagged each tweet with metadata (date, time, language, supposed geographical region, number of followers, etc.), and published this dataset on the polling aggregation website FiveThirtyEight. Machine Learning researchers at the Institute for Defense Analyses (IDA) downloaded Clemson's dataset from FiveThirtyEight and analyzed both the content of the IRA tweets and their accompanying metadata. Using unsupervised learning techniques (Latent Dirichlet Allocation), IDA researchers mapped out how the patterns in the IRA's tweet topics evolved over time. Results showed that the IRA started tweeting in/before February 2012, but ramped up significantly in May/June 2015. Most tweets were in English, and most likely targeted the U.S. The IRA created new accounts after the first Twitter suspension in November 2017, with each new account quickly establishing an audience. Between at least January 2015 and October 2017, the IRA's English tweet topics evolved over time, becoming tighter, more specific, more negative, and more polarizing, with the final pattern emerging in late 2015. The United States government must expect that our adversaries' social media activity will continue to evolve over time. Efficient processing pipelines are needed for semi-automated analyses of time-evolving social media activity.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2020
- Accession Number
- AD1222299
Entities
People
- Emily M. Parrish
- Jenny R. Holzer
- Shelley M. Cazares
Organizations
- Institute for Defense Analyses