"THE RUSSIANS ARE HACKING MY BRAIN!" investigating Russia's internet research agency twitter tactics during the 2016 United States presidential campaign. (October 2019)
- Record Type:
- Journal Article
- Title:
- "THE RUSSIANS ARE HACKING MY BRAIN!" investigating Russia's internet research agency twitter tactics during the 2016 United States presidential campaign. (October 2019)
- Main Title:
- "THE RUSSIANS ARE HACKING MY BRAIN!" investigating Russia's internet research agency twitter tactics during the 2016 United States presidential campaign
- Authors:
- Linvill, Darren L.
Boatwright, Brandon C.
Grant, Will J.
Warren, Patrick L. - Abstract:
- Abstract: This study analyzed tweets from handles associated with the Russian Internet Research Agency in an effort to better understand the tactics employed by that organization on the social media platform Twitter in their attempt to influence U.S. political discourse and the outcome of the 2016 U.S. Presidential election. We sampled tweets from the month preceding the election and analyzed to understand the qualitative nature of these tweets as well as quantitative differences between how types of IRA Twitter accounts communicated. Seven categories of tweet behavior were identified: attack left, support right, attack right, support left, attack media, attack civil institutions, and camouflage. While camouflage was the most common type of tweet (52.6%), descriptive analyses showed it was followed by attack left (12%) and support right (7%). A variety of quantitative differences were shown between how account types behaved. Highlights: We sampled Russian Internet Research Agency tweets from the month preceding the 2016 U.S. Presidential election. We analyzed tweets to understand IRA messaging as well as differences between how types of IRA accounts communicated. Seven distinct categories of behavior were identified and categories were employed differently by account type. We discuss implications for what findings mean relative to prevailing and competing narratives surrounding IRA activity. Findings suggest the IRA was both sowing division while also supporting candidateAbstract: This study analyzed tweets from handles associated with the Russian Internet Research Agency in an effort to better understand the tactics employed by that organization on the social media platform Twitter in their attempt to influence U.S. political discourse and the outcome of the 2016 U.S. Presidential election. We sampled tweets from the month preceding the election and analyzed to understand the qualitative nature of these tweets as well as quantitative differences between how types of IRA Twitter accounts communicated. Seven categories of tweet behavior were identified: attack left, support right, attack right, support left, attack media, attack civil institutions, and camouflage. While camouflage was the most common type of tweet (52.6%), descriptive analyses showed it was followed by attack left (12%) and support right (7%). A variety of quantitative differences were shown between how account types behaved. Highlights: We sampled Russian Internet Research Agency tweets from the month preceding the 2016 U.S. Presidential election. We analyzed tweets to understand IRA messaging as well as differences between how types of IRA accounts communicated. Seven distinct categories of behavior were identified and categories were employed differently by account type. We discuss implications for what findings mean relative to prevailing and competing narratives surrounding IRA activity. Findings suggest the IRA was both sowing division while also supporting candidate Trump. … (more)
- Is Part Of:
- Computers in human behavior. Volume 99(2019)
- Journal:
- Computers in human behavior
- Issue:
- Volume 99(2019)
- Issue Display:
- Volume 99, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 99
- Issue:
- 2019
- Issue Sort Value:
- 2019-0099-2019-0000
- Page Start:
- 292
- Page End:
- 300
- Publication Date:
- 2019-10
- Subjects:
- Interactive computer systems -- Periodicals
Man-machine systems -- Periodicals
004.019 - Journal URLs:
- http://www.sciencedirect.com/science/journal/07475632 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.chb.2019.05.027 ↗
- Languages:
- English
- ISSNs:
- 0747-5632
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.921600
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16409.xml