Newswise — A University of Arkansas at Little Rock professor has received $230,000 to help defend the United States against the use of social bots.
Dr. Nitin Agarwal, Jerry L. Maulden-Entergy Endowed Chair of Information Science, received the grant to develop a socio-computational model for the U.S. Defense Advanced Research Projects Agency (DARPA) to detect the online presence of social bots.
These bots automatically generate messages that persuade social media users on particular issues, ideas, and campaigns.
Agarwal is working with Intelligent Automation, Inc., a company based in Rockville, Maryland, that specializes in research and development for federal agencies and corporations in the United States.
Agarwal will work on multiple tasks to better understand how social bots have affected public discourse at a social and computational level. These tasks include identifying specific cases in which these bots have affected information and data collection, examining the computational framework of bots, discovering what a bot can and cannot do in a social media space, and developing behavior models to identify strategies in which bots are used.
"It is vital to study these rapidly evolving cyber warfare tactics to understand influence operations conducted on social media that distort public discourse, weaponize narratives, and fabricate perceptions," Agarwal said.
"In this project, we will develop and perfect methodologies informed by social science and computational social network analysis to study the information dissemination and coordination behaviors of social bots and to aid the development of detection tools ready for deployment in cyber operations."
In the next phase of the project, Agarwal will explore the content that social bots create, map their behavior, and explore their effectiveness in information campaigns.
This project is sponsored by the United States Department of Defense. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the agency.