Professor Uses Tech to Tackle Social Problems

A Mason Engineering professor is using the power of technology and artificial intelligence (AI) to tackle social problems on the web by analyzing social media messages. Hemant Purohit, assistant professor of information sciences and technology, has been working with Bonnie Stabile from the Schar School of Policy and Government for the last two years on their multidisciplinary research project to use AI techniques to look at the connection between social media and its impact on policy and law and the way people perceive misleading or misguided information on the web. “We address this problem of how policies to support women’s empowerment are undermined due to the way women are negatively socially constructed in online social spaces by people with potentially malicious intent,” says Purohit. “Like the Stanford swimmer sexual assault case, where some people took a stand for the accused and they were maliciously creating uncertainty about the survivor.” Purohit and his PhD student Rahul Pandey, in collaboration with Stabile and her PhD student Aubrey Grant, created a computational framework to collect, process, and analyze social media messages discussing rape or sexual assault topics using natural-language

ILLUSTRATION BY CLAIRE BRANDT

understanding methods of AI. Purohit says the group then categorized their data set of tweets into four categories based on intent: accusational, validational, sensational, and other. “We found that nearly half of 100,000 tweets referencing key terms associated with ‘rape’ and ‘deception’ were accusational, meaning that they blamed, disparaged, and disbelieved women reporting rape or sexual assault,” says Stabile. In comparison, only 12 percent of these tweets validated the victim, making accusational and negative tweets almost three times as prevalent. Stabile and Purohit believe this reflects an unfortunate reality of how social construction in online public conversations could influence the implementation and actual impact of policy and laws, given that there are several strong policies and laws in place to curb gender violence and sexual assault. “We believe that this both reflects damaging portrayals of those who experience sexual assault and can serve to perpetuate such portrayals,” says Stabile. “Such evidence is critical in bringing attention to how women, the predominant victims of sexual assault and harassment, can be mischaracterized in ways that can disadvantage them when policy is made.” Purohit and Stabile have worked on numerous papers and intend to pursue further research that connects AI and policy. “We will continue to explore other application areas of policy and laws where we could take our multidisciplinary research approach to study the social media and web spaces with theoretically inspired computational methods,” says Purohit. “We are currently exploring hate speech on social media platforms and how to detect and mitigate that, again given the fact that there are already many policies and laws to prevent this phenomenon.”

Assistant Professor Hemant Purohit uses artificial intelligence and machine learning to analyze social media posts for different social causes. Photo by Ron Aira

—Ryley McGinnis