Today, we are joined by Liza Gak, a Ph.D student at UC Berkeley. Liza’s research interest lies around human-computer interaction (HCI), social computing, and how people are harmed online. She discusses her research on .
She started by discussing some observations from her study on weight loss ads, many of which are not in the interest of the ad viewers. She also discussed the problem with weight loss ads and unsubstantiated facts. Speaking of her research methodology, Liza explained how she sourced respondents for her interviews. She delved into the kind of questions asked and the strategies she employed in eliciting information from the respondents.
Liza explained how she grouped and coded the qualitative data using the inductive iterative approach. She spoke about her findings, iterating how weight loss ads target the vulnerable. She then discussed the several sources of harm in weight loss ads.
Liza discussed how advertisers can be more transparent with the data they use for ad targeting. She also explained how ad distribution platforms can play a role in ameliorating the harm ads cause to users.
I am a third year PhD student at the School of Information at UC Berkeley, where I am advised by Dr. Niloufar Salehi. Most recently, I published The Distressing Ads That Persist: Uncovering The Harms of Targeted Weight-Loss Ads Among Users with Histories of Disordered Eating at CSCW 2022. I am interested broadly in human-computer interaction, social computing, online harms, and virtual communities. My research is generously funded by the National Science Foundation Graduate Research Fellowship, the Center for Technology, Society, and Policy, and the Algorithmic Fairness and Opacity Group. In the past, I have worked at Meta, AT&T, and US Bank. I graduated from Washington University in St. Louis, studying Computer Science, Mathematics, and American Culture Studies.
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