I’ll be speaking at the 2022 Politics and Computational Social Science conference today with my colleague Meg Heckman. We’ll be presenting work, with Emily Boardman Ndulue, that took an intersectional lens to analyzing how online news media covered the election of current US Vice President Kamala Harris.
Partisan Media Coverage and Intersectionality: A Case Study of Vice President Kamala Harris
Rahul Bhargava, Meg Heckman, Emily Boardman Ndulue
Talk abstract
Partisan news coverage of politicians is well documented and studied, as are the many ways sexist and racist tropes have historically played out about those who identify as women, people of color, or both. Our current U.S. online media environment, meanwhile, has been shown to have become increasingly polarized. Kamala Harris’s election to the vice presidency presents a unique opportunity to study how these trends play out with regards to her various identities (woman, Black, Southeast Asian, mixed-culture household). To analyze coverage of Harris, we built on prior work to create collections of online news media grouped by a partisan score based on link sharing in a panel of Twitter users associated with voter registration records. We gathered and analyzed a corpus of news stories about VP Harris from these sources from August 2020 through April 2021 (n=17,165). Employing computational and qualitative methods, we found strong evidence of coverage of Harris playing out differently across an asymmetrically polarized media landscape. We found evidence of varying levels of sexist and racist tropes in all sources—but on the far right we discovered a particular cluster of (often factually incorrect) narratives that did not appear elsewhere on the partisan spectrum. Our work contributes to our growing understanding of how online media portray female politicians with multiple identities, suggesting that new intersectional biases may play out as this population grows.
Read the associated piece for Nieman Labs: It’s O.K. to write about women, fashion, and politics — but here’s how to do it better
