Zayne Sember

I am a social and data scientist who uses computational methods to study social systems—in particular, how elections are administered in the United States. I am the Research Director at the MIT Election Data and Science Lab (MEDSL), whose mission is to improve the democratic experience for all U.S. voters. Managing a team of research staff and students, I oversee MEDSL’s election datasets, lead novel academic research, and produce flagship data products like the Elections Performance Index.

My own research asks when and how members of Congress respond to the people they represent. I treat legislators’ public communications—press releases, speeches, social media—as text-as-data: my dissertation, Timely Talk, traces how members adapt what they say as their districts and the national mood shift, and related work looks at election administration and affective polarization.

Outside of election science I enjoy developing new data science tools. I created speccurvieR, an R package for fast, pretty, and easy specification curve analysis (available on CRAN), wrote pressR to scrape and tidy the press releases of nearly every member of Congress, and built SufjanViz, a dashboard analyzing the discography of one of my favorite musicians.