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Dec
6
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CITP Seminar: Eszter Hargittai – The Black Box of Information Access: Measuring People’s Algorithm Skills

Princeton School of Public and International Affairs

While we know that algorithms are an increasingly important part of what information people encounter in everyday life, little work has focused on studying users’ awareness and understanding of how algorithms may influence what they see and do. There is also more to learn about what actions users may be taking to try to influence what content they get from search engines, social media, video sites, and other online services. This presentation will discuss people’s algorithm skills drawing on data collected through interviews in several countries and through a national survey of US adults.

Bio:

Eszter Hargittai is a professor and holds the Chair of Internet Use and Society at the Institute of Communication and Media Research of the University of Zurich. She is a fellow of the International Communication Association and an External Member of the Hungarian Academy of Sciences. She is past fellow of the Center for Advanced Study in the Behavioral Sciences at Stanford and Harvard’s Berkman Center for Internet & Society. She has also held visiting positions at Trinity College, Dublin (Ireland), the University of St. Gallen (Switzerland), University of Queensland (Australia), and the University of Vienna (Austria).

Hargittai’s research looks at how people may benefit from or be left behind as a result of their varied digital media uses with a particular focus on how differences in people’s digital skills influence what they do online. She has looked at these questions in the domains of information seeking, health content (including Covid-19), political participation, job search, the sharing of creative content, and privacy management.

Hargittai’s work has received awards from several professional associations including the International Communication Association’s Outstanding Young Scholar Award. For her teaching, she received the Galbut Outstanding Faculty Mentor Award of the School of Communication at Northwestern University, which honors one faculty member each year for exemplary teaching and engagement with students both inside and outside of the classroom. She has published over 100 journal articles, dozens of book chapters, and has edited four books. In addition to having presented her work across the US, she has also given invited talks in 15 countries on four continents. She has keynoted 18 meetings, given over 160 invited talks, and has presented at numerous conferences.

Her work has been featured in many popular media outlets in the United States and internationally. Her research has been supported by the U.S. National Science Foundation, the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, Microsoft Research, Nokia, Google, Facebook, and Merck, among others.

Hargittai is editor of the Handbook of Digital Inequality (Edward Elgar Publishing, 2021), Research Exposed: How Empirical Social Science Gets Done in the Digital Age (Columbia University Press 2021), Digital Research Confidential (with Christian Sandvig, The MIT Press, 2015), and Research Confidential: Solutions to Problems Most Social Scientists Pretend They Never Have (University of Michigan Press, 2009). The latter three present a behind-the-scenes look at doing empirical social science research. She has published academic career advice at Inside Higher Ed under the Ph.Do column.

She has won some photo contests, has had her photography featured in books and calendars, and people she doesn’t know have been willing to part with their money to own some of her paintings.

She tweets @eszter.

To request accommodations for a disability please contact Jean Butcher, butcher@princeton.edu, at least one week prior to the event.

This talk will be recorded and posted here, on the CITP YouTube channel and on the Princeton University Media Central website.

Click here to watch the webinar.

Event Details

Date

December 6, 2022

Time

12:30 p.m.

Location

Campus Location

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