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Advertising on Social Media – Keynote Talk – Krishna Gummadi (MPI-SWS, Germany) – COMSNETS 2018

Abstract: All popular social media sites like Facebook, Twitter, and Pinterest are funded by advertising, and the detailed user data that these sites collect about their users make them attractive platforms for advertisers. In this talk, I will first present an overview of how social media sites enable advertisers to target their users. Next, I will pose and attempt to answer the following four high-level questions related to privacy, fairness, transparency and control of social media advertising today. Privacy threats: what personal information about users are the sites leaking to advertisers to enable targeted ads? Fairness: can an advertiser target users in a discriminatory manner? If so, how can we detect and prevent discriminatory advertising? Transparency: can users learn what personal data about them is being used when they are targeted with an ad? Control: can users control what personal data about them is being used when they are targeted with an ad? About Krishna: Krishna Gummadi is a tenured faculty member and head of the Networked Systems research group at the Max Planck Institute for Software Systems (MPI-SWS) in Germany. He received his Ph.D. (2005) and M.S. (2002) degrees in Computer Science and Engineering from the University of Washington. He also holds a B.Tech (2000) degree in Computer Science and Engineering from the Indian Institute of Technology, Madras. Krishna’s research interests are in the measurement, analysis, design, and evaluation of complex Internet-scale systems. His current projects focus on understanding and building social computing systems. Specifically, they tackle the challenges associated with (i) assessing the credibility of information shared by anonymous online crowds, (ii) understanding and controlling privacy risks for users sharing data on online forums, (iii) understanding, predicting and influencing human behaviors on social media sites (e.g., viral information diffusion), and (iv) enhancing fairness and transparency of machine (data-driven) decision making in social computing systems. Krishna’s work on online social networks, Internet access networks, and peer-to-peer systems has led to a number of widely cited papers and award papers at IW3C2’s WWW, NIPS’s ML & Law Symposium, ACM’s COSN, ACM/Usenix’s SOUPS, AAAI’s ICWSM, Usenix’s OSDI, ACM’s SIGCOMM IMC, and SPIE’s MMCN conferences. He has also co-chaired AAAI’s ICWSM 2016, IW3C2 WWW 2015, ACM COSN 2014, and ACM IMC 2013 conferences.

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