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Algorithms and social media: Don't forget the users

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Venue: Birkbeck Main Building, Malet Street

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Many of us are working on building systems that aim to solve important problems, with an ultimate goal to "help" users. This is what many areas in computer science are about. A big focus has been for the last 10 to 20 years to make sense of social media, and build algorithms to support users in some of their leisure- and work-related tasks.


In this talk, I am arguing that we need consider two things when we build algorithms for social media: the source of what we use as input to the algorithms, and whether users are impacted the way we want to impact them. The talk is based on two uses cases around providing diversity (something many of us believe is good) to users: (1) Engaging through diversity - serendipity (same algorithm, different sources); and (2) Engaging through diversity - awareness (effective algorithm, perception). My goal is to say, we may have the best algorithms, but we may get it wrong if we forget the users. It is important that we ask the right questions and evaluate appropriately in today's world, when we build algorithmic solutions to distribute, inform, recommend, or simply display information from social media to users.

This talk is based on a presentation at the WWW 2017 workshop "International Workshop on Modeling Social Media: Machine Learning and AI for Modeling and Analyzing Social Media"

Biog

Mounia Lalmas is a Director of Research at Yahoo, where until recently she led a team of scientists working on Advertising Quality. She has just joined the Publisher Science team at Yahoo working on building personalised and engaging products and services. She also holds an Honorary Professorship at University College London. Prior to this, she held a Microsoft Research/RAEng Research Chair at the School of Computing Science, University of Glasgow. Before that, she was Professor of Information Retrieval at the Department of Computer Science at Queen Mary, University of London. Her work focuses on studying user engagement in areas such as native advertising, digital media, social media, and search.

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