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What and Who

Machine Learning for Social Systems: Modeling Opinions, Activities, and Interactions

Julian McAuley
Stanford University
SWS Colloquium

Julian McAuley is a postdoctoral scholar at Stanford University, where he works with Jure Leskovec on modeling the structure
and dynamics of social networks. His current work is concerned with modeling opinions and behavior in online communities, especially
with respect to their linguistic and temporal dimensions. Previously, Julian received his PhD from the ANU under Tiberio Caetano, with
whom he worked on inference and learning in structured output spaces. His work has been featured in Time, Forbes, New Scientist,
and Wired, and has received over 30,000 "likes" on Facebook.
SWS, RG1  
AG Audience
English

Date, Time and Location

Thursday, 6 March 2014
11:30
90 Minutes
G26
113
Kaiserslautern

Abstract

The proliferation of user-generated content on the web provides a wealth of opportunity to study humans through their online traces.
I will discuss three aspects of my research, which aims to model and understand people's behavior online. First, I will develop rich
models of opinions by combining structured data (such as ratings) with unstructured data (such as text). Second, I will describe how
preferences and behavior evolve over time, in order to characterize the process by which people "acquire tastes" for products such
as beer and wine. Finally, I will discuss how people organize their personal social networks into communities with common interests
and interactions. These lines of research require models that are capable of handling high-dimensional, interdependent, and
time-evolving data, in order to gain insights into how humans behave.

Contact

Claudia Richter
9303 9103
--email hidden

Video Broadcast

Yes
Saarbrücken
E1 5
029
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Claudia Richter, 03/04/2014 15:33 -- Created document.