[talks] Colloquium Speaker Robert West, Friday April 15- 12:30pm

Mitra D. Kelly mkelly at CS.Princeton.EDU
Thu Apr 14 10:03:03 EDT 2016


Colloquium Speaker

Robert West, Infolab at Stanford University

Friday April 15- 12:30pm 

Computer Science 105

 

Human Behavior in Networks

 

Humans as well as information are organized in networks. Interacting with
these networks is part of our daily lives: we talk to friends in our social
network; we find information by navigating the Web; and we form opinions by
listening to others and to the media. Thus, understanding, predicting, and
enhancing human behavior in networks poses important research problems for
computer and data science with practical applications of high impact. In
this talk I will present some of my work in this area, focusing on (1) human
navigation of information networks and (2) person-to-person opinions in
social networks.

 

Network navigation constitutes a fundamental human behavior: in order to
make use of the information and resources around us, we constantly explore,
disentangle, and navigate networks such as the Web. Studying navigation
patterns lets us understand better how humans reason about complex networks
and lets us build more human-friendly information systems. As an example, I
will present an algorithm for improving website hyperlink structure by
mining raw web server logs. The resulting system is being deployed on
Wikipedia's full server logs at terabyte scale, producing links that are
clicked 10 times as frequently as the average link added by human Wikipedia
editors.

 

Communication and coordination through natural language is another prominent
human network behavior. Studying the interplay of social network structure
and language has the potential to benefit both sociolinguistics and natural
language processing. Intriguing opportunities and challenges have arisen
recently with the advent of online social media, which produce large amounts
of both network and natural language data. As an example, I will discuss my
work on person-to-person sentiment analysis in social networks, which
combines the sociological theory of structural balance with techniques from
natural language processing, resulting in a machine learning model for
sentiment prediction that clearly outperforms both text-only and
network-only versions.

 

I will conclude the talk by sketching interesting future directions for
computational approaches to studying and enhancing human behavior in
networks.

 

Bio:

Robert West is a sixth-year Ph.D. candidate in Computer Science in the
Infolab at Stanford University, advised by Jure Leskovec. His research aims
to understand, predict, and enhance human behavior in social and information
networks by developing techniques in data science, data mining, network
analysis, machine learning, and natural language processing. Previously, he
obtained a Master's degree from McGill University in 2010 and a Diplom
degree from Technische Universität München in 2007.

 

 

 

Mitra Kelly

Academic Secretary

Princeton University

Computer Science Dept

35 Olden Street

Princeton NJ 08540

mkelly at cs.princeton.edu <mailto:mkelly at cs.princeton.edu> 

609-258-4562

 

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