Language as Influence(d): Power and Memorability
, Cornell University
Date: Wednesday, April 16, 2014
Time: 4:00 PM to 5:00 PM Note: all times are in the Eastern Time Zone
Refreshments: 3:45 PM
Location: 32-G449 (Stata Center - Patil/Kiva Conference Room)
Host: Jim Glass and Victor Zue, MIT CSAIL
Contact: Marcia G. Davidson, 617-253-3049, firstname.lastname@example.org
Speaker URL: None
TALK: Language as Influence(d): Power and Memorability
What effect does language have on people, and what effect do people have on language?
You might say in response, "Who are you to discuss these problems?" and you would be right to do so; these are Major Questions that science has been tackling for many years. But as a field, I think natural language processing and computational linguistics have much to contribute to the conversation, and I hope to encourage the community to further address these issues. To this end, I'll describe two efforts I've been involved in.
The first project provides evidence that in group discussions, power differentials between participants are subtly revealed by how much one individual immediately echoes the linguistic style of the person they are responding to. We consider multiple types of power: status differences (which are relatively static), and dependence (a more ''situational'' relationship). Using a precise probabilistic formulation of the notion of linguistic coordination, we study how conversational behavior can reveal power relationships in two very different settings: discussions among Wikipedians and arguments before the U.S. Supreme Court.
Our second project is motivated by the question of what information achieves widespread public awareness. We consider whether, and how, the way in which the information is phrased --- the choice of words and sentence structure --- can affect this process. We introduce an experimental paradigm that seeks to separate contextual from language effects, using movie quotes as our test case. We find that there are significant differences between memorable and non-memorable quotes in several key dimensions, even after controlling for situational and contextual factors. One example is lexical distinctiveness: in aggregate, memorable quotes use less common word choices (as measured by statistical language models), but at the same time are built upon a scaffolding of common syntactic patterns.
Joint work with Justin Cheng, Cristian Danescu-Niculescu-Mizil, Jon Kleinberg, and Bo Pang.
Lillian Lee is a professor of computer science at Cornell University. Her research interests include natural language processing, information retrieval, and machine learning. She is the recipient of the inaugural Best Paper Award at HLT-NAACL 2004 (joint with Regina Barzilay), a citation in "Top Picks: Technology Research Advances of 2004" by Technology Research News (also joint with Regina Barzilay), and an Alfred P. Sloan Research Fellowship; and in 2013, she was named a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI). Her group's work has received several mentions in the popular press, including The New York Times, NPR's All Things Considered, and NBC's The Today Show.
This CSAIL SEMINAR SERIES, organized in cooperation with the Siri team at Apple, invites leading researchers in HLT to give lectures that introduce the fundamentals of spoken language systems, assess the current state of the art, outline challenges, and speculate on how they can be met. Lectures occur 2-3 times per semester and should be accessible to undergraduates with some technical background.
Created by Marcia G. Davidson at Tuesday, March 25, 2014 at 12:18 PM.