Defense Event

Mining Multiple Perspectives From Social Media and Scientific Literature

Amjad Abu Jbara

Monday, April 22, 2013
09:00am - 11:00am
3725 BBB

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About the Event

This thesis studies how Natural Language Processing techniques can be used to mine perspectives from textual data. The first part of the thesis focuses on analyzing the text posted by people who participate in discussions on social media sites. We particularly focus on threaded discussions that discuss ideological and political topics. The goal is to identify the different viewpoints that the discussants have with respect to the discussion topic. We use subjectivity and sentiment analysis techniques to identify the attitudes that the participants carry toward one another and toward the different aspects of the discussion topic. This involves identifying opinion expressions and their polarities, and identifying the targets of opinion. We use this information to represent discussions in one of two representations: discussant attitude vectors or signed attitude networks. We use data mining and network analysis techniques to analyze these representations to detect rifts in discussion groups and study how the discussants split into subgroups with contrasting opinions. In the second part of the thesis, we focus on mining perspectives from scientific literature. We analyze the text adjacent to reference anchors in scientific articles as a means to identify researchers’ viewpoints toward previously published work. We propose methods for identifying, extracting, and cleaning citation text. We analyze this text to identify the purpose (author’s intention) and polarity (author’s sentiment) of citation. Finally, we present several applications that can benefit from this analysis such as generating multi-perspective summaries of scientific articles and predicting future prominence of publications.

Additional Information

Sponsor(s): Dragomir Radev

Open to: Public