Friday, October 10, 09:30 a.m.
Where: 3002 Newell-Simon Hall
LTI PhD Thesis Defense
Polarizing opinions about political and social issues take place commonly in mass and user-generated media. A democratic society
builds on civic discussions between people holding different beliefs. However, so far few computer technologies are devoted to
facilitate mutual understanding.
We envision a computer system that can automatically understand different ideological viewpoints on an issue, and can identify
biased news stories, blog posts, and television news. Such a computer system can raise news readers' awareness of individual
+ Computer understanding of ideological perspectives, however, has been long considered almost impossible. In this thesis, we show
that ideology, although very abstract, exhibits a concrete pattern when it is communicated among a group of people who share similar
beliefs in written text, spoken text, television news video, and web video folksonomies. This emphatic pattern in ideological
discourse opens up a new field of automatic ideological analysis, and enables a large amount of ideological text and video to be
+ We develop a new statistical model, called Joint Topic and Perspective Models, for the emphatic pattern in ideological
discourse. The model combines two essential aspects of ideological discourse: topics and ideological biases. The
simultaneous inference on topics and ideological emphasis, however, poses a computational challenge. We develop an
approximate inference algorithm based on variational methods.
+ The emphatic pattern in ideological discourse enables many interesting applications in text analysis and multimedia content
understanding. At the corpus level, we show that ideological discourse can be reliably distinguished from non-ideological
discourse. At the document level, we show that the perspective from which a document is written or a video is produced can be
identified with high accuracy. At the sentence level, we summarize an ideological document by selecting sentences that
strongly express a particular perspective.