III: Small: Topical Positioning System (TPS) for Informed Reading of Web Pages

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This work addresses the challenge of increasing the critical literacy of people looking for information on the Web, including information regarding healthcare, policy, or any other broadly discussed topic. The proposed research on Topical Positioning System "TPS" drives the vision of developing a browser tool that shows a person whether the web page in front of them discusses a provocative topic, whether the material is presented in a heavily biased way, whether it represents an outlier (fringe) idea, and how its discussion of issues relates to the broader context and to information presented in "familiar" sources. This research applies and extends text analysis and comparison techniques to this problem. It uses statistical language modeling, topic modeling, machine learning, and link analysis techniques to represent Web pages and clusters of Web pages. It requires both off-line pre-processing to organize web-scale collections and on-line, query-time fine-tuning of the organization for presentation in a TPS browser add-on. This research will be the foundation of class projects as well as graduate student research, exposing a large number of students to issues of web-based search and critical evaluation of information. More importantly, however, this work has the potential to impact many people, helping them make more informed choices in response to what they read on the Web and elsewhere. The results of this project will be published in peer-reviewed venues and listed at the project Web site (http://ciir.cs.umass.edu/research/tps). A freely available TPS browser add-on will be available at this Web site.