Timestamp-based correlation measures for finding hidden groups in chat rooms

Authors
Willmore, Christopher P.
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Other Contributors
Goldberg, Mark
Issue Date
2008-05
Keywords
Computer science
Degree
MS
Terms of Use
Attribution-NonCommercial-NoDerivs 3.0 United States
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
Abstract
This thesis describes a new two-step algorithm for finding hidden groups from chat transcripts, that is, transcripts of communication where the recipient of a message is not known. The algorithm is presented in two steps: calculating a correlation value between every pair of users in the chat transcript, and finding clusters in the weighted undirected graph that results. The inter-user correlation can be calculated in a number of different ways, some of which are accomplished by projecting individual user transcripts into an inner product space. The clustering step uses the existing iterative-scan algorithm, with some new modifications. This approach is found to work under limited conditions.
Description
May 2008
School of Science
Department
Dept. of Computer Science
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
Access
CC BY-NC-ND. Users may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.