Community Detection in Twitter
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Title
Community Detection in Twitter
Author
Kewalramani , Mohit Naresh
Advisors
Finin , Timothy
Program
Computer Science
UMBC Department
Computer Science and Electrical Engineering
Document Type
thesis
Sponsors
University of Maryland , Baltimore County (UMBC) .
Keywords
clusters ; community ; groups ; twitter
Date Issued
2011-01-01
Abstract
Twitter has evolved into a source of social , political and real time information in addition to being a means of mass-communication and marketing . Monitoring and analyzing information on Twitter can lead to invaluable insights , which might otherwise be hard to get using conventional media resources . An important task in analyzing highly networked information sources like twitter is to identify communities that are formed . A community on twitter can be defined as a set of users that are more similar to other members than to non-members . We present a technique to devise a similarity metric between any two users on twitter based on the similarity of their content , links and metadata . The link structure on Twitter can be characterized using the twitter notion of followers , being followed and the @Mentions , @Reply and @RT tags in tweets . Content similarity is characterized by the words in the tweets combined with the hash-tags they are annotated with. Meta-data similarity includes similarity based on other sources of user information such as location , age and gender . We then use this similarity metric to cluster users into communities using spectral and bottom-up agglomerative hierarchical clustering . We evaluate the performance of clustering using different similarity measures on different types of datasets . We also present a heuristic to find communities in twitter that take advantage of the network characteristics of twitter .
Identifier
10524
Format
application:pdf
Language
en
Collection
UMBC Thesis and Dissertations .
Rights Statement
This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. for permission to publish or reproduce, please see http://aok.lib.umbc.edu/specoll/repro.php or contact Special Collections at speccoll(at)umbc.edu.
Source
Kewalramani_umbc_0434M_10524.pdf
Access Rights
Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan through a local library, pending author/copyright holder's permission.
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