De-anonymizing Social Network Neighborhoods Using Auxiliary and Semantic Information
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Authors
Morgan, Steven Michael
Novillo, Jorge; Adviser
Andriamanalimanana, Bruno; Reviewer
Reale, Michael; Reviewer
Issue Date
2015-12-11
Type
Thesis
Language
en_US
Keywords
social networks , semantic information , data mining , auxiliary information , textual analysis , social network data
Alternative Title
Abstract
The increasing popularity of social networks and their progressively more robust uses provides an interesting intersection of data. Social graphs have been rigorously studied for de-anonymization. Users of social networks will provide feedback
to pages of interest and will create a vibrant profile. In addition to user interests, textual analysis provides another feature set for users. The user profile can be viewed as a classical relational dataset in conjunction with graph data. This paper uses semantic information to improve the accuracy of de-anonymizing social network data.
Description
Approved and recommended for acceptance as a thesis in partial fulfillment of the requirements for the degree of Master of Science in Computer and Information Science.