User Interests Identification on Twitter Using a Hierarchical Knowledge Base

TitleUser Interests Identification on Twitter Using a Hierarchical Knowledge Base
Publication TypeConference Proceedings
Year of Publication2014
AuthorsPavan Kapanipathi, Prateek Jain, Chitra Venkataramani, Amit Sheth
EditorValentina Presutti, Milan Stankovic, Erik Cambria, Iván Cantador, Angelo DiLorio, Tommaso DiNoia, Christoph Lange, Diego Reforgiato-Recupero, Anna Tordai
Conference Name11th Extended Semantic Web Conference (ESWC 2014)
PublisherSpringer International Publishing
Conference LocationCrete, Greece
ISSN Number978-3-319-12023-2
KeywordsHierarchical Interest Graph, personalization, Semantics, Social Web, twitter, User Profiles, Wikipedia

Twitter, due to its massive growth as a social networking platform, has been in focus for the analysis of its user-generated content for personalization and recommendation tasks. A common challenge across these tasks is identifying user interests from tweets. Semantic enrichment of Twitter posts to determine user interests has been an active area of research in the recent past. These approaches typically use available public knowledge-bases (such as Wikipedia) to spot entities and create entity-based user profiles. However, exploitation of such knowledge-bases to create richer user profiles has yet to be explored. In this work, we leverage hierarchical relationships present in knowledge-bases to infer user interests expressed as a Hierarchical Interest Graph. We argue that the hierarchical semantics of concepts can enhance existing systems to personalize or recommend items based on a varied level of conceptual abstractness. We demonstrate the effectiveness of our approach through a user study which shows an average of approximately eight of the top ten weighted hierarchical interests in the graph being relevant to a user’s interests.