Beomap: Ad hoc topic maps for enhanced exploration of social media data

Martin Leginus, Cheng Xiang Zhai, Peter Dolog

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Social media is ubiquitous. There is a need for intelligent retrieval interfaces that will enable a better understanding, exploration and browsing of social media data. A novel two dimensional ad hoc topic map is proposed (called Beomap). The main novelty of Beomap is that it allows a user to define an ad hoc semantic dimension with a keyword query when visualizing topics in text data. This not only helps to impose more meaningful spatial dimensions for visualization, but also allows users to steer browsing and exploration of the topic map through ad hoc defined queries. We developed a system to implement Beomap for exploring Twitter data, and evaluated the proposed Beomap in two ways, including an offline simulation and a user study. Results of both evaluation strategies show that the new Beomap interface is better than a standard interactive interface.

Original languageEnglish (US)
Title of host publicationEngineering the Web in the Big Data Era - 15th International Conference, ICWE 2015, Proceedings
EditorsFlavius Frasincar, Geert-Jan Houben, Philipp Cimiano, Daniel Schwabe
PublisherSpringer-Verlag Berlin Heidelberg
Pages200-218
Number of pages19
ISBN (Electronic)9783319198897
DOIs
StatePublished - Jan 1 2015
Event15th International Conference on Web Engineering, ICWE 2015 - Rotterdam, Netherlands
Duration: Jun 23 2015Jun 26 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9114
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Web Engineering, ICWE 2015
CountryNetherlands
CityRotterdam
Period6/23/156/26/15

Keywords

  • Adaptive browsing
  • Adaptive visualization
  • Social media
  • Topic map

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Leginus, M., Zhai, C. X., & Dolog, P. (2015). Beomap: Ad hoc topic maps for enhanced exploration of social media data. In F. Frasincar, G-J. Houben, P. Cimiano, & D. Schwabe (Eds.), Engineering the Web in the Big Data Era - 15th International Conference, ICWE 2015, Proceedings (pp. 200-218). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9114). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-319-19890-3_14