Semantic hashtag relation classification using co-occurrence word information

Sungwon Seo, Jong-Kook Kim, Lynn Choi

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

3 Citations (Scopus)

Abstract

Social Networking Service users express their thoughts and feelings using hashtags. Hashtags can be related to other hashtags and these hashtags and images are used together in a post that the user wrote. Understanding the meaning of a hashtag is one of the ways to learn latent semantic expressions of words. Existing methods for learning semantic analysis use large corpus. This research focuses on the classification of semantic words using a user's hashtag data and co-occurrence hashtag information.

Original languageEnglish
Title of host publicationICUFN 2017 - 9th International Conference on Ubiquitous and Future Networks
PublisherIEEE Computer Society
Pages860-862
Number of pages3
ISBN (Electronic)9781509047499
DOIs
Publication statusPublished - 2017 Jul 26
Event9th International Conference on Ubiquitous and Future Networks, ICUFN 2017 - Milan, Italy
Duration: 2017 Jul 42017 Jul 7

Other

Other9th International Conference on Ubiquitous and Future Networks, ICUFN 2017
CountryItaly
CityMilan
Period17/7/417/7/7

Keywords

  • Hashtag
  • Information Retrieval
  • Natural Language Processing
  • Social Networking Service

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture

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  • Cite this

    Seo, S., Kim, J-K., & Choi, L. (2017). Semantic hashtag relation classification using co-occurrence word information. In ICUFN 2017 - 9th International Conference on Ubiquitous and Future Networks (pp. 860-862). [7993922] IEEE Computer Society. https://doi.org/10.1109/ICUFN.2017.7993922