Topic Derivation in Weibo Through Both Interactions and Content

Zihan Wang, Bing Li

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)

Abstract

Social media represented by Weibo has become one of the most important platforms, covering all kinds of topics for information dissemination and day-to-day communications. As a result, topic derivation in Weibo can support various applications scenarios, including sentiment analysis, opinion controlling, market forecasting, etc. As traditional topic derivation in Weibo is mainly based on the short text of a weibo post, these methods usually encounter the data sparsity problem. To solve this problem, we find that both content and interactions can help improve the quality of topic derivation in Weibo. Thus, this paper proposed a method that additionally takes three typical interactions into features: mentioning, forwarding and the topic tags. The proposed method clusters the weibo posts and identifies the representative terms for each topic by matrix factorization technique. Our experimental results show that the proposed method performs better than advanced baseline methods in both topic clustering accuracy and keywords extraction.

Original languageEnglish
Title of host publication2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS 2018)
Subtitle of host publicationProceedings of a meeting held 23-25 November 2018, Beijing, China.
EditorsM. Surendra Prasad Babu, Li Wenzheng
PublisherIEEE Computer Society
Pages932-935
Number of pages4
Volume2018-November
ISBN (Electronic)9781538665640
ISBN (Print)9781538665664
DOIs
Publication statusPublished - 8 Mar 2019
Event9th IEEE International Conference on Software Engineering and Service Science, ICSESS 2018 - Beijing, China
Duration: 23 Nov 201825 Nov 2018

Conference

Conference9th IEEE International Conference on Software Engineering and Service Science, ICSESS 2018
CountryChina
CityBeijing
Period23/11/1825/11/18

Keywords

  • Interactions of Weibo posts
  • NMF
  • topic derivation
  • weibo

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