Analyzing Influence of Emotional Tweets on User Relationships by Naive Bayes Classification and Statistical Tests

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

    2 Citations (Scopus)

    Abstract

    As an SNS, Twitter is popular because users can post their emotions as a short message easily. Emotional tweets may influence user relationships. In our previous study, we found that positive users construct mutual relationships in Twitter. Keyword matching with emotional word dictionaries was used to detect positive users. The problem of keyword matching is the limitation of word number. To solve this problem, we use machine learning, specifically Naive Bayes Classification, to classify emotions of tweets. We analyze whether there is a difference in user relationships between the positive and negative groups by the Brunner-Munzel test. The result shows that the relationships of positive users increase more than that of negative users in the followee fluctuation, follower fluctuation and mutual follow fluctuation, which means that a positive user is more active to construct user relationships than a negative user.

    Original languageEnglish
    Title of host publicationProceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages217-222
    Number of pages6
    Volume2017-January
    ISBN (Electronic)9781538613269
    DOIs
    Publication statusPublished - 2017 Dec 28
    Event10th IEEE International Conference on Service-Oriented Computing and Applications, SOCA 2017 - Kanazawa, Japan
    Duration: 2017 Nov 222017 Nov 25

    Other

    Other10th IEEE International Conference on Service-Oriented Computing and Applications, SOCA 2017
    CountryJapan
    CityKanazawa
    Period17/11/2217/11/25

    Keywords

    • Brunner-Munzel test
    • Naive Bayes Classification
    • Twitter

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Computer Science Applications
    • Hardware and Architecture
    • Information Systems and Management

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  • Cite this

    Tago, K., & Jin, Q. (2017). Analyzing Influence of Emotional Tweets on User Relationships by Naive Bayes Classification and Statistical Tests. In Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017 (Vol. 2017-January, pp. 217-222). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SOCA.2017.37