A cross-cultural analysis of celebrity practice in microblogging

  • Min Zhang
  • , Doreen D. Wu

    Research output: Journal article publicationJournal articleAcademic researchpeer-review

    16 Citations (Scopus)

    Abstract

    This study attempts to explore how celebrities manage rapport with followers through an array of speech acts in microblogging - the essential building blocks of virtual identity on social media. Six months of postings of eight of the most-followed Twitter and Weibo celebrities from USA and China were retrieved and analysed. A taxonomy of nine speech acts for rapport management was identified to give a categorised descriptive snapshot of celebrities' microblogging discourse. The results revealed that the celebrities from both countries employ self-disclosing speech acts extensively to report events, anecdotes, or initiate small talk with fans for solidarity building. In addition, the attention fostered by the personalised, affective, and eye-catching self-disclosure posts is frequently directed to the posts promoting their professional activities or products to commercialise the solidarity as much needed for maintaining a strong fan base. In general, the celebrity practices in USA and China display a converging trend as the prevalent speech acts are largely overlapping across cultures, while culture-specific microblogging behaviours were also identified from the less frequently performed speech acts.

    Original languageEnglish
    Pages (from-to)179-200
    Number of pages22
    JournalEast Asian Pragmatics
    Volume3
    Issue number2
    DOIs
    Publication statusPublished - 31 Aug 2018

    Keywords

    • Celebrity discourse
    • Rapport management
    • Speech act
    • Twitter
    • Weibo

    ASJC Scopus subject areas

    • Cultural Studies
    • Language and Linguistics
    • Communication
    • Linguistics and Language

    Fingerprint

    Dive into the research topics of 'A cross-cultural analysis of celebrity practice in microblogging'. Together they form a unique fingerprint.

    Cite this