IDEAS home Printed from https://ideas.repec.org/a/bla/jamist/v63y2012i12p2521-2535.html
   My bibliography  Save this article

Sentiment analysis of twitter audiences: Measuring the positive or negative influence of popular twitterers

Author

Listed:
  • Younggue Bae
  • Hongchul Lee

Abstract

Twitter is a popular microblogging service that is used to read and write millions of short messages on any topic within a 140‐character limit. Popular or influential users tweet their status and are retweeted, mentioned, or replied to by their audience. Sentiment analysis of the tweets by popular users and their audience reveals whether the audience is favorable to popular users. We analyzed over 3,000,000 tweets mentioning or replying to the 13 most influential users to determine audience sentiment. Twitter messages reflect the landscape of sentiment toward its most popular users. We used the sentiment analysis technique as a valid popularity indicator or measure. First, we distinguished between the positive and negative audiences of popular users. Second, we found that the sentiments expressed in the tweets by popular users influenced the sentiment of their audience. Third, from the above two findings we developed a positive‐negative measure for this influence. Finally, using a Granger causality analysis, we found that the time‐series‐based positive‐negative sentiment change of the audience was related to the real‐world sentiment landscape of popular users. We believe that the positive‐negative influence measure between popular users and their audience provides new insights into the influence of a user and is related to the real world.

Suggested Citation

  • Younggue Bae & Hongchul Lee, 2012. "Sentiment analysis of twitter audiences: Measuring the positive or negative influence of popular twitterers," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2521-2535, December.
    • Handle: RePEc:bla:jamist:v:63:y:2012:i:12:p:2521-2535
    DOI: 10.1002/asi.22768
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asi.22768
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asi.22768?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Martin Quinn & Theodore Lynn & Stephen Jollands & Binesh Nair, 2016. "Domestic Water Charges in Ireland - Issues and Challenges Conveyed through Social Media," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3577-3591, August.
    2. Wei-Lun Chang, 2019. "The Impact of Emotion: A Blended Model to Estimate Influence on Social Media," Information Systems Frontiers, Springer, vol. 21(5), pages 1137-1151, October.
    3. Rowe, Francisco & Mahony, Michael & Graells-Garrido, Eduardo & Rango, Marzia & Sievers, Niklas, 2021. "Using Twitter to Track Immigration Sentiment During Early Stages of the COVID-19 Pandemic," SocArXiv pc3za, Center for Open Science.
    4. Topaloglu, Omer & Dass, Mayukh & Kumar, Piyush, 2017. "Does who we are affect what we say and when? Investigating the impact of activity and connectivity on microbloggers' response to new products," Journal of Business Research, Elsevier, vol. 77(C), pages 23-29.
    5. Joaquin Sanchez & Carmen Abril & Michael Haenlein, 2020. "Competitive spillover elasticities of electronic word of mouth: an application to the soft drink industry," Journal of the Academy of Marketing Science, Springer, vol. 48(2), pages 270-287, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jamist:v:63:y:2012:i:12:p:2521-2535. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.