IDEAS home Printed from https://ideas.repec.org/a/igg/jebr00/v15y2019i3p1-15.html
   My bibliography  Save this article

Initial Exploration on an Effective Social Media Analytics Method and Algorithm for Instagram Hashtags

Author

Listed:
  • Nurul Atikah Ahmad Rosli

    (Universiti Sains Malaysia, Penang, Malaysia)

  • Mohd Heikal Husin

    (Universiti Sains Malaysia, Penang, Malaysia)

Abstract

Over the years, social media has brought many benefits to different fields, especially in the business sector. Most of the existing organizations have taken these benefits to actively engage with the public to increase their online business value. The use of hashtags on numerous social media platforms especially on Instagram is one of the highly used benefits. By tagging specific postings, business organizations are able to promote and communicate with their customers directly in a more interactive manner. In this article, the authors are exploring the following: (1) to determine the effectiveness of the existing analytics method (text identification and trend analysis) for analyzing Instagram hashtag data and; (2) to determine the effectiveness of existing analytic techniques such as Naïve Bayes and Support Vector Machines (SVM) suited for the selected analytics method. As a result, the authors have identified that the combination of Trend Analysis method and SVM are an effective social media analytics approach for analyzing Instagram hashtag data.

Suggested Citation

  • Nurul Atikah Ahmad Rosli & Mohd Heikal Husin, 2019. "Initial Exploration on an Effective Social Media Analytics Method and Algorithm for Instagram Hashtags," International Journal of E-Business Research (IJEBR), IGI Global, vol. 15(3), pages 1-15, July.
    • Handle: RePEc:igg:jebr00:v:15:y:2019:i:3:p:1-15
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJEBR.2019070101
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Josué Gutiérrez-Barroso & Alberto Javier Báez-García & Francisco Flores-Muñoz & Diego Valentinetti, 2021. "Instagram: Balancing Information Asymmetry of the Tourism Industry," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 68(4), pages 445-457, November.

    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:igg:jebr00:v:15:y:2019:i:3:p:1-15. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.