A case study on mining social media data

Chan, H. K. and Lacka, E. and Yee, R. W. Y. and Lim, M. K. (2014) A case study on mining social media data. In: IEEM 2014, 2014-12-09 - 2014-12-12, Sunway Resort Hotel & Spa. (https://doi.org/10.1109/IEEM.2014.7058707)

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Abstract

In recent years, usage of social media websites have been soaring. This trend not only limits to personal but corporate web-sites. The latter platforms contain an enormous amount of data posted by customers or users. Without a surprise, the data in corporate social media web-sites are normally link to the products or services provided by the companies. Therefore, the data can be utilized for the sake of companies’ benefits. For example, operations management research and practice with the objective to make decisions on product and process design. Nevertheless, little has been done in this area. In this connection, this paper presents a case study to showcase how social media data can be exploited. A structured approach is proposed which involves the analysis of social media comments and a statistical cluster analysis to identify the inter-relationships among important factors.

ORCID iDs

Chan, H. K., Lacka, E. ORCID logoORCID: https://orcid.org/0000-0003-4911-2030, Yee, R. W. Y. and Lim, M. K.;
  • Item type:Conference or Workshop Item(Paper)
    ID code:51031
    Dates:
    Date
    Event
    December 2014
    Published
    1 August 2014
    Accepted
    Notes:© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Social Sciences > Commerce > Marketing. Distribution of products
    Department:Strathclyde Business School > Marketing
    Depositing user: Pure Administrator
    Date deposited:12 Jan 2015 19:52
    Last modified:11 Nov 2024 16:43
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/51031
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