@inproceedings{2cf9f5e0b3334127983d3c84c2c53f6a,
title = "A case study on mining social media data",
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.",
keywords = "Social Media, cluster analysis, content analysis, text mining",
author = "Chan, {H. K.} and E. Lacka and Yee, {R. W.Y.} and Lim, {M. K.}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2014 ; Conference date: 09-12-2014 Through 12-12-2014",
year = "2014",
doi = "10.1109/IEEM.2014.7058707",
language = "English",
series = "IEEE International Conference on Industrial Engineering and Engineering Management",
publisher = "IEEE Computer Society",
pages = "593--596",
booktitle = "IEEM 2014 - 2014 IEEE International Conference on Industrial Engineering and Engineering Management",
address = "United States",
}