Paper Info
Title
What's buzzing in the blizzard of buzz? Automotive component isolation in social media postings
Abstract
In the blizzard of social media postings, isolating what is important to a corporation is a huge challenge. In the consumer-related manufacturing industry, for instance, manufacturers and distributors are faced with an unrelenting, accumulating snow of millions of discussion forum postings. In this paper, we describe and evaluate text mining tools for categorizing this user-generated content and distilling valuable intelligence frozen in the mound of postings. Using the automotive industry as an example, we implement and tune the parameters of a text-mining model for component diagnostics from social media. Our model can automatically and accurately isolate the vehicle component that is the subject of a user discussion. The procedure described also rapidly identifies the most distinctive terms for each component category, which provides further marketing and competitive intelligence to manufacturers, distributors, service centers, and suppliers.
Year
DOI
Venue
2013
10.1016/j.dss.2012.12.023
Decision Support Systems
Keywords
Field
DocType
discussion forum postings,automotive industry,component diagnostics,competitive intelligence,social media postings,social media,automotive component isolation,text-mining model,consumer-related manufacturing industry,component category,vehicle component,text mining
Competitive intelligence,Corporation,Data mining,Social media analytics,World Wide Web,Manufacturing,Social media,Social network,Computer science,Marketing buzz,Automotive industry
Journal
Volume
Issue
ISSN
55
4
0167-9236
Citations 
PageRank 
References 
34
1.08
61
Authors
5
Name
Order
Citations
PageRank
Alan S. Abrahams123214.41
Jian Jiao21524.66
Weiguo Fan32055133.38
G. Alan Wang427119.89
Zhongju Zhang537421.01