Title
Unlocking Social Media And User Generated Content As A Data Source For Knowledge Management
Abstract
The pervasiveness of social media and user-generated content has triggered an exponential increase in global data. However, due to collection and extraction challenges, data in embedded comments, reviews and testimonials are largely inaccessible to a knowledge management system. This article describes a KM framework for the end-to-end knowledge management and value extraction from such content. This framework embodies solutions to unlock the potential of UGC as a rich, real-time data source. Three contributions are described in this article. First, a method for automatically navigating webpages to expose UGC for collection is presented. This is evaluated using browser emulation integrated with automated collection. Second, a method for collecting data without any a priori knowledge of the sites is introduced. Finally, a new testbed is developed to reflect the current state of internet sites and shared publicly to encourage future research. The discussion benchmarks the new algorithm alongside existing techniques, providing evidence of the increased amount of UGC data extracted.
Year
DOI
Venue
2020
10.4018/IJKM.2020010105
INTERNATIONAL JOURNAL OF KNOWLEDGE MANAGEMENT
Keywords
Field
DocType
Content Discovery, Data Acquisition, Data Manipulation, Knowledge Management, Social Mining, User-Generated Content, Web Data Extraction
User-generated content,Data source,Social media,Computer science,Knowledge management
Journal
Volume
Issue
ISSN
16
1
1548-0666
Citations 
PageRank 
References 
1
0.34
0
Authors
5
Name
Order
Citations
PageRank
James Meneghello110.34
Nik Thompson2205.87
Kevin Lee334027.53
Kok Wai Wong472577.68
Bilal Abu-Salih5255.53