Identifying Online Opinion Leaders Using K-means Clustering

被引：0

作者：

Hudli, Shrihari A. ^{[1
]}

Hudli, Aditi A. ^{[1
]}

Hudli, Anand V. ^{[2
]}

机构：

[1] MS Ramaiah Inst Technol, Dept Comp Sci, Bangalore, Karnataka, India

[2] ObjectOrb Technol, Bangalore, Karnataka, India

来源：

2012 12TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA) | 2012年

关键词：

online opinion leaders; online discussion forum; data mining; clustering; supervised machine learning;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Online opinion leaders play an important role in the dissemination of information in discussion forums. They are a high-priority target group for viral marketing campaigns. On an average, an opinion leader will tell about his or her experience with a product or company to 14 other people. It is important to identify such opinion leaders from data derived from online activity of users. We present an approach to identification of opinion leaders using the K-means clustering algorithm. This approach does not require knowledge of the user's opinions or membership in other forums.

引用

页码：416 / 419

页数：4

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