IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Special Section on Data Engineering and Information Management
Analyzing Information Flow and Context for Facebook Fan Pages
Kwanho KIMJosué OBREGONJae-Yoon JUNG
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JOURNAL FREE ACCESS

2014 Volume E97.D Issue 4 Pages 811-814

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Abstract

As the recent growth of online social network services such as Facebook and Twitter, people are able to easily share information with each other by writing posts or commenting for another's posts. In this paper, we firstly suggest a method of discovering information flows of posts on Facebook and their underlying contexts by incorporating process mining and text mining techniques. Based on comments collected from Facebook, the experiment results illustrate how the proposed method can be applied to analyze information flows and contexts of posts on social network services.

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© 2014 The Institute of Electronics, Information and Communication Engineers
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