Paper Info
Title
News credibility scroing - suggestion of research methodology to determine the reliability of news distributed in SNS.
Abstract
We provide a more optimized model for calculating credibility score of information in SNS. We premeditated two heuristics which using characteristics of the credibility score for each document: (1) Expertise and (2) unbiasedness. Also, we divide the users in SNS into three types: (1) Creator (2) Distributor, and (3) Follower. Our model is designed to calculate Expertise and Un-biasedness for three types of SNS users (Creator, Distributor, and Follower) by using logistic regression model. Our model not only reveals whether the information is 'accurate and unbiased', but also investigates the 'source, distribution channel, and audience' of the information. We expect our credibility scoring will give answers to the 'qualitative problem' our online world is currently facing.
Year
DOI
Venue
2019
10.1145/3341161.3343683
ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining Vancouver British Columbia Canada August, 2019
Keywords
Field
DocType
Credibility, Scoring, Reliability, Fake News
Data science,Credibility,Computer science,Artificial intelligence,Research methodology,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4503-6868-1
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Ki-Young Shin100.34
Woosang Song2201.75
Jinhee Kim3214.68
Jong-Hyeok Lee474097.88