Paper Info
Title
How does Truth Evolve into Fake News? An Empirical Study of Fake News Evolution
Abstract
ABSTRACT Automatically identifying fake news from the Internet is a challenging problem in deception detection tasks. Online news is modified constantly during its propagation, e.g., malicious users distort the original truth and make up fake news. However, the continuous evolution process would generate unprecedented fake news and cheat the original model. We present the Fake News Evolution (FNE) dataset: a new dataset tracking the fake news evolution process. Our dataset is composed of 950 paired data, each of which consists of articles representing the three significant phases of the evolution process, which are the truth, the fake news, and the evolved fake news. We observe the features during the evolution and they are the disinformation techniques, text similarity, top 10 keywords, classification accuracy, parts of speech, and sentiment properties.
Year
DOI
Venue
2021
10.1145/3442442.3452328
International World Wide Web Conference
Keywords
DocType
ISSN
datasets, fake news evolution, fake news
Conference
The Web Conference 2021, Workshop on News Recommendation and Intelligence
Citations 
PageRank 
References 
0
0.34
10
Authors
5
Name
Order
Citations
PageRank
Lianhai Miao151.45
Xiuying Chen2196.28
Juntao Li396.62
Dongyan Zhao499896.35
Rui Yan596176.69