Believe It or Not! Identifying Bizarre News in Online News Media

被引：2
|
作者：
Indurthi, Vijayasaradhi [1 ]
Oota, Subba Reddy [1 ]
Gupta, Manish [1 ]
Varma, Vasudeva [1 ]
机构：
[1] Int Inst Informat Technol, Hyderabad, India
来源：
PROCEEDINGS OF THE ACM INDIA JOINT INTERNATIONAL CONFERENCE ON DATA SCIENCE AND MANAGEMENT OF DATA (CODS-COMAD'18) | 2018年
关键词：
D O I：
10.1145/3152494.3152524
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Bizarre news items are those news items so strange and unusual that readers might question the claims presented in the news. This paper presents the first machine learning approach to bizarre news detection in online news media. We contribute by compiling the first bizarre news corpus of 23754 bizarre news headlines, and by developing a bizarre news detection model based on various syntactic and semantic features. We experiment with various machine learning techniques including deep learning methods, and find that a logistic regression classifier achieves an F1 score of 0.92 for the task.
引用
收藏
页码：257 / 264
页数：8
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