Title
"Twitterspamdetector" A Spam Detection Framework For Twitter
Abstract
Twitter is the most popular microblogging platform which lets users post status messages called tweets. This popularity and the advanced API provided by Twitter to read and write Twitter data programmatically attracts the attention of spammers as well as legitimate users. Since Twitter has some unique characteristics, the traditional spam detecting methods cannot be directly used to detect spam on Twitter. Therefore, a spam detection framework which is specially designed for Twitter namely TwitterSpamDetector is proposed in this paper. TwitterSpamDetector uses Twitter-specific features to detect spam on Twitter. 77,033 tweets which are posted by 50,490 users collected using the API provided by Twitter. Naive Bayes is used to train TwitterSpamDetector using the selected features of Twitter which clearly classify the spammers from legitimate users. According to the evaluation result, TwitterSpamDetector's accuracy and sensitivity are calculated as 0.943 and 0.913, respectively.
Year
DOI
Venue
2019
10.4018/IJKSS.2019070101
INTERNATIONAL JOURNAL OF KNOWLEDGE AND SYSTEMS SCIENCE
Keywords
Field
DocType
Microblogs, Social Network Security, Spam Detection, Twitter
World Wide Web,Computer science,Knowledge management
Journal
Volume
Issue
ISSN
10
3
1947-8208
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Abdullah Talha Kabakus100.68
Resul Kara2103.17