Investigating the deceptive information in twitter spam

Chen, Chao, Wen, Sheng, Zhang, Jun, Xiang, Yang, Oliver, Jonathan, Alelaiwi, Abdulhameed, and Hassan, Mohammad Mehedi (2017) Investigating the deceptive information in twitter spam. Future Generation Computer Systems, 72. pp. 319-326.

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Abstract

Online Social Networks (OSNs) such as Facebook and Twitter have become popular communication and information sharing tools for hundreds of millions of individuals in recent years. OSNs not only make people’s life more connected, but also attract the interest of spammers. Twitter spam generally contains deceptive information, such as “free voucher” and “weight loss advertisement” to attract the interest of victims. A comprehensive analysis on the deceptive information will be of great benefit to the detection of Twitter spam. This paper presents a study of deceptive information in Twitter spam. The analysis is based on a collection of over 550 million tweets with around 6% spam. We find that various deceptive content of spam performs differently in luring victims to malicious sites. We also find the regional response rate to various Twitter spam outbreaks varies greatly. These two factors can contribute to improve the performance of spam detection techniques.

Item ID: 64422
Item Type: Article (Research - C1)
ISSN: 1872-7115
Keywords: online social network, big data, Twitter spam analysis
Copyright Information: © 2016 Elsevier B.V. All rights reserved.
Funders: Australian Research Council (ARC), Deanship of Scientific Research at King Saud University (KSU)
Projects and Grants: ARC Project DP150103732, ARC Project DP140103649, ARC Project LP140100816, KSU project no. RGP-318
Date Deposited: 22 Sep 2020 21:06
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0803 Computer Software > 080303 Computer System Security @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890299 Computer Software and Services not elsewhere classified @ 100%
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