Abstract
The connectivity and openness of the Internet have cultivated a blistering expansion of online media websites. However, the culture of openness also makes the emerging platforms an effective channel for content pollution, such as fraud, phishing, and other online abuses. To complicate the problem, content polluters actively manipulate the characteristics of the Internet through establishing links with normal users and blending the malicious information with legitimate content. The manipulated links and content, being used as camouflage, make it very intricate to detect content polluters. Recent work has investigated camouflaged fraud in networks. However, due to the lack of availability of label information for camouflaged content, it is challenging to detect content polluters with traditional approaches. In this paper, we make the first attempt on detecting camouflaged content polluters. In order to evaluate the proposed approach, we conduct experiments on real-world data. The results show that our method achieves better results than existing approaches.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 11th International Conference on Web and Social Media, ICWSM 2017 |
| Publisher | AAAI Press |
| Pages | 696-699 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781577357889 |
| State | Published - 2017 |
| Event | 11th International Conference on Web and Social Media, ICWSM 2017 - Montreal, Canada Duration: May 15 2017 → May 18 2017 |
Other
| Other | 11th International Conference on Web and Social Media, ICWSM 2017 |
|---|---|
| Country | Canada |
| City | Montreal |
| Period | 5/15/17 → 5/18/17 |
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ASJC Scopus subject areas
- Computer Networks and Communications
Cite this
Detecting camouflaged content polluters. / Wu, Liang; Hu, Xia; Morstatter, Fred; Liu, Huan.
Proceedings of the 11th International Conference on Web and Social Media, ICWSM 2017. AAAI Press, 2017. p. 696-699.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Detecting camouflaged content polluters
AU - Wu, Liang
AU - Hu, Xia
AU - Morstatter, Fred
AU - Liu, Huan
PY - 2017
Y1 - 2017
N2 - The connectivity and openness of the Internet have cultivated a blistering expansion of online media websites. However, the culture of openness also makes the emerging platforms an effective channel for content pollution, such as fraud, phishing, and other online abuses. To complicate the problem, content polluters actively manipulate the characteristics of the Internet through establishing links with normal users and blending the malicious information with legitimate content. The manipulated links and content, being used as camouflage, make it very intricate to detect content polluters. Recent work has investigated camouflaged fraud in networks. However, due to the lack of availability of label information for camouflaged content, it is challenging to detect content polluters with traditional approaches. In this paper, we make the first attempt on detecting camouflaged content polluters. In order to evaluate the proposed approach, we conduct experiments on real-world data. The results show that our method achieves better results than existing approaches.
AB - The connectivity and openness of the Internet have cultivated a blistering expansion of online media websites. However, the culture of openness also makes the emerging platforms an effective channel for content pollution, such as fraud, phishing, and other online abuses. To complicate the problem, content polluters actively manipulate the characteristics of the Internet through establishing links with normal users and blending the malicious information with legitimate content. The manipulated links and content, being used as camouflage, make it very intricate to detect content polluters. Recent work has investigated camouflaged fraud in networks. However, due to the lack of availability of label information for camouflaged content, it is challenging to detect content polluters with traditional approaches. In this paper, we make the first attempt on detecting camouflaged content polluters. In order to evaluate the proposed approach, we conduct experiments on real-world data. The results show that our method achieves better results than existing approaches.
UR - http://www.scopus.com/inward/record.url?scp=85029459448&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85029459448&partnerID=8YFLogxK
M3 - Conference contribution
SP - 696
EP - 699
BT - Proceedings of the 11th International Conference on Web and Social Media, ICWSM 2017
PB - AAAI Press
ER -