Social-spam profile detection based on content classification and user behavior

Title: Social-spam profile detection based on content classification and user behavior
Authors: Vuong, T.-H.
Tran, V.-H.
Nguyen, M.-D., (...)
Pham, T.-H.
Tran, M.-V.
Keywords: social networks;spam accounts detection
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Scopus
Abstract: Web-based social system enables new community-based opportunities for participants to engage, share and interact. The rapid growth of Facebook has triggered a dramatic increase in spam volume and sophistication. Spammers post their status or comment in Page to send spam content to their friends or other users in the network. In this paper, we consider the problem of detecting spam accounts on Facebook based on comment content and user social behavior. We will propose a hybrid approach using Maximum Entropy (Maxent) model for classifying user comments as either spam or non-spam. We carefully conducted an empirical evaluation for our model on a large collection of comments in Vietnamese Facebook Pages and achieved promising results with an average accuracy of more than 90%.
Description: Proceedings - 2016 8th International Conference on Knowledge and Systems Engineering, KSE 2016 28 November 2016, Article number 7758064, Pages 264-267
URI: http://ieeexplore.ieee.org/document/7758064/
http://repository.vnu.edu.vn/handle/VNU_123/33983
ISBN: 978-146738929-7
Appears in Collections:Bài báo của ĐHQGHN trong Scopus

Nhận xét

Bài đăng phổ biến từ blog này

Đánh giá tiềm năng giảm phát thải và đề xuất giải pháp tiết kiệm năng lượng trong hoạt động khai thác thủy sản trên địa bàn các xã ven biển huyện Triệu Phong, tỉnh Quảng Trị: Luận văn ThS. Biến đổi khí hậu

Resveratrol primes the effects of physical activity in old mice

PERIDOT FROM THE CENTRAL HIGHLANDS OF VIETNAM: PROPERTIES, ORIGIN, AND FORMATION