NDLI: Who are the spoilers in social media marketing? Incremental learning of latent semantics for social spam detection

Content Provider	Springer Nature Link
Author	Song, Long Lau, Raymond Yiu Keung Kwok, Ron Chi Wai Mirkovski, Kristijan Dou, Wenyu
Copyright Year	2016
Abstract	With the rise of social web, there has also been a great concern about the quality of user-generated content on social media sites (SMSs). Deceptive comments harm users’ trust in online social media and cause financial loss to firms. Previous studies use various features and classification algorithms to detect and filter social spam on several social media platforms. However, to the best of our knowledge, previous studies have not exploited both probabilistic topic modeling and incremental learning to detect social spam on SMSs. Thus, the main contribution of this paper is design of a novel detection methodology that combines topic- and user-based features to improve the effectiveness of social spam detection. The proposed methodology exploits a probabilistic generative model, namely the labeled latent Dirichlet allocation (L-LDA), for mining the latent semantics from user-generated comments, and an incremental learning approach for tackling the changing feature space. An experiment based on a large dataset extracted from YouTube demonstrates the effectiveness of our proposed methodology, which achieves an average accuracy of 91.17 % in social spam detection. Our statistical analysis reveals that topic-based features significantly improve social spam detection, which has significant implications for business practice.
Starting Page	51
Ending Page	81
Page Count	31
File Format	PDF
ISSN	13895753
Journal	Electronic Commerce Research
Volume Number	17
Issue Number	1
e-ISSN	15729362
Language	English
Publisher	Springer US
Publisher Date	2016-10-08
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Social spam Spam detection Topic modeling Incremental learning Machine learning Big data IT in Business Data Structures, Cryptology and Information Theory Operation Research/Decision Theory Computer Communication Networks Business and Management e-Commerce/e-business
Content Type	Text
Resource Type	Article
Subject	Economics, Econometrics and Finance Human-Computer Interaction

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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