Web Spam Detection
Web Spam Detection is a computational method in the field of Web Mining and Web Search that identifies deceptive or manipulative web content designed to exploit search engine algorithms, distinguishing itself from general content classification by focusing specifically on detecting pages created solely for artificially inflating search rankings through irrelevant, duplicated, or hidden information.
608
Publications
37.8K
Citations
1.6K
Authors
542
Institutions
Publications per year
2017–2026
179
Parents
608
Nitin Jindal, Bing Liu · 2008 · 1.5K citations
HT06, tagging paper, taxonomy, Flickr, academic article, to read
Cameron Marlow, Mor Naaman, danah boyd et al. · 2006 · 878 citations
Justin Ma, Lawrence K. Saul, Stefan Savage et al. · 2009 · 780 citations
Detecting product review spammers using rating behaviors
Ee‐Peng Lim, Viet-An Nguyen, Nitin Jindal et al. · 2010 · 726 citations · Full text
Gabriel Magno, Tiago Rodrigues, Virgı́lio Almeida · 2010 · 657 citations
1–5 of 608
1.6K
11
h-index
10
h-index
9
h-index
8
h-index
8
h-index
1–5 of 1.6K
542
Georgia Institute of Technology
Atlanta, United States
14 h-index
39 publications
1.6K citations
Microsoft (United States)
Redmond, United States
12 h-index
33 publications
5.8K citations
Tsinghua University
Beijing, China
11 h-index
57 publications
2.1K citations
University of Illinois Chicago
Chicago, United States
10 h-index
25 publications
10K citations
Stanford University
Stanford, United States
10 h-index
28 publications
3.5K citations
Curtin University
Perth, Australia
9 h-index
22 publications
640 citations
Carnegie Mellon University
Pittsburgh, United States
9 h-index
19 publications
2K citations
University of California San Diego
San Diego, United States
9 h-index
37 publications
8.9K citations
1–8 of 542
14 publications · 643 citations
14
h-index
8 publications · 476 citations
8
h-index
Repository · 7 publications · 407 citations
7
h-index
TWEB · 7 publications · 430 citations
7
h-index
7 publications · 975 citations
7
h-index
1–5