Detecting spamming activities in twitter based on deep-learning technique-Reference-Cited by-同舟云学术

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Detecting spamming activities in twitter based on deep-learning technique

Published:2017-06-20 Issue:19 Volume:29 Page:e4209
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat: Pract Exper

Author:

Wu Tingmin¹^ORCID,Wen Sheng¹,Liu Shigang¹^ORCID,Zhang Jun¹,Xiang Yang¹^ORCID,Alrubaian Majed²,Hassan Mohammad Mehedi²^ORCID

Affiliation:

1. School of Information Technology; Deakin University; Victoria 3125 Australia

2. College of Computer and Information Sciences King Saud University; Riyadh 11543 Saudi Arabia

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference30 articles.

1. Java A Song X Finin T Tseng B Why we twitter: Understanding microblogging usage and communities San Jose, CA, US 2007

2. Benevenuto F Magno G Rodrigues T Almeida V Detecting spammers on twitter Redmond, Washington, USA 2010

3. Grier C Thomas K Paxson V Zhang M @ spam: The underground on 140 characters or less Chicago, IL 2010

4. Stringhini G Kruegel C Vigna G Detecting spammers on social networks Austin, Texas, USA 2010

5. Wang AH Don't follow me: Spam detection in twitter Athens, Greece 2010

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