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Leveraging Careful Microblog Users for Spammer Detection

Hao Fu, Xing Xie, Yong Rui
2015 Proceedings of the 24th International Conference on World Wide Web - WWW '15 Companion  
Microblogging websites, e.g. Twitter and Sina Weibo, have become a popular platform for socializing and sharing information in recent years.  ...  Spammers have also discovered this new opportunity to unfairly overpower normal users with unsolicited content, namely social spams.  ...  We take it as a baseline to compare with. • TrustRank [10] was proposed to detect web spams, and we adapt it for spammer detection in a microblogging site.  ... 
doi:10.1145/2740908.2745400 dblp:conf/www/FuXR15 fatcat:ex2u2cszojf7xkvu7ub5jbovmu

Suspicious Behavior Detection: Current Trends and Future Directions

Meng Jiang, Peng Cui, Christos Faloutsos
2016 IEEE Intelligent Systems  
Detection methods often look for the most suspicious parts of the data by optimizing scores, but quantifying the suspiciousness of a behavioral pattern is still an open issue.  ...  The proposed Social Spammer Detection in Microblogging (SSDM) approach is a matrix factorization-based model that integrates both social network information and content information for social spammer detection  ...  (spam versus regular message), and shows promising accuracy in combating email spams. 1 People don't want legitimate email blocked, so to take false-positive rates (FPRs) into consideration, AFSD gives  ... 
doi:10.1109/mis.2016.5 fatcat:afco6xovnbhbdggw7jmyo22uge

Spam, a Digital Pollution and Ways to Eradicate It

2019 International Journal of Engineering and Advanced Technology  
This survey is thus mainly used to discuss and analyze the recent research that had been put forth regarding the spam detection in social media sites such as Twitter.  ...  Due to the growing popularity of the microblogging and networking sites like twitter, Gmail, Facebook etc., there has been an increase in the number of spammers.  ...  Spammers are using different features for their spam messages and are evolving over time. Spamming is usually done with similar content and in large quantities.  ... 
doi:10.35940/ijeat.b4107.129219 fatcat:uze7gfg3wrgjdmetvpuhzhl7p4

Detecting malicious tweets in trending topics using a statistical analysis of language

Juan Martinez-Romo, Lourdes Araujo
2013 Expert systems with applications  
In addition, we have developed a machine learning system with some orthogonal features that can be combined with other sets of features with the aim of analyzing emergent characteristics of spam in social  ...  This growing microblogging phenomenon therefore allows spammers to disseminate malicious tweets quickly and massively.  ...  Acknowledgments This work has been partially supported by the Spanish Ministry of Science and Innovation within the project Holopedia (TIN2010-21128-C02-01) and the Regional Government of Madrid under  ... 
doi:10.1016/j.eswa.2012.12.015 fatcat:es6fmurrvjau5nyk7twgplesjm

CATS: Characterizing automation of Twitter spammers

Amit A. Amleshwaram, Narasimha Reddy, Sandeep Yadav, Guofei Gu, Chao Yang
2013 2013 Fifth International Conference on Communication Systems and Networks (COMSNETS)  
Spammers use myriad of techniques to evade security mechanisms and post spam messages, which are either unwelcome advertisements for the victim or lure victims in to clicking malicious URLs embedded in  ...  Our analysis reveals detection of more than 90% of spammers with less than five tweets and about half of the spammers detected with only a single tweet.  ...  However, the need to push the same spam message or URL to several users links these spammers and enables our detection methodology.  ... 
doi:10.1109/comsnets.2013.6465541 dblp:conf/comsnets/AmleshwaramRYGY13 fatcat:vu5wyvuuafb33m4m4ozvoqemcu

Integrating web-based intelligence retrieval and decision-making from the twitter trends knowledge base

Marc Cheong, Vincent Lee
2009 Proceeding of the 2nd ACM workshop on Social web search and mining - SWSM '09  
Our methodology differs from the existing literature in the sense that we are doing analysis on Twitter microblog messages as opposed to traditional blog analysis in the literature which deals with the  ...  Another key difference in our methodology is that we apply visualization techniques in conjunction with artificial intelligence-based data mining methods to classify messages dealing with the trend topic  ...  Trended: this detects the presence of the word 'trend' in a message in the context of the user 'piggybacking' on the trending topic but not genuinely discussing the topic in a proper context.  ... 
doi:10.1145/1651437.1651439 dblp:conf/cikm/CheongL09 fatcat:5tjhdcr7njfidap2rwwd6j4ony

Seminar Users in the Arabic Twitter Sphere [article]

Kareem Darwish, Dimitar Alexandrov, Preslav Nakov, Yelena Mejova
2017 arXiv   pre-print
We introduce the notion of "seminar users", who are social media users engaged in propaganda in support of a political entity.  ...  We develop a framework that can identify such users with 84.4% precision and 76.1% recall.  ...  and detection of microblogging spam accounts.  ... 
arXiv:1707.07276v1 fatcat:kj7t6bjfurh43akssglhs735cq

Adversarial Web Search

Carlos Castillo
2010 Foundations and Trends in Information Retrieval  
They observe that, while in the case of e-mail spam each message should be analyzed independently in principle, in the case of comments there is a context which is the page and site where the comment is  ...  Additionally, in social media sites users can, and usually do, help with policing bad behavior by reporting abuse and spam.  ... 
doi:10.1561/1500000021 fatcat:toxnvajrmbdppf5hytdbnykuiq

What do people study when they study Twitter? Classifying Twitter related academic papers

Shirley A. Williams, Melissa M. Terras, Claire Warwick
2013 Journal of Documentation  
Structured Abstract Purpose Since its introduction in 2006, messages posted to the microblogging system Twitter have provided a rich dataset for researchers, leading to the publication of over a thousand  ...  Findings The majority of published work relating to Twitter concentrates on aspects of the messages sent and details of the users.  ...  --Enhancing spammer detection on the twitter microblogging platform using friends and followers 2010 Communications in Computer and Mowbray M.  ... 
doi:10.1108/jd-03-2012-0027 fatcat:3rfuptki5bgxvfxumtf6ea6vxi

User-Generated Content (UGC) Credibility on Social Media Using Sentiment Classification

Esraa Afify, Ahmed Sharaf Eldin, Ayman E. Khedr, Fahad Kamal Alsheref
2019 النشرة المعلوماتیة فی الحاسبات والمعلومات  
Because online users face difficulty in finding which piece of information is credible or not, the researchers found that assessing User-Generated Content (UGC) of social media is very important in resolving  ...  They usually rely on this information without any verification and this prevents them from making accurate decisions concerning their social lives, politics, or business events.  ...  As in the case of opinion spam detection, recent approaches are focusing on the identification of spammers as well as fake news detection.  ... 
doi:10.21608/fcihib.2019.107506 fatcat:w4vazjtyl5h6zdz2kol2vn5hsy

Twitter Bot Detection Using Bidirectional Long Short-term Memory Neural Networks and Word Embeddings [article]

Feng Wei, Uyen Trang Nguyen
2020 arXiv   pre-print
Twitter is a web application playing dual roles of online social networking and micro-blogging.  ...  ., tweets delivering news and updating feeds, while malicious bots spread spam or malicious contents.  ...  In addition, when a spam account is detected, Twitter suspends it or even blocks his IP address temporally, so spammers only need to create a different account to continue sending spam messages or wait  ... 
arXiv:2002.01336v1 fatcat:fmqknywbrvgc7j5obqnv3cldeq

Online Social Deception and Its Countermeasures for Trustworthy Cyberspace: A Survey [article]

Zhen Guo, Jin-Hee Cho, Ing-Ray Chen, Srijan Sengupta, Michin Hong, Tanushree Mitra
2020 arXiv   pre-print
attacks and cybercrimes; (iii) comprehensive defense mechanisms embracing prevention, detection, and response (or mitigation) against OSD attacks along with their pros and cons; (iv) datasets/metrics  ...  We conclude this survey paper with an in-depth discussions on the limitations of the state-of-the-art and recommend future research directions in this area.  ...  Crowdturfing activities in social media exploit social networking platforms (e.g., instant message groups, microblogs, blogs, and online forums) as the main information channel of the campaign [162] .  ... 
arXiv:2004.07678v1 fatcat:k4a6siywefb6lhkmyn67lmoqwe

Social Media Identity Deception Detection: A Survey [article]

Ahmed Alharbi, Hai Dong, Xun Yi, Zahir Tari, Ibrahim Khalil
2021 arXiv   pre-print
This survey provides a detailed review of social media identity deception detection techniques. It also identifies primary research challenges and issues in the existing detection techniques.  ...  Many social media identity deception cases have arisen over the past few years. Recent studies have been conducted to prevent and detect identity deception.  ...  [107] proposed a Supervised Matrix Factorization method with Social Regularization (SMFSR) to detect spammers.  ... 
arXiv:2103.04673v1 fatcat:zf6xcn3pafcgfbxmoewc3yhhpi

A Survey of Techniques for Event Detection in Twitter

Farzindar Atefeh, Wael Khreich
2013 Computational intelligence  
Twitter is among the fastest-growing microblogging and online social networking services.  ...  Twitter streams contain large amounts of meaningless messages and polluted content, which negatively affect the detection performance.  ...  that co-trend with the query terms in relevant timespans.  ... 
doi:10.1111/coin.12017 fatcat:wr3wcvxmavbarityeu2szfcuw4

Critical Impact of Social Networks Infodemic on Defeating Coronavirus COVID-19 Pandemic: Twitter-Based Study and Research Directions [article]

Azzam Mourad, Ali Srour, Haidar Harmanani, Cathia Jenainatiy, Mohamad Arafeh
2020 arXiv   pre-print
In this context, several insights and findings have been provided while elaborating computing and non-computing implications and research directions for potential solutions and social networks management  ...  Further data analysis revealed the importance of using social networks in a global pandemic crisis by relying on credible users with variety of occupations, content developers and influencers in specific  ...  Spam and Misleading Posts Detection Detecting spammers on social networks most often relies on analyzing the content of messages [9], [29] , [31] - [33] , [57] .  ... 
arXiv:2005.08820v1 fatcat:vzwmd5mwzjendeaq3vfol6yxw4
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