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Identify Online Store Review Spammers via Social Review Graph

Guan Wang, Sihong Xie, Bing Liu, Philip S. Yu
2012 ACM Transactions on Intelligent Systems and Technology  
In the review graph, we have three kinds of nodes, namely, reviewer, review, and store.  ...  Online shopping reviews provide valuable information for customers to compare the quality of products, store services, and many other aspects of future purchases.  ...  INTRODUCTION Online social intelligence is becoming ubiquitous recently.  ... 
doi:10.1145/2337542.2337546 fatcat:bij23lvkijcidevermw3hleakq

A Robust Opinion Spam Detection Method Against Malicious Attackers in Social Media [article]

Amir Jalaly Bidgolya, Zoleikha Rahmaniana
2020 arXiv   pre-print
Online reviews are potent sources for industry owners and buyers, however opportunistic people may try to destruct or promote their desired product by publishing fake comments named spam opinion.  ...  Moreover, a robust graph-based spam detection method is proposed.  ...  Identify online store review spammers via social review graph. ACM Transactions on Intelligent Systems and Technology (TIST), 3(4):61. [24] Wang, Z., Hou, T., Song, D., Li, Z., and Kong, T. (2016).  ... 
arXiv:2008.08650v1 fatcat:thceztcodffilpxkkrmowlyhoa

Review spam detection via temporal pattern discovery

Sihong Xie, Guan Wang, Shuyang Lin, Philip S. Yu
2012 Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '12  
We discover that singleton review is a significant source of spam reviews and largely affects the ratings of online stores.  ...  Online reviews play a crucial role in today's electronic commerce. It is desirable for a customer to read reviews of products or stores before making the decision of what or from where to buy.  ...  Another work considers reviewers' behaviors by introducing a social graph connecting reviewers, their reviews and stores [6] .  ... 
doi:10.1145/2339530.2339662 dblp:conf/kdd/XieWLY12 fatcat:bzskk5y4onhchdyn7ntbdzb2vq

Blackmarket-Driven Collusion on Online Media: A Survey

Hridoy Sankar Dutta, Tanmoy Chakraborty
2021 ACM/IMS Transactions on Data Science  
We refer to such unfair ways of bolstering social reputation in online media as collusion .  ...  Increasing, the reputation of individuals in online media (aka social reputation ) is thus essential these days, particularly for business owners and event managers who are looking to improve their publicity  ...  [141] proposed an end-to-end deep learning model based on Graph Convolution Networks (GCNs) that operates on directed social graphs to detect social spammers.  ... 
doi:10.1145/3517931 fatcat:7fvgujegh5hohdiemsok6kzviq

Fake Reviewer Group Detection in Online Review Systems [article]

Chen Cao, Shihao Li, Shuo Yu, Zhikui Chen
2021 arXiv   pre-print
Online review systems are important components in influencing customers' purchase decisions.  ...  To manipulate a product's reputation, many stores hire large numbers of people to produce fake reviews to mislead customers.  ...  Akoglu, “Collective opinion spam detection: Bridging online store review spammer detection,” in 2011 IEEE 11th international review networks and metadata,” in Proceedings of the 21th ACM  ... 
arXiv:2112.06403v1 fatcat:vf6ku3uezva23fuoi6kohnooay

Blackmarket-driven Collusion on Online Media: A Survey [article]

Hridoy Sankar Dutta, Tanmoy Chakraborty
2020 arXiv   pre-print
We refer to such unfair ways of bolstering social reputation in online media as collusion.  ...  Increasing the reputation of individuals in online media (aka Social growth) is thus essential these days, particularly for business owners and event managers who are looking to improve their publicity  ...  [124] proposed a graph-based framework, called GGSpam to detect review spammer groups. It recursively splits the entire reviewer graph into small groups.  ... 
arXiv:2008.13102v1 fatcat:vi6yiw5u7rbtvezi6fg32vcmwi

Spammer Detection and Fake User Identification on Social Networks

Faiza Masood, Ghana Ammad, Ahmad Almogren, Assad Abbas, Hasan Ali Khattak, Ikram Ud Din, Mohsen Guizani, Mansour Zuair
2019 IEEE Access  
In this paper, we perform a review of techniques used for detecting spammers on Twitter.  ...  Recently, the detection of spammers and identification of fake users on Twitter has become a common area of research in contemporary online social Networks (OSNs).  ...  Twitter is an Online Social Network (OSN) where users can share anything and everything, such as news, opinions, The associate editor coordinating the review of this manuscript and approving it for publication  ... 
doi:10.1109/access.2019.2918196 fatcat:jht2723d4zbwzj6exkc4yyjdke

Combating Friend Spam Using Social Rejections

Qiang Cao, Michael Sirivianos, Xiaowei Yang, Kamesh Munagala
2015 2015 IEEE 35th International Conference on Distributed Computing Systems  
Unwanted friend requests in online social networks, also known as friend spam, have proven to be among the most evasive malicious activities.  ...  We argue that our design, which leverages the aforementioned graph cut, can reliably detect a region that comprises friend spammers.  ...  Since the social graph is held on the workers, the master needs to fetch the social graph structure via network I/O.  ... 
doi:10.1109/icdcs.2015.32 dblp:conf/icdcs/CaoSYM15 fatcat:5j5zlt3fxvflxi2e7k7teoyrjq

Fake Review Detection Using Behavioral and Contextual Features [article]

Jay Kumar
2020 arXiv   pre-print
User reviews reflect significant value of product in the world of e-market. Many firms or product providers hire spammers for misleading new customers by posting spam reviews.  ...  We empirically proved importance of selected feature set for classification model to identify fake reviews. We ranked features in selected feature set where reviewer deviation achieved ninth rank.  ...  Graph mining techniques are used by various researchers to identify the group spammers based on collaboration of spammer activities.  ... 
arXiv:2003.00807v1 fatcat:s7posvlc35f5ffksgeqluk2ury

Deceptive Review Spam Detection via Exploiting Task Relatedness and Unlabeled Data

Zhen Hai, Peilin Zhao, Peng Cheng, Peng Yang, Xiao-Li Li, Guangxia Li
2016 Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing  
We then propose a novel semi-supervised multitask learning method via Laplacian regularized logistic regression (SMTL-LLR) to further improve the review spam detection performance.  ...  To leverage the unlabeled data, we introduce a graph Laplacian regularizer into each base model.  ...  Wang et al. (2012) investigated the relationships among reviewers, reviews, and stores, and developed a social review graph based method to identify online store spammers.  ... 
doi:10.18653/v1/d16-1187 dblp:conf/emnlp/HaiZCYLL16 fatcat:cxhnjz2b6jafhnmxahz7s4o5h4

Harnessing the Power of the General Public for Crowdsourced Business Intelligence: A Survey

Bin Guo, Yan Liu, Yi Ouyang, Vincent W. Zheng, Daqing Zhang, Zhiwen Yu
2019 IEEE Access  
[116] introduce a heterogeneous graph model to discover the reinforcement relations of reviewers' trustiness, reviews' honesty, and stores' reliability, which are used to discover suspicious spammers  ...  It is able to monitor online reviews, blogs, news, forums and social networks, and also can identify community leaders and customers' behaviors.  ... 
doi:10.1109/access.2019.2901027 fatcat:a5vz6vl7urckpdsreplkvjalea

SocialFilter: Introducing social trust to collaborative spam mitigation

Michael Sirivianos, Kyungbaek Kim, Xiaowei Yang
2011 2011 Proceedings IEEE INFOCOM  
We thank the anonymous reviewers for their helpful feedback and suggestions.  ...  These users maintain accounts in online social networks (OSN.)  ...  We also assume that the OSN provider and the Social-Filter repository reliably maintain the social graph, and the spammer reports.  ... 
doi:10.1109/infcom.2011.5935047 dblp:conf/infocom/SirivianosKY11 fatcat:5aukgiz6nrfltja4dmwwgyoojm

Learning to Represent Review with Tensor Decomposition for Spam Detection

Xuepeng Wang, Kang Liu, Shizhu He, Jun Zhao
2016 Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing  
Based on such representations, the classifier could identify the opinion spam more precisely.  ...  We concatenate the review text, the embeddings of the reviewer and the reviewed product as the representation of a review.  ...  Bing Liu for sharing the Yelp review dataset with us, and the anonymous reviewers for their detailed comments and suggestions.  ... 
doi:10.18653/v1/d16-1083 dblp:conf/emnlp/WangLH016 fatcat:ouiu5a3dmzaoro3fpgmnqtjpla

Detection of Email Spam using Natural Language Processing Based Random Forest Approach

M.A. Nivedha, S. Raja
2022 International journal of computer science and mobile computing  
., the email addresses used for any online registrations may be collected by the malignant third parties (spammers) and they expose the genuine user to various kinds of attacks.  ...  This method is well suited for misusing those temporary email addresses for sending free spam emails without revealing the spammers real account details.  ...  The false URLs sent to a user via email seem to be a legal one, so that it is a great challenge to identify it.  ... 
doi:10.47760/ijcsmc.2022.v11i02.002 fatcat:nqnacdqscfarneroogxr4can3q

Machine Learning-Based malicious users' detection in the VKontakte social network

Denis Igorevich SAMOKHVALOV
2020 Proceedings of the Institute for System Programming of RAS  
This paper presents a machine learning-based approach for detection of malicious users in the largest Russian online social network VKontakte.  ...  Furthermore, a tool for automated collection of the information about malicious accounts in the VKontakte online social network was developed and used for the dataset collection, described in this research  ...  Introduction An online social network (OSN) is an online platform that allows people who share the same views or have real-life connections to interact with each other online [1] .  ... 
doi:10.15514/ispras-2020-32(3)-10 fatcat:jggr5g4muvb7rheuecjquzkreq
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