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Graph-based Modeling of Online Communities for Fake News Detection [article]

Shantanu Chandra, Pushkar Mishra, Helen Yannakoudakis, Madhav Nimishakavi, Marzieh Saeidi, Ekaterina Shutova
2020 arXiv   pre-print
In this work, we propose a novel social context-aware fake news detection framework, SAFER, based on graph neural networks (GNNs).  ...  We furthermore perform a systematic comparison of several GNN models for this task and introduce novel methods based on relational and hyperbolic GNNs, which have not been previously used for user or community  ...  To advance this line of research, we propose SAFER (Socially Aware Fake nEws detection fRamework), a graph-based approach to fake news detection that aggregates information from 1) the content of the article  ... 
arXiv:2008.06274v4 fatcat:v4en2yshzjgq3ha3mokemvz7cy

Community Spam Detection Methodologies for Recommending Nodes

2019 International journal of recent technology and engineering  
The work is comprehended in how data is collected, types of spammers, classifiers, machine learning, review on spammers and community detection and whether it is graph based or non graph based dataset.  ...  A survey of research publications on Spammers and Malicious account based on malicious categories for the detected communities with the help of various categories discussed in the mindmap  ...  ONLINE SOCIAL NETWORK DATASET The online network dataset is categorized in to two main domains Graph based and Non-Graph in figure 3 based by comparing the previous studies dealt in line with malicious  ... 
doi:10.35940/ijrte.b1024.0782s419 fatcat:6cettiuwwrfrbaehbt4l6voff4

Combating fake news

Laks V. S. Lakshmanan, Michael Simpson, Saravanan Thirumuruganathan
2019 Proceedings of the VLDB Endowment  
Detection and mitigation of fake news is one of the fundamental problems of our times and has attracted widespread attention.  ...  Effective tools for addressing fake news could only be built by leveraging the synergistic relationship between database and other research communities.  ...  First, we wish to familiarize the database community with prior attempts by the ML and AI communities for detecting fake news.  ... 
doi:10.14778/3352063.3352117 fatcat:zvmwkilnifamjndncz6k5qqmr4

A Framework for Detecting Cloning Attacks in OSN Based on a Novel Social Graph Topology

Ali M. Meligy, Hani M. Ibrahim, Mohamed F. Torky
2015 International Journal of Intelligent Systems and Applications  
Our proposed detection model used to recognize the stranger instances of communications and social actions that performed using fake profiles in OSN.  ...  Another contribution is a proposed detection model that based on TSG topology as well as two techniques; Deterministic Finite Automaton (DFA) and Regular Expression.  ...  Fig. 6 . 6 A proposed Detection Model of TSG (DMT) model for recognizing Fake Profiles VI.  ... 
doi:10.5815/ijisa.2015.03.02 fatcat:pew6msbdi5csbmddh3mwlyvcle

Security techniques for intelligent spam sensing and anomaly detection in online social platforms

Monther Aldwairi, Loai Tawalbeh
2020 International Journal of Electrical and Computer Engineering (IJECE)  
In addition, we use the concept of social graphs and weighted cliques in the detection of suspicious behavior of certain online groups and to prevent further planned actions such as cyber/terrorist attacks  ...  This research provides a comprehensive related work survey and investigates the application of artificial neural networks for intrusion detection systems and spam filtering for OSNs.  ...  Many previous related works discussed the wide spread of fake news over social networks and proposed some solutions for fake news detection by applying machine learning techniques over Online Social Networks  ... 
doi:10.11591/ijece.v10i1.pp275-287 fatcat:hucpuhkbhfam5efmyjva3l2iki

Social Media Fake Account Detection for Afan Oromo Language using Machine Learning

2020 New Media and Mass Communication  
In this work we propose new model using machine learning and NLP (Natural Language Processing) techniques to enhance the accuracy rate in detecting the fake identities in online social networks.  ...  Most social network services are web-based and provide means for users to interact over the Internet. (M.  ...  Social Networks being the center of attraction for many applications and they incorporate a range of new information and communication tools to the user community.  ... 
doi:10.7176/nmmc/90-01 fatcat:agdvymucizh7rm4rvejk3kd3ye

Fake Reviewer Group Detection in Online Review Systems [article]

Chen Cao, Shihao Li, Shuo Yu, Zhikui Chen
2021 arXiv   pre-print
First, cohensive groups are detected with modularity-based graph convolutional networks.  ...  In this work, we present an unsupervised and end-to-end approach for fake reviewer group detection in online reviews. Specifically, our method can be summarized into two procedures.  ...  based heterogeneous graph neural network for fake news detection,” [3] S. Feng, R. Banerjee, and Y.  ... 
arXiv:2112.06403v1 fatcat:vf6ku3uezva23fuoi6kohnooay

An Empirical Study for Detecting Fake Facebook Profiles Using Supervised Mining Techniques

Mohammed Basil Albayati, Ahmad Mousa Altamimi
2019 Informatica (Ljubljana, Tiskana izd.)  
Fake profiles are also used by Scammers to infiltrate networks of friends to wreak all sorts of havoc as stealing valuable information, financial fraud, or entering other user's social graph.  ...  Our social life and the way of people communicate are greatly affected by the social media technologies.  ...  ACKNOWLEDGMENT The authors are grateful to the Applied Science Private University, Amman-Jordan, for the full financial support granted to cover the publication fee of this research article.  ... 
doi:10.31449/inf.v43i1.2319 fatcat:57we457kl5dpdo7e4hrvn7lkem

Social Media Identity Deception Detection: A Survey [article]

Ahmed Alharbi, Hai Dong, Xun Yi, Zahir Tari, Ibrahim Khalil
2021 arXiv   pre-print
Social media have been growing rapidly and become essential elements of many people's lives. Meanwhile, social media have also come to be a popular source for identity deception.  ...  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.  ...  Therefore, it is worthwhile to explore the application of graph-based techniques for social botnet detection. • Exploring social botnets in a new context such as interference of bots with public discourse  ... 
arXiv:2103.04673v1 fatcat:zf6xcn3pafcgfbxmoewc3yhhpi

Influencing Opinions through False Online Information : A Study

Baldev Singh
2019 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
It summarized various False information spreading Mechanisms, False Information Detection Algorithms, Mining Techniques for Online False Information to detect and prevent false online information.  ...  In this study, the focus is on to highlight false information generated through fake reviews, fake news and hoaxes based on web & social media.  ...  The broad categories of algorithms for false information detection are mainly Feature engineering [25,29], modeling and graph based.  ... 
doi:10.32628/cseit1952101 fatcat:nl6aeqetjjandpsuyp7qxrh4oe

Improving Generalizability of Fake News Detection Methods using Propensity Score Matching [article]

Bo Ni, Zhichun Guo, Jianing Li, Meng Jiang
2020 arXiv   pre-print
Recently, due to the booming influence of online social networks, detecting fake news is drawing significant attention from both academic communities and general public.  ...  In this paper, we consider the existence of confounding variables in the features of fake news and use Propensity Score Matching (PSM) to select generalizable features in order to reduce the effects of  ...  The topics mainly include fake news detection and causal inference. Fake News Detection Online fake news detection has attracted a lot of attention from researchers.  ... 
arXiv:2002.00838v1 fatcat:fl6v76wcufbkvncbogg4yapyme

Abnormal User Detection of Malicious Accounts in Online Social Networks using Cookie Based Cross Verification

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
cross-verification to detect malicious activity in an online social network by using random forest machine learning algorithm We also attempt to understand the limitations posed by Facebook in terms of  ...  availability of data for collection, and analysis, and try to understand if existing techniques can be used to identify and study poor quality content on Facebook and other social networks.  ...  Mohammadreza Mohammadrezaei et al proposed [5] "Identifying Fake Accounts on Social Networks Based on Graph Analysis and Classification Algorithms" It is a new model which is based on similarity between  ... 
doi:10.35940/ijitee.i1131.0789s419 fatcat:zsuk6wqjs5hzrfbilwv3nnpw5i

A comparative analysis of Graph Neural Networks and commonly used machine learning algorithms on fake news detection [article]

Fahim Belal Mahmud, Mahi Md. Sadek Rayhan, Mahdi Hasan Shuvo, Islam Sadia, Md.Kishor Morol
2022 arXiv   pre-print
Besides this, we create different GNN layers for fusing graph-structured news propagation data and the text data as the node feature in our GNN models.  ...  Most of the existing fake news detection algorithms are solely focused on the news content only but engaged users prior posts or social activities provide a wealth of information about their views on news  ...  [26] described the importance of modeling the social context for the task of fake news detection.  ... 
arXiv:2203.14132v1 fatcat:okudbjyu65enjhxk4ss67f65uu

Realistic Aspects of Simulation Models for Fake News Epidemics over Social Networks

Quintino Francesco Lotito, Davide Zanella, Paolo Casari
2021 Future Internet  
Online social networks make it common for users to inform themselves online and share news among their peers, but also favor the spreading of both reliable and fake news alike.  ...  It is customary to model the spreading of fake news via the same epidemic models used for common diseases; however, these models often miss concepts and dynamics that are peculiar to fake news spreading  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/fi13030076 fatcat:rpbvqozje5fxhnhm5h2ylbqcaa

Information Credibility in the Social Web: Contexts, Approaches, and Open Issues [article]

Gabriella Pasi, Marco Viviani
2020 arXiv   pre-print
Three of the main contexts in which the assessment of information credibility has been investigated concern: (i) the detection of opinion spam in review sites, (ii) the detection of fake news in microblogging  ...  Many of them are based on data-driven models, i.e., they employ machine learning techniques to identify misinformation, but recently also model-driven approaches are emerging, as well as graph-based approaches  ...  spam detection, fake news detection, and credibility assessment of online healthrelated information [47] .  ... 
arXiv:2001.09473v1 fatcat:4iczmmnuw5geveatbmx3p4r7im
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