scholarly journals CNMF: A Community-Based Fake News Mitigation Framework

Information ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 376
Author(s):  
Shaimaa Galal ◽  
Noha Nagy ◽  
Mohamed. E. El-Sharkawi
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
User Behavior ◽  
News Article ◽  
Fake News ◽  
Community Based ◽  
The Social ◽  
Mitigation Techniques ◽  
Directing Attention ◽  
Entire Network

Fake news propagation in online social networks (OSN) is one of the critical societal threats nowadays directing attention to fake news mitigation and intervention techniques. One of the typical mitigation techniques focus on initiating news mitigation campaigns targeting a specific set of users when the infected set of users is known or targeting the entire network when the infected set of users is unknown. The contemporary mitigation techniques assume the campaign users’ acceptance to share a mitigation news (MN); however, in reality, user behavior is different. This paper focuses on devising a generic mitigation framework, where the social crowd can be employed to combat the influence of fake news in OSNs when the infected set of users is undefined. The framework is composed of three major phases: facts discovery, facts searching and, community recommendation. Mitigation news circulation is accomplished by recruiting a set of social crowd users (news propagators) who are likely to accept posting the mitigation news article. We propose a set of features that identify prospect OSN audiences and news propagators. Moreover, we inspect the variant properties of the news circulation process, such as incentivizing news propagators, determining the required number of news propagators, and the adaptivity of the MN circulation process. The paper pinpoints the significance of facts searching and news propagator’s behavior features introduced in the experimental results.

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

2021 ◽  
Vol 13 (3) ◽  
pp. 76
Author(s):  
Quintino Francesco Lotito ◽  
Davide Zanella ◽  
Paolo Casari
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Simulation Models ◽  
Epidemic Models ◽  
Time Varying ◽  
Fake News ◽  
Network Access ◽  
Spreading Process ◽  
Network Topologies ◽  
Access Patterns

The pervasiveness of online social networks has reshaped the way people access information. 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. Because fake news may have a profound impact on the society at large, realistically simulating their spreading process helps evaluate the most effective countermeasures to adopt. 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. In this paper, we fill this gap by enriching typical epidemic models for fake news spreading with network topologies and dynamics that are typical of realistic social networks. Specifically, we introduce agents with the role of influencers and bots in the model and consider the effects of dynamical network access patterns, time-varying engagement, and different degrees of trust in the sources of circulating information. These factors concur with making the simulations more realistic. Among other results, we show that influencers that share fake news help the spreading process reach nodes that would otherwise remain unaffected. Moreover, we emphasize that bots dramatically speed up the spreading process and that time-varying engagement and network access change the effectiveness of fake news spreading.

Characterization of Fake News Based on Subjectivity Lexicons

2020 ◽  
Vol 1 (4) ◽  
pp. 419-441
Author(s):  
Caio L.M. Jeronimo ◽  
Leandro B. Marinho ◽  
Cclaudio E.C. Carmpelo ◽  
Adriano Veloso ◽  
Allan S. Da Costa Melo
Keyword(s):  
Social Networks ◽  
Brazilian Portuguese ◽  
News Article ◽  
Bag Of Words ◽  
Fake News ◽  
Feature Vectors ◽  
Textual Content

While many works investigate spread patterns of fake news in social networks, we focus on the textual content. Instead of relying on syntactic representations of documents (aka Bag of Words) as many works do, we seek more robust representations that may better differentiate fake from legitimate news. We propose to consider the subjectivity of news under the assumption that the subjectivity levels of legitimate and fake news are significantly different. For computing the subjectivity level of news, we rely on a set subjectivity lexicons for both Brazilian Portuguese and English languages. We then build subjectivity feature vectors for each news article by calculating the Word Mover's Distance (WMD) between the news and these lexicons considering the embedding the news words lie in, in order to analyze and classify the documents. The results demonstrate that our method is robust, especially in scenarios where training and test domains are different.

Towards a Unified Semantic Model for Online Social Networks to Ensure Interoperability and Aggregation for Analysis

2018 ◽  
pp. 978-1003
Author(s):  
Asmae El Kassiri ◽  
Fatima-Zahra Belouadha
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Online Social Networks ◽  
Semantic Model ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowing That ◽  
The Social ◽  
Industrial Projects ◽  
Media Organizations

The Online Social Networks (OSN) have a positive evolution due to the diversity of social media and the increase in the number of users. The revenue of the social media organizations is generated from the analysis of users' profiles and behaviors, knowing that surfers maintain several accounts on different OSNs. To satisfy its users, the social media organizations have initiated projects for ensuring interoperability to allow for users creating other accounts on other OSN using an initial account, and sharing content from one media to others. Believing that the future generations of Internet will be based on the semantic web technologies, multiple academic and industrial projects have emerged with the objective of modeling semantically the OSNs to ensure interoperability or data aggregation and analysis. In this chapter, we present related works and argue the necessity of a unified semantic model (USM) for OSNs; we introduce a kernel of a USM using standard social ontologies to support the principal social media and it can be extended to support other future social media.

Information Attacks and Defenses on the Social Web

2018 ◽  
pp. 216-235
Author(s):  
Agostino Poggi ◽  
Michele Tomaiuolo
Keyword(s):  
Social Networks ◽  
Social Networking ◽  
Real World ◽  
Web Sites ◽  
Online Social Networks ◽  
Social Web ◽  
Security Measures ◽  
The Social ◽  
Attacks And Defenses ◽  
Interest In Technology

Social web sites are used daily by many millions of users. They have attracted users with very weak interest in technology, including absolute neophytes of computers in general. Common users of social web sites often have a carefree attitude in sharing information. Moreover, some system operators offer sub-par security measures, which are not adequate for the high value of the published information. For all these reasons, online social networks suffer more and more attacks by sophisticated crackers and scammers. To make things worse, the information gathered from social web sites can trigger attacks to even more sensible targets. This work reviews some typical social attacks that are conducted on social networking systems, describing real-world examples of such violations and analyzing in particular the weakness of password mechanisms. It then presents some solutions that could improve the overall security of the systems.

Information Diffusion in Social Networks

2011 ◽  
pp. 146-163 ◽  
Author(s):  
Dmitry Zinoviev
Keyword(s):  
Social Networks ◽  
Information Flow ◽  
Online Social Networks ◽  
Information Diffusion ◽  
Diffusion Processes ◽  
Small World ◽  
The Social ◽  
Strength Of Weak Ties ◽  
Strategic Position

The issue of information diffusion in small-world social networks was first systematically brought to light by Mark Granovetter in his seminal paper “The Strength of Weak Ties” in 1973 and has been an area of active academic studies in the past three decades. This chapter discusses information proliferation mechanisms in massive online social networks (MOSN). In particular, the following aspects of information diffusion processes are addressed: the role and the strategic position of influential spreaders of information; the pathways in the social networks that serve as conduits for communication and information flow; mathematical models describing proliferation processes; short-term and long-term dynamics of information diffusion, and secrecy of information diffusion.

Fake News Polarization for Sentiment Analysis

2022 ◽  
pp. 255-263
Author(s):  
Chirag Visani ◽  
Vishal Sorathiya ◽  
Sunil Lavadiya
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Sentiment Analysis ◽  
Online Social Networks ◽  
Opinion Mining ◽  
Easy Access ◽  
The Internet ◽  
Fake News ◽  
Social Media Networks ◽  
Sentiment Mining

The popularity of the internet has increased the use of e-commerce websites and news channels. Fake news has been around for many years, and with the arrival of social media and modern-day news at its peak, easy access to e-platform and exponential growth of the knowledge available on social media networks has made it intricate to differentiate between right and wrong information, which has caused large effects on the offline society already. A crucial goal in improving the trustworthiness of data in online social networks is to spot fake news so the detection of spam news becomes important. For sentiment mining, the authors specialise in leveraging Facebook, Twitter, and Whatsapp, the most prominent microblogging platforms. They illustrate how to assemble a corpus automatically for sentiment analysis and opinion mining. They create a sentiment classifier using the corpus that can classify between fake, real, and neutral opinions in a document.

Multilevel Visualization Using Enhanced Social Network Analysis with Smartphone Data

2013 ◽  
Vol 5 (4) ◽  
pp. 34-54 ◽  
Author(s):  
Panagiotis Andriotis ◽  
Zacharias Tzermias ◽  
Anthi Mparmpaki ◽  
Sotiris Ioannidis ◽  
George Oikonomou
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Direct Marketing ◽  
Forensic Analysis ◽  
Three Dimensions ◽  
Fully Integrated ◽  
Aggregate Information ◽  
The Social ◽  
Correlated Information

While technology matures and becomes more productive, mobile devices can be affordable and, consequently, fully integrated in people's lives. After their unexpected bloom and acceptance, Online Social Networks are now sources of valuable information. The authors therefore use them for tasks varying from direct marketing to forensic analysis. The authors have already seen Social Network Forensics techniques focused on particular networks implementing methods that collect data from user accounts. During the forensic analysis it is common to aggregate information from different sources but, usually, this procedure causes correlation problems. Here, the authors present their method to correlate data gathered from various social networks in combination with smartphones creating a new form of social map of the user under investigation. In addition, the authors introduce a multi level graph that utilises the correlated information from the smartphone and the social networks and demonstrates in three dimensions the relevance of each contact with the suspect.

Building Online Social Networks to Engage Female Students in Information Systems

2015 ◽  
Vol 10 (4) ◽  
pp. 33-51
Author(s):  
Jaymeen R. Shah ◽  
Hsun-Ming Lee
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Information Systems ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Role Models ◽  
Online Social Network ◽  
Research Process ◽  
Female Students ◽  
The Social

During the next decade, enrollment growth in Information Systems (IS) related majors is unlikely to meet the predicted demand for qualified IS graduates. Gender imbalance in the IS related program makes the situation worse as enrollment and retention of women in the IS major has been proportionately low compared to male. In recent years, majority of high school and college students have integrated social networking sites in their daily life and habitually use these sites. Providing female students access to role models via an online social network may enhance their motivation to continue as an IS major and pursue a career in IS field. For this study, the authors follow the action research process – exploration of information systems development. In particular, a Facebook application was developed to build the social network connecting role models and students. Using the application, a basic framework is tested based on the gender of participants. The results suggest that it is necessary to have adequate number of role models accessible to students as female role-models tend to select fewer students to develop relationships with a preference for female students. Female students likely prefer composite role models from a variety of sources. This pilot study yields valuable lessons to provide informal learning fostered by role modeling via online social networks. The Facebook application may be further expanded to enhance female students' interests in IS related careers.

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