False News On Social Media: A Data-Driven Survey

In the past few years, the research community has dedicated growing interest to the issue of false news circulating on social networks. The widespread attention on detecting and characterizing false news has been motivated by considerable backlashes of this threat against the real world. As a matter of fact, social media platforms exhibit peculiar characteristics, with respect to traditional news outlets, which have been particularly favorable to the proliferation of deceptive information. They also present unique challenges for all kind of potential interventions on the subject. As this issue becomes of global concern, it is also gaining more attention in academia. The aim of this survey is to offer a comprehensive study on the recent advances in terms of detection, characterization and mitigation of false news that propagate on social media, as well as the challenges and the open questions that await future research on the field. We use a data-driven approach, focusing on a classification of the features that are used in each study to characterize false information and on the datasets used for instructing classification methods. At the end of the survey, we highlight emerging approaches that look most promising for addressing false news

Чутки як соціокомунікаційний феномен

У статті комплексно розглянуто особливості феномену чуток, обставини, за яких вони виникають, та суспільну роль, яку вони виконують. Наведено стислий аналіз ключових етапів вивчення феномену чуток у різні історичні періоди. Відповідно до цього виокремлено головні характеристики та спроби систематизації чуток на різних етапах розвитку наукової думки. У результаті здійсненого аналізу зроблено висновок, що чутки є особливим жанром комунікації зі специфічними характеристиками. Поява, розповсюдження та потенційні наслідки чуток аналізуються з точки зору масових комунікацій з урахуванням напрацювань суміжних наук. Використано доробок науковців у царині психології, соціальної психології, соціології, історії, політичних технологій, реклами. Окрему увагу приділено новітній проблематиці, пов’язаній з особливостями й наслідками поширення чуток у соціальних мережах. Проаналізовано зміни каналів поширення чуток з розвитком засобів масової комунікації, а також простежено зв’язок чуток з фейковими новинами. Зроблено висновок, що у зв’язку з блискавичністю поширення чуток у соцмережах ця інформація має високий потенціал шкідливого впливу. Під час масових заворушень чи суспільних криз це може стати серйозною загрозою для державної безпеки та життя людей. Зроблено огляд актуальних досліджень, пов’язаних з намаганням виявити закономірності поширення чуток у соціальних мережах, спробами зрозуміти його динаміку й можливі засоби протидії. Хоча дослідники активно шукають шляхи виявлення та стримування шкідливих чуток, зокрема з використанням машинного навчання та штучного інтелекту, досі не запропоновано системного рішення цієї проблеми. Виходячи з цього, окреслено перспективи подальших наукових студій у цьому напрямі.The article proposes to consider comprehensively the features of the rumors phenomenon, the circumstances under which they arise, and the social role they play. A brief analysis of the key stages of studying the phenomenon of rumors in different historical periods is given. Accordingly, the main characteristics and attempts to systematize rumors at different stages of scientific thought development highlighted. As a result of the analysis, it is concluded that rumors are a special genre of communication with specific characteristics. The appearance, spread and potential consequences of rumors are analyzed in terms of mass communications, taking into account the findings of related sciences. The works of scientists in the field of psychology, social psychology, sociology, history, political technology, advertising are used. This review paid particular attention to the latest issues related to the features and consequences of the spread of rumors on social networks. The paper analyses the changes in rumors’ distribution channels with the development of mass media and traces the connection of rumors with fake news. The paper concludes that due to the lightning spread of rumors on social networks, this information has a high potential for harmful effects. During riots or social crises, this can be a serious threat to national security and people’s lives. An overview of current research related to the attempt to identify patterns of rumors in social networks, attempts to understand its dynamics and possible ways to counteract. Although researchers are actively looking for ways to detect and deter harmful rumors, using machine learning and artificial intelligence, no on put forward systemic solution for this issue. Based on this, the paper outlined the prospect of further study in this direction

Rumor Detection on Social Media: Datasets, Methods and Opportunities

Social media platforms have been used for information and news gathering, and they are very valuable in many applications. However, they also lead to the spreading of rumors and fake news. Many efforts have been taken to detect and debunk rumors on social media by analyzing their content and social context using machine learning techniques. This paper gives an overview of the recent studies in the rumor detection field. It provides a comprehensive list of datasets used for rumor detection, and reviews the important studies based on what types of information they exploit and the approaches they take. And more importantly, we also present several new directions for future research.Comment: 10 page

The Web of False Information: Rumors, Fake News, Hoaxes, Clickbait, and Various Other Shenanigans

A new era of Information Warfare has arrived. Various actors, including state-sponsored ones, are weaponizing information on Online Social Networks to run false information campaigns with targeted manipulation of public opinion on specific topics. These false information campaigns can have dire consequences to the public: mutating their opinions and actions, especially with respect to critical world events like major elections. Evidently, the problem of false information on the Web is a crucial one, and needs increased public awareness, as well as immediate attention from law enforcement agencies, public institutions, and in particular, the research community. In this paper, we make a step in this direction by providing a typology of the Web's false information ecosystem, comprising various types of false information, actors, and their motives. We report a comprehensive overview of existing research on the false information ecosystem by identifying several lines of work: 1) how the public perceives false information; 2) understanding the propagation of false information; 3) detecting and containing false information on the Web; and 4) false information on the political stage. In this work, we pay particular attention to political false information as: 1) it can have dire consequences to the community (e.g., when election results are mutated) and 2) previous work show that this type of false information propagates faster and further when compared to other types of false information. Finally, for each of these lines of work, we report several future research directions that can help us better understand and mitigate the emerging problem of false information dissemination on the Web

Early Detection of Cyberbullying on Social Media Networks

[Abstract] Cyberbullying is an important issue for our society and has a major negative effect on the victims, that can be highly damaging due to the frequency and high propagation provided by Information Technologies. Therefore, the early detection of cyberbullying in social networks becomes crucial to mitigate the impact on the victims. In this article, we aim to explore different approaches that take into account the time in the detection of cyberbullying in social networks. We follow a supervised learning method with two different specific early detection models, named threshold and dual. The former follows a more simple approach, while the latter requires two machine learning models. To the best of our knowledge, this is the first attempt to investigate the early detection of cyberbullying. We propose two groups of features and two early detection methods, specifically designed for this problem. We conduct an extensive evaluation using a real world dataset, following a time-aware evaluation that penalizes late detections. Our results show how we can improve baseline detection models up to 42%.This research was supported by the Ministry of Economy and Competitiveness of Spain and FEDER funds of the European Union (Project PID2019-111388GB-I00) and by the Centro de Investigación de Galicia “CITIC”, funded by Xunta de Galicia (Galicia, Spain) and the European Union (European Regional Development Fund — Galicia 2014–2020 Program) , by grant ED431G 2019/01Xunta de Galicia; ED431G 2019/0

FAKE NEWS PROLIFERATION IN NIGERIA: CONSEQUENCES, MOTIVATIONS, AND PREVENTION THROUGH AWARENESS STRATEGIES

Purpose: This study aims to understand the effects of fake news spreading in Nigeria, the reasons for fake news sharing among social media users, and eventually propose preventive measures (i.e. awareness strategies) to combat the proliferation of fake news in Nigeria. Main results: Some grave implications of fake news sharing were identified such as death, conflict escalation, political hostility, and societal panic. Meanwhile, people were motivated to share news mainly because of their civil obligation to inform others and provide advice or warning. These motivations, together with other contextual reasons such as media control, interpersonal trust and youth unemployment, had led to fake news proliferation in Nigeria. Methodology: This study adopts a documentary research method to generate the information necessary to investigate fake news spread in Nigeria. A total of 265 articles were drawn from Google Scholar search and after a close examination, only 20 articles were included for analysis. Implications: There is a need to increase fake news awareness, media and information literacy among Nigerians. Social media users should be constantly informed through adequate advertisements, workshops, conferences, and other forms of sensitization, about the consequences of fake news sharing, how to spot and differentiate fake news with made-up news and why it is imperative to be self-aware before forwarding any message. Originality/novelty: This paper contributes to knowledge in two ways. First, it compiles past research on fake news in Nigeria and analysed contextual factors and consequences of fake news proliferation in this context. Second, it reinforces the need for fake news awareness as a means of reducing the spread of fake news among social media users in Nigeria

A systematic literature review on spam content detection and classification

The presence of spam content in social media is tremendously increasing, and therefore the detection of spam has become vital. The spam contents increase as people extensively use social media, i.e ., Facebook, Twitter, YouTube, and E-mail. The time spent by people using social media is overgrowing, especially in the time of the pandemic. Users get a lot of text messages through social media, and they cannot recognize the spam content in these messages. Spam messages contain malicious links, apps, fake accounts, fake news, reviews, rumors, etc. To improve social media security, the detection and control of spam text are essential. This paper presents a detailed survey on the latest developments in spam text detection and classification in social media. The various techniques involved in spam detection and classification involving Machine Learning, Deep Learning, and text-based approaches are discussed in this paper. We also present the challenges encountered in the identification of spam with its control mechanisms and datasets used in existing works involving spam detection