scholarly journals A Reliable Weighting Scheme for the Aggregation of Crowd Intelligence to Detect Fake News

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 319 ◽  
Author(s):  
Franklin Tchakounté ◽  
Ahmadou Faissal ◽  
Marcellin Atemkeng ◽  
Achille Ntyam
Keyword(s):  
Social Networks ◽  
Majority Vote ◽  
Internet User ◽  
Majority Voting ◽  
Third Party ◽  
Weighted Averaging ◽  
The Internet ◽  
Fake News ◽  
Vote Model ◽  
The Public

Social networks play an important role in today’s society and in our relationships with others. They give the Internet user the opportunity to play an active role, e.g., one can relay certain information via a blog, a comment, or even a vote. The Internet user has the possibility to share any content at any time. However, some malicious Internet users take advantage of this freedom to share fake news to manipulate or mislead an audience, to invade the privacy of others, and also to harm certain institutions. Fake news seeks to resemble traditional media to establish its credibility with the public. Its seriousness pushes the public to share them. As a result, fake news can spread quickly. This fake news can cause enormous difficulties for users and institutions. Several authors have proposed systems to detect fake news in social networks using crowd signals through the process of crowdsourcing. Unfortunately, these authors do not use the expertise of the crowd and the expertise of a third party in an associative way to make decisions. Crowds are useful in indicating whether or not a story should be fact-checked. This work proposes a new method of binary aggregation of opinions of the crowd and the knowledge of a third-party expert. The aggregator is based on majority voting on the crowd side and weighted averaging on the third-party side. An experimentation has been conducted on 25 posts and 50 voters. A quantitative comparison with the majority vote model reveals that our aggregation model provides slightly better results due to weights assigned to accredited users. A qualitative investigation against existing aggregation models shows that the proposed approach meets the requirements or properties expected of a crowdsourcing system and a voting system.

A Taxonomy Approach to Fake News

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Ivan Valchanov ◽  
Keyword(s):  
Communication Channels ◽  
The Internet ◽  
Online Environment ◽  
Fake News ◽  
Media Environment ◽  
The Public ◽  
The Media ◽  
Fact Checking ◽  
Points Of View ◽  
Media Corporations

The development of the Internet and social media and networks as a media environment and communication channels combined with the specificity of the journalistic profession in the online environment are a factor which contributes to the emergence and proliferation of fake news. The lack of reliable fact checking by the media and the fast news consumption by the public lead to mass disinformation about certain issues or subjects. The current paper examines fake news from several points of view and describes the models of their use – as harmless jokes, as lack of journalistic competence or professionalism and as means of manipulation and intentional misleading of public opinion. The attempts of big media corporations to fight fake news are also described.

Privacy Concerns for Ubiquitous Data Aggregation and Storage

2014 ◽  
Author(s):  
Jarrod M. Rifkind ◽  
Seymour E. Goodman
Keyword(s):  
World Bank ◽  
High Performance ◽  
Business Models ◽  
The United States ◽  
Third Party ◽  
The Internet ◽  
Public And Private ◽  
Personal Lives ◽  
The Public ◽  
The World

Information technology has drastically changed the ways in which individuals are accounted for and monitored in societies. Over the past two decades, the United States and other countries worldwide have seen a tremendous increase in the number of individuals with access to the Internet. Data collected by the World Bank shows that 17.5 of every 100 people in the world had access to the Internet in 2006, and this number increased to 23.2 in 2008, 29.5 in 2010, and 32.8 in 2011 (World Bank 2012). According to the latest Cisco traffic report, Internet traffic exceeded 30 exabytes (1018 bytes) per month in 2011 and is expected to reach a zettabyte (1021 bytes) per month by 2015 (Cisco Systems 2011). Activities on the Web are no longer limited to seemingly noncontroversial practices like e-mail. The sheer growth of the Internet as a medium for communication and information sharing as well as the development of large, high-performance data centers have made it easier and less expensive for companies and governments to aggregate large amounts of data generated by individuals. Today, many people’s personal lives can be pieced together relatively easily according to their search histories and the information that they provide on social networking websites such as Facebook and Twitter. Therefore, technological breakthroughs associated with computing raise important questions regarding information security and the role of privacy in society. As individuals begin using the Internet for e-commerce, e-government, and a variety of other services, data about their activities has been collected and stored by entities in both the public and private sectors. For the private sector, consumer activities on the Internet provide lucrative information about user spending habits that can then be used to generate targeted advertisements. Companies have developed business models that rely on the sale of such information to third-party entities, whether they are other companies or the federal government. As for the public sector, data collection occurs through any exchange a government may have with its citizens.

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.

scholarly journals Modern holiday culture of Russia: preservation Russian traditions, constructing new symbols and meanings

2020 ◽  
Vol 10 ◽  
pp. 160-171
Author(s):  
Т. N. Zolotova ◽  
Keyword(s):  
Social Networks ◽  
Social Practice ◽  
Public Life ◽  
Consumer Psychology ◽  
The Internet ◽  
Cultural Institutions ◽  
National Unity ◽  
Cultural Traditions ◽  
The Public ◽  
Public Consciousness

The article is devoted to identifying Russian ethnic traditions and symbols that are preserved in the holiday calendar of modern Russia. Most attention is paid to such holidays as Christmas, Epiphany, Russia day and national unity day. Conclusions are made about the preservation, revival and transformation in the public life of a private celebratory customs on semantic convergence of the notions “Russian” and “Orthodox”, established in the public consciousness and social practice new social and political holidays thanks to their chronological overlay on the traditional advent calendar and the activities of cultural institutions due to the needs of the state in strengthening the ideological component of the holidays and strengthening of the unity of the nation. The popularity and mass character of holidays is influenced by the spread of modern forms of communication — television and the Internet with a variety of content and social networks that form a kind of “fashion” in society to follow certain customs. Strengthening consumer psychology and ignoring cultural traditions lead to a functional imbalance in the festive and ceremonial sphere, so it is necessary to take care of the historical and cultural heritage and design new images and meanings.

scholarly journals Fake News Detection with Machine Learning

2020 ◽  
Vol 10 (1) ◽  
pp. 124-127
Keyword(s):  
Machine Learning ◽  
Natural Language Processing ◽  
Language Processing ◽  
Online News ◽  
The Internet ◽  
Daily Routine ◽  
Fake News ◽  
Criminal Records ◽  
The Public ◽  
Processing Techniques

As the internet is becoming part of our daily routine there is sudden growth and popularity of online news reading. This news can become a major issue to the public and government bodies (especially politically) if its fake hence authentication is necessary. It is essential to flag the fake news before it goes viral and misleads the society. In this paper, various Natural Language Processing techniques along with the number of classifiers are used to identify news content for its credibility.Further this technique can be used for various applications like plagiarismcheck , checking for criminal records.

Genre shifts in Israeli campaign advertisements: Strategies and rhetorical functions

2019 ◽  
Vol 39 (2) ◽  
pp. 261-288 ◽  
Author(s):  
Pnina Shukrun-Nagar
Keyword(s):  
Social Networks ◽  
Present Article ◽  
The Internet ◽  
Political Campaign ◽  
The Public ◽  
Visual Elements ◽  
Personal Conversation ◽  
Linguistic Strategies

Abstract The present article addresses genre shifts in Israeli political campaign in 2013, specifically written advertisements published in newspapers, on the Internet, on stickers, in leaflets, and on billboards. I examine shifts to diverse genres (protest slogans, writing on social networks, personal conversation, a math exercise etc.), and analyze various discursive and para-linguistic strategies by means of which these shifts are implemented: use of registers and sociolects identified with particular genres; syntactical, semantic and lexical repetitions; graphic, typographical, and visual elements, etc. I show that due to the expectations of the addressees regarding the reconstructed genres and the addressing parties, genre shifts may serve to fulfill two main pragmatic-rhetorical functions: (1) Promoting messages regarding the desired conduct of the voters during the elections; (2) Self-positioning of the parties, either to strengthen their existing image among the public or to create a new, surprising one. I thus emphasize the key role played by genre shifts in the intertextual phenomenon of integrating semiotic meanings into a linguistic text; specifically in this case, integrating cultural-societal meanings into campaign advertisements.

scholarly journals The Internet and Cancellation Culture: The Impact of the Public Opinion on the Exercise of the Individual Right to Freedom of Expression

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Elaine Celina Afra da Silva Santos
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Freedom Of Expression ◽  
The Internet ◽  
Individual Rights ◽  
The Public ◽  
Deductive Method ◽  
The Individual ◽  
The Impact ◽  
Legal Consequences

This article analyzes the impact of the culture of cancellation promoted by users of social networks on the exercise of individual rights, more precisely Freedom of Expression. The study presents the analysis of the content inherent to what would be the cancellation, its aspects and practical consequences in the individual sphere of the users. The theme is approached by the deductive method and through doctrinal research. The article intends to answer if there are legal consequences resulting from the use of this resource by users.

scholarly journals Fake News Reaching Young People on Social Networks: Distrust Challenging Media Literacy

Publications ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 24
Author(s):  
Ana Pérez-Escoda ◽  
Luis Miguel Pedrero-Esteban ◽  
Juana Rubio-Romero ◽  
Carlos Jiménez-Narros
Keyword(s):  
Social Networks ◽  
Young People ◽  
Media Literacy ◽  
Exploratory Study ◽  
The Internet ◽  
Fake News ◽  
Convenience Sample ◽  
Generation Z ◽  
The Media ◽  
Special Concern

Current societies are based on huge flows of information and knowledge circulating on the Internet, created not only by traditional means but by all kinds of users becoming producers, which leads to fake news and misinformation. This situation has been exacerbated by the pandemic to an unprecedented extent through social media, with special concern among young people. This study aims to provide significant data about the youngest generation in Spain (Generation Z) regarding their media and information consumption, their social network use, and their relationship with fake news, all in relation to the feeling of reliability/trust. Focusing on a convenience sample of 408 young Spanish students from Generation Z aged 18 to 22, a descriptive exploratory study is presented. Data collection was performed with an adapted questionnaire. Results show that young Spanish people use networks for information, showing a surprising lack of trust in social networks as the media they consume the most. The content they consume the most since the occurrence of COVID-19 is related to politics, entertainment, humor, and music. On the other hand, distrust of politicians, media, and journalists is evident. The conclusion is that media literacy is still more necessary than ever, but with the added challenge of mistrust: maybe it is time to rethink media literacy.

Extreme Gradient Boosting for Cyberpropaganda Detection

2021 ◽  
Author(s):  
Jaouhar Fattahi ◽  
Mohamed Mejri ◽  
Marwa Ziadia
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Gradient Boosting ◽  
The Internet ◽  
Bag Of Words ◽  
Fake News ◽  
Inverse Document Frequency ◽  
Document Frequency ◽  
Extreme Gradient Boosting ◽  
New Phenomena

Propaganda, defamation, abuse, insults, disinformation and fake news are not new phenomena and have been around for several decades. However, with the advent of the Internet and social networks, their magnitude has increased and the damage caused to individuals and corporate entities is becoming increasingly greater, even irreparable. In this paper, we tackle the detection of text-based cyberpropaganda using Machine Learning and NLP techniques. We use the eXtreme Gradient Boosting (XGBoost) algorithm for learning and detection, in tandem with Bag-of-Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF) for text vectorization. We highlight the contribution of gradient boosting and regularization mechanisms in the performance of the explored model.

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