The Never Ending Intellectual Theft of Truth

2021 ◽  
pp. 39-68
Author(s):  
David Brian Ross ◽  
Gina Lynne Peyton
Keyword(s):  
Printing Press ◽  
Digital Citizenship ◽  
Fake News ◽  
False Information ◽  
Mainstream Media ◽  
Political Perspective

The purpose of this chapter is to examine how the fake news has originated. This term has been in existence for decades, since the evolution of the printing press, which also disseminated false information. The mainstream media and non-mainstream media or just individuals in general have their own biases and agendas, so misinformation, disinformation, exaggerations, and deceptions will exist. This chapter will provide individuals from any political perspective or other beliefs evidence to make their own judgements. Digital citizenship and literacy will be explored using various examples of obtaining information and use of devices. In addition, this chapter will consider how researchers should take risks to explore controversial topics such as fake news to inform an audience using research.

scholarly journals Fake and Real News detection Using Python

2020 ◽  
pp. 423-428
Author(s):  
Fakhra Akhtar ◽  
Faizan Ahmed Khan
Keyword(s):  
Social Media ◽  
Fake News ◽  
False Information ◽  
False Negatives ◽  
Mainstream Media ◽  
Social Media Platforms ◽  
The Masses ◽  
Negative Attributes ◽  
Entire Dataset ◽  
F Measure

<p>In the digital age, fake news has become a well-known phenomenon. The spread of false evidence is often used to confuse mainstream media and political opponents, and can lead to social media wars, hatred arguments and debates.Fake news is blurring the distinction between real and false information, and is often spread on social media resulting in negative views and opinions. Earlier Research describe the fact that false propaganda is used to create false stories on mainstream media in order to cause a revolt and tension among the masses The digital rights foundation DRF report, which builds on the experiences of 152 journalists and activists in Pakistan, presents that more than 88 % of the participants find social media platforms as the worst source for information, with Facebook being the absolute worst. The dataset used in this paper relates to Real and fake news detection. The objective of this paper is to determine the Accuracy , precision , of the entire dataset .The results are visualized in the form of graphs and the analysis was done using python. The results showed the fact that the dataset holds 95% of the accuracy. The number of actual predicted cases were 296. Results of this paper reveals that The accuracy of the model dataset is 95.26 % the precision results 95.79 % whereas recall and F-Measure shows 94.56% and 95.17% accuracy respectively.Whereas in predicted models there are 296 positive attributes , 308 negative attributes 17 false positives and 13 false negatives. This research recommends that authenticity of news should be analysed first instead of drafting an opinion, sharing fake news or false information is considered unethical journalists and news consumers both should act responsibly while sharing any news.</p>

Student Experiences with Digital Citizenship: A Comparative Cultural Study

Libri ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jenna Kammer ◽  
Kodjo Atiso ◽  
Edward Mensah Borteye
Keyword(s):  
United States ◽  
Cultural Study ◽  
Undergraduate Students ◽  
Information Literacy ◽  
Technology Use ◽  
Student Experiences ◽  
The Internet ◽  
Digital Citizenship ◽  
Fake News ◽  
Ethical Aspects

Abstract This comparative cultural study examines differences in digital citizenship between undergraduate information literacy students at two different, but similar, universities across the globe from each other. Under the notion that the internet and prevalence of mobile devices allow students to participate online as digital citizens in ways that were impossible before, we use mixed methods to compare the attitudes and experiences of undergraduate students at a university in the midwestern United States (U.S.), with a university on the southwestern coast of Ghana. We also examine the policies related to technology use at these schools. The findings indicate that Ghanaian students had higher levels of digital citizenship. Other findings suggest that network issues are a problem for students in both schools, especially for Ghana, and ethical aspects of internet use, like cyberbullying, hacking, and fake news, deter students from participating online as much as they would like.

scholarly journals Intelligent Detection of False Information in Arabic Tweets Utilizing Hybrid Harris Hawks Based Feature Selection and Machine Learning Models

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 556
Author(s):  
Thaer Thaher ◽  
Mahmoud Saheb ◽  
Hamza Turabieh ◽  
Hamouda Chantar
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Feature Selection ◽  
Language Processing ◽  
User Profile ◽  
Vital Role ◽  
Classification Model ◽  
Fake News ◽  
False Information ◽  
Social Media Platforms

Fake or false information on social media platforms is a significant challenge that leads to deliberately misleading users due to the inclusion of rumors, propaganda, or deceptive information about a person, organization, or service. Twitter is one of the most widely used social media platforms, especially in the Arab region, where the number of users is steadily increasing, accompanied by an increase in the rate of fake news. This drew the attention of researchers to provide a safe online environment free of misleading information. This paper aims to propose a smart classification model for the early detection of fake news in Arabic tweets utilizing Natural Language Processing (NLP) techniques, Machine Learning (ML) models, and Harris Hawks Optimizer (HHO) as a wrapper-based feature selection approach. Arabic Twitter corpus composed of 1862 previously annotated tweets was utilized by this research to assess the efficiency of the proposed model. The Bag of Words (BoW) model is utilized using different term-weighting schemes for feature extraction. Eight well-known learning algorithms are investigated with varying combinations of features, including user-profile, content-based, and words-features. Reported results showed that the Logistic Regression (LR) with Term Frequency-Inverse Document Frequency (TF-IDF) model scores the best rank. Moreover, feature selection based on the binary HHO algorithm plays a vital role in reducing dimensionality, thereby enhancing the learning model’s performance for fake news detection. Interestingly, the proposed BHHO-LR model can yield a better enhancement of 5% compared with previous works on the same dataset.

What the fake? Assessing the extent of networked political spamming and bots in the propagation of #fakenews on Twitter

2019 ◽  
Vol 43 (1) ◽  
pp. 53-71 ◽  
Author(s):  
Ahmed Al-Rawi ◽  
Jacob Groshek ◽  
Li Zhang
Keyword(s):  
Social Media ◽  
Data Sets ◽  
Fake News ◽  
Content Type ◽  
Mainstream Media ◽  
News Discourse ◽  
Twitter Data ◽  
News Organizations ◽  
Twitter Users ◽  
One Year

PurposeThe purpose of this paper is to examine one of the largest data sets on the hashtag use of #fakenews that comprises over 14m tweets sent by more than 2.4m users.Design/methodology/approachTweets referencing the hashtag (#fakenews) were collected for a period of over one year from January 3 to May 7 of 2018. Bot detection tools were employed, and the most retweeted posts, most mentions and most hashtags as well as the top 50 most active users in terms of the frequency of their tweets were analyzed.FindingsThe majority of the top 50 Twitter users are more likely to be automated bots, while certain users’ posts like that are sent by President Donald Trump dominate the most retweeted posts that always associate mainstream media with fake news. The most used words and hashtags show that major news organizations are frequently referenced with a focus on CNN that is often mentioned in negative ways.Research limitations/implicationsThe research study is limited to the examination of Twitter data, while ethnographic methods like interviews or surveys are further needed to complement these findings. Though the data reported here do not prove direct effects, the implications of the research provide a vital framework for assessing and diagnosing the networked spammers and main actors that have been pivotal in shaping discourses around fake news on social media. These discourses, which are sometimes assisted by bots, can create a potential influence on audiences and their trust in mainstream media and understanding of what fake news is.Originality/valueThis paper offers results on one of the first empirical research studies on the propagation of fake news discourse on social media by shedding light on the most active Twitter users who discuss and mention the term “#fakenews” in connection to other news organizations, parties and related figures.

scholarly journals Discursive Deflection: Accusation of “Fake News” and the Spread of Mis- and Disinformation in the Tweets of President Trump

2018 ◽  
Vol 4 (2) ◽  
pp. 205630511877601 ◽  
Author(s):  
Andrew S. Ross ◽  
Damian J. Rivers
Keyword(s):  
Corpus Analysis ◽  
Fake News ◽  
Hillary Clinton ◽  
Donald Trump ◽  
The Public ◽  
Mainstream Media ◽  
Objective Truth ◽  
Reliable Source ◽  
The Media ◽  
Media Reports

Twitter is increasingly being used within the sociopolitical domain as a channel through which to circulate information and opinions. Throughout the 2016 US Presidential primaries and general election campaign, a notable feature was the prolific Twitter use of Republican candidate and then nominee, Donald Trump. This use has continued since his election victory and inauguration as President. Trump’s use of Twitter has drawn criticism due to his rhetoric in relation to various issues, including Hillary Clinton, the size of the crowd in attendance at his inauguration, the policies of the former Obama administration, and immigration and foreign policy. One of the most notable features of Trump’s Twitter use has been his repeated ridicule of the mainstream media through pejorative labels such as “fake news” and “fake media.” These labels have been deployed in an attempt to deter the public from trusting media reports, many of which are critical of Trump’s presidency, and to position himself as the only reliable source of truth. However, given the contestable nature of objective truth, it can be argued that Trump himself is a serial offender in the propagation of mis- and disinformation in the same vein that he accuses the media. This article adopts a corpus analysis of Trump’s Twitter discourse to highlight his accusations of fake news and how he operates as a serial spreader of mis- and disinformation. Our data show that Trump uses these accusations to demonstrate allegiance and as a cover for his own spreading of mis- and disinformation that is framed as truth.

scholarly journals A family of falsehoods: Deception, media hoaxes and fake news

2018 ◽  
Vol 39 (3) ◽  
pp. 350-361 ◽  
Author(s):  
Teri Finneman ◽  
Ryan J. Thomas
Keyword(s):  
Social Media ◽  
Fake News ◽  
Public Officials ◽  
False Information ◽  
Media Environment ◽  
News Organizations ◽  
Information Spread ◽  
History Of

“Fake news” became a concern for journalists in 2017 as news organizations sought to differentiate themselves from false information spread via social media, websites and public officials. This essay examines the history of media hoaxing and fake news to help provide context for the current U.S. media environment. In addition, definitions of the concepts are proposed to provide clarity for researchers and journalists trying to explain these phenomena.

Countering misinformation and disinformation during contentious episodes in a divided society: Tweeting the 2014 and 2015 Ardoyne parade disputes

First Monday ◽  
2021 ◽  
Author(s):  
Paul Reilly
Keyword(s):  
Digital Media ◽  
Information Flows ◽  
Fake News ◽  
Liberal Democracies ◽  
Minimal Impact ◽  
Mainstream Media ◽  
Crisis Events ◽  
Public Demonstrations ◽  
Acute Crisis

Whereas there has been much research into the manufacture of ‘fake news’ to sow disunity within liberal democracies, little is known about how information disorders affect deeply divided societies. This paper addresses that gap in the literature by exploring how digital media are used to share misinformation and disinformation during contentious public demonstrations in Northern Ireland. It does so by reviewing the literature on social media information flows during acute crisis events, and qualitatively exploring the role of Twitter in spreading misinformation and disinformation during the 2014 and 2015 Ardoyne parade disputes. Results indicate that visual disinformation, presumably shared to inflame sectarian tensions during the parade, was quickly debunked in information flows co-curated by citizens and professional journalists. Online misinformation and disinformation appeared to have minimal impact on events on the ground, although there was some evidence of belief echoes among tweeters who distrusted the information provided by mainstream media.

The impact of the information factor on modern international relations

2021 ◽  
Vol 62 (01) ◽  
pp. 141-146
Author(s):  
Gulnaz Tahir Hasanova ◽  
Keyword(s):  
International Relations ◽  
Outer Space ◽  
Cyber Attacks ◽  
The Internet ◽  
Information Warfare ◽  
Fake News ◽  
False Information ◽  
Fifth Dimension ◽  
Private Actors ◽  
The Impact

This study aims to highlight the growing strategic importance that cyberspace is gaining in the dynamics of international politics. After land, sea, air, and outer space, cyberspace is the fifth dimension of conflict. The type of non-military weapons used to fight, as well as the subjects targeted, make civilian systems new centers of gravity to defend against an enemy that most often "operates in the shadows." The international scenario rmation revolution (which contributed to the "democratization of information"), is radically evolving from a unipolar (American-led) to an almost multipolar architecture. The Internet today is an indispensable communication and information network for various legal and illegal subjects of international relations. Social networks (Facebook, Twitter, Telegram) play a very important role in this process. The Internet can also allow manipulation or even destabilization of the international community with the spread of false information (fake news). It is also a field for intelligence activities. Finally, the Internet is becoming the field of a new form of confrontation. Thus, both states and private actors protect themselves from possible cyber attacks by developing cybersecurity. In anticipation of this, states are developing cyberspace strategies and military-digital capabilities. Key words: international relations, information, cyberspace, cybersecurity, territorial integrity, state, subjects of international relations, information warfare

Fake News and Information Warfare

2019 ◽  
pp. 167-191 ◽  
Author(s):  
Rosanna E. Guadagno ◽  
Karen Guttieri
Keyword(s):  
Presidential Election ◽  
Information Age ◽  
Psychological Research ◽  
Individual Factors ◽  
Cyber Warfare ◽  
Information Warfare ◽  
Fake News ◽  
False Information ◽  
Russian Government ◽  
Key Terms

Fake news—false information passed off as factual—is an effective weapon in the information age. For instance, the Russian government perfected techniques used in its 2007 Estonian and 2008 Georgian cyber campaigns to support Donald Trump's successful candidacy in the 2016 United States presidential election. In this chapter, the authors examine fake news and Russia's cyberwarfare efforts across time as case studies of information warfare. The chapter identifies key terms and reviews extant political science and psychological research related to obtaining an understanding of psychological cyber warfare (“psywar”) through the proliferation of fake news. Specifically, the authors suggest that there are social, contextual, and individual factors that contribute to the spread and influence of fake news and review these factors in this chapter.

Fake News and Information Warfare

2021 ◽  
pp. 218-242
Author(s):  
Rosanna E. Guadagno ◽  
Karen Guttieri
Keyword(s):  
Presidential Election ◽  
Information Age ◽  
Psychological Research ◽  
Individual Factors ◽  
Cyber Warfare ◽  
Information Warfare ◽  
Fake News ◽  
False Information ◽  
Russian Government ◽  
Key Terms

Fake news—false information passed off as factual—is an effective weapon in the information age. For instance, the Russian government perfected techniques used in its 2007 Estonian and 2008 Georgian cyber campaigns to support Donald Trump's successful candidacy in the 2016 United States presidential election. In this chapter, the authors examine fake news and Russia's cyberwarfare efforts across time as case studies of information warfare. The chapter identifies key terms and reviews extant political science and psychological research related to obtaining an understanding of psychological cyber warfare (“psywar”) through the proliferation of fake news. Specifically, the authors suggest that there are social, contextual, and individual factors that contribute to the spread and influence of fake news and review these factors in this chapter.

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