Fake News Finds an Audience

2019 ◽  
pp. 201-222
Author(s):  
Erik P. Bucy ◽  
John E. Newhagen
Keyword(s):  
Social Media ◽  
Big Data ◽  
Information Processing ◽  
Educational Strategy ◽  
Fake News ◽  
False Information ◽  
User Experiences ◽  
The Social ◽  
Social Media Platforms ◽  
Media Systems

The vulnerabilities shown by media systems and individual users exposed to attacks on truth from fake news and computational propaganda in recent years should be considered in light of the characteristics and concerns surrounding big data, especially the volume and velocity of messages delivered over social media platforms that tax the average user’s capacity to determine their truth value in real time. For reasons explained by the psychology of information processing, a high percentage of fake news that reaches audiences is accepted as true, particularly when distractions and interruptions typify user experiences with technology. As explained in this essay, fake news thrives in environments lacking editorial policing and epistemological vigilance, making the social media milieu ideally suited for spreading false information. In response, we suggest the value of an educational strategy to combat the dilemma that digital disinformation poses to informed citizenship.

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.

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>

scholarly journals Conspiracy beliefs and vaccination intent for COVID-19 in an infodemic

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0261559
Author(s):  
Ali Ghaddar ◽  
Sanaa Khandaqji ◽  
Zeinab Awad ◽  
Rawad Kansoun
Keyword(s):  
Social Media ◽  
Cross Sectional Study ◽  
Fake News ◽  
Sources Of Information ◽  
Cross Sectional ◽  
Viral Spread ◽  
The Social ◽  
Conspiracy Beliefs ◽  
Social Media Platforms ◽  
Guidelines And Recommendations

Background The massive, free and unrestricted exchange of information on the social media during the Covid-19 pandemic has set fertile grounds for fear, uncertainty and the rise of fake news related to the virus. This “viral” spread of fake news created an “infodemic” that threatened the compliance with public health guidelines and recommendations. Objective This study aims to describe the trust in social media platforms and the exposure to fake news about COVID-19 in Lebanon and to explore their association with vaccination intent. Methods In this cross-sectional study conducted in Lebanon during July–August, 2020, a random sample of 1052 participants selected from a mobile-phone database responded to an anonymous structured questionnaire after obtaining informed consent (response rate = 40%). The questionnaire was conducted by telephone and measured socio-demographics, sources and trust in sources of information and exposure to fake news, social media activity, perceived threat and vaccination intent. Results Results indicated that the majority of participants (82%) believed that COVID-19 is a threat and 52% had intention to vaccinate. Exposure to fake/ unverified news was high (19.7% were often and 63.8% were sometimes exposed, mainly to fake news shared through Watsapp and Facebook). Trust in certain information sources (WHO, MoPH and TV) increased while trust in others (Watsapp, Facebook) reduced vaccination intent against Covid-19. Believing in the man-made theory and the business control theory significantly reduced the likelihood of vaccination intent (Beta = 0.43; p = 0.01 and Beta = -0.29; p = 0.05) respectively. Conclusion In the context of the infodemic, understanding the role of exposure to fake news and of conspiracy believes in shaping healthy behavior is important for increasing vaccination intent and planning adequate response to tackle the Covid-19 pandemic.

Flattening the Curve of Fake News in the Epoch of Infodemic

2021 ◽  
pp. 143-161
Author(s):  
Oluwole Olumide Durodolu ◽  
Collence Takaingenhamo Chisita ◽  
Tinyiko Vivian Dube
Keyword(s):  
Social Media ◽  
Digital Media ◽  
Research Methodology ◽  
Political Stability ◽  
Fake News ◽  
The Social ◽  
Social Media Platforms

Globally, no country has been spared by the spectre of the COVID-19 pandemic and infodemic that continues to wreak havoc on the socio-economic and political stability of governments and communities. The oxymoronic nature of fake news raises many questions with regards to the issues of authenticity because the concept of news is underpinned by verifiability. While fake news lacks variability, it is surprising that its digital imprint on the social media platforms continues to leave indelible marks that will undermine democracy, responsible journalism, and the benefits of the digital media. It is against this background that this chapter seeks to find strategies to flatten the curve of fake news in the epoch of the COVID-19 pandemic and infodemic, an epistemic challenge. The chapter is based on a positivist research methodology that sought to gather views from the study respondents on their epistemic experiences with fake news amidst the COVID-19 pandemic and infodemic. It seeks to gather views to counter the upsurge of fake news amidst the COVID-19 pandemic.

Fake or real news? Understanding the gratifications and personality traits of individuals sharing fake news on social media platforms

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Brinda Sampat ◽  
Sahil Raj
Keyword(s):  
Social Media ◽  
Personality Traits ◽  
Information Sharing ◽  
Fake News ◽  
Content Type ◽  
Social Media Platform ◽  
The Social ◽  
Social Media Platforms ◽  
Media Platform ◽  
News Sharing

Purpose“Fake news” or misinformation sharing using social media sites into public discourse or politics has increased dramatically, over the last few years, especially in the current COVID-19 pandemic causing concern. However, this phenomenon is inadequately researched. This study examines fake news sharing with the lens of stimulus-organism-response (SOR) theory, uses and gratification theory (UGT) and big five personality traits (BFPT) theory to understand the motivations for sharing fake news and the personality traits that do so. The stimuli in the model comprise gratifications (pass time, entertainment, socialization, information sharing and information seeking) and personality traits (agreeableness, conscientiousness, extraversion, openness and neuroticism). The feeling of authenticating or instantly sharing news is the organism leading to sharing fake news, which forms the response in the study.Design/methodology/approachThe conceptual model was tested by the data collected from a sample of 221 social media users in India. The data were analyzed with partial least squares structural equation modeling to determine the effects of UGT and personality traits on fake news sharing. The moderating role of the platform WhatsApp or Facebook was studied.Findings The results suggest that pass time, information sharing and socialization gratifications lead to instant sharing news on social media platforms. Individuals who exhibit extraversion, neuroticism and openness share news on social media platforms instantly. In contrast, agreeableness and conscientiousness personality traits lead to authentication news before sharing on the social media platform.Originality/value This study contributes to social media literature by identifying the user gratifications and personality traits that lead to sharing fake news on social media platforms. Furthermore, the study also sheds light on the moderating influence of the choice of the social media platform for fake news sharing.

Illusions of Empowerment

2012 ◽  
Vol 2 (1) ◽  
pp. 36-51 ◽  
Author(s):  
Corinne Weisgerber
Keyword(s):  
Social Media ◽  
New Media ◽  
The Public ◽  
Media Technologies ◽  
Digital Democracy ◽  
Internet Users ◽  
Attention Economy ◽  
The Social ◽  
Social Media Platforms ◽  
Media Systems

This article calls into question the social media empowerment narrative and the underlying idea that social media platforms are empowering everyday netizens to have their voices heard. The author argues that social media technologies may simply privilege only those Internet users who are new media savvy and have leisure time to participate in the so-called digital democracy. While social media systems might have lowered the entrance threshold for civic engagement, hurdles such as the growing competition in an attention economy, the odds of standing out amidst millions of other individual voices, knowledge of new media technologies required to achieve visibility, and time demands make the social media empowerment vision more difficult to attain than the architects of the empowerment ideology have made the public to believe.

scholarly journals Propaganda through ‘reflexive control’ and the mediated construction of reality

2020 ◽  
pp. 146144482090244
Author(s):  
Christopher Till
Keyword(s):  
Social Media ◽  
Political Action ◽  
The Internet ◽  
Fake News ◽  
Political Reality ◽  
The Social ◽  
Deceptive Advertising ◽  
Social Media Platforms ◽  
Political Intervention ◽  
Psychological Operations

The nature of reality has been a central concern of philosophy and the social sciences, but since the proliferation of social media, psychological operations have taken on greater visibility and significance in political action. ‘Fake news’ and micro-targeted and deceptive advertising in elections and votes has brought the tenuous character of political reality to the fore. The affordances of the Internet, World Wide Web and social media have enabled users to be mobilised to varying degrees of awareness for propaganda and disinformation campaigns both as producers and spreaders of content and as generators of data for profiling and targeting. This article will argue that social media platforms and the broader political economy of the Internet create the possibilities for online interactions and targeting which enable form of political intervention focused on the destabilisation of perceptions of reality and recruit users in the construction of new politically useful realities.

scholarly journals Machine learning-based mathematical modelling for prediction of social media consumer behavior using big data analytics

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Kiran Chaudhary ◽  
Mansaf Alam ◽  
Mabrook S. Al-Rakhami ◽  
Abdu Gumaei
Keyword(s):  
Social Media ◽  
Big Data ◽  
Consumer Behavior ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Process Data ◽  
Social Media Platform ◽  
The Social ◽  
Social Media Platforms ◽  
Media Platform

AbstractSocial media is popular in our society right now. People are using social media platforms to purchase various products. We collected the data from various social media platforms. We analyzed the data for prediction of the consumer behavior on the social media platform. We considered the consumer data from Facebook, Twitter, Linked In and YouTube, Instagram, and Pinterest, etc. There are diverse and high-speed, high volume data which are coming from social media platform, so we used predictive big data analytics. In this paper, we have used the concept of big data technology to process data and analyze it to predict consumer behavior on social media. We have analyzed consumer behavior on social media platforms based on some parameters and criteria. We analyzed the consumer perception, attitude towards the social media platform. To get good quality of result, we pre-process data using various data pre-processing to detect outlier, noises, error, and duplicate record. We developed mathematical modeling using machine learning to predict consumer behavior on the social media platform. This model is a predictive model for predicting consumer behavior on the social media platform. 80% of data are used for training purposes and 20% for testing.

scholarly journals Relevance of Big Data Technologies to and users in Context of Social Networking Applications

2020 ◽  
Vol 8 (6) ◽  
pp. 4182-4186
Keyword(s):  
Social Media ◽  
Big Data ◽  
Social Networking ◽  
Data Storage ◽  
Vital Role ◽  
Research Article ◽  
The Social ◽  
Big Data Technologies ◽  
Social Media Platforms ◽  
Big Data Storage

Unremitting generation of data by various data analytics platforms, ubiquitous ,edge nodes and social networks in the concurrent scenario has shaped the exceptional amount of data in volume, velocity, veracity, variety and value. Exceptional data have made traditional information technology and method unfeasible to cope up amid. This exceptional data has been termed as Big Data. Social media is one of the most important sources of Big Data. social media is a constituent of Big Data. Besides Big Data plays a vital role in moving forward the Social Networking Applications to innovate and enhance the experience of users. Various technologies are factored for Big Data storage, processing and analysis in the context of social networking. This paper investigates these technologies which are being used by social networking applications with their relevance to the end users. The research article provides a relevance computation of various social media platforms. It further summarizes a visualization of the use of the platforms in their contribution to the big data.

scholarly journals MISINFORMATION AND DISINFORMATION DURING COVID-19: THE EFFECTS AND THE RELEVANT LAWS IN MALAYSIA

2020 ◽  
Vol 5 (21) ◽  
pp. 202-209
Author(s):  
Hanis Wahed
Keyword(s):  
Social Media ◽  
Social Situation ◽  
Fake News ◽  
False Information ◽  
Legal Research ◽  
Conspiracy Theories ◽  
The Public ◽  
The Social ◽  
The Future ◽  
Use Of Social Media

Misinformation and disinformation are increasing as fast as the spreading of Coronavirus disease 2019 or Covid-19. Both happen as a result of the use of social media and technologies. The act of spreading fake news, rumors, and conspiracy theories or giving false information is considered an offence under the laws of Malaysia. However, the number of cases that relate to this offence has been increasing especially during the current pandemic. Thus, this article discusses the effects of the offence and the efforts taken in preventing it from happening. The focus is on the laws that are applicable in the situation. The methodology used is socio-legal research that involves analysing the laws that are applicable in the social situation. The article suggests that further research should be carried out on the applicable laws and amendments should be made to the relevant laws in order to combat the commission of the offence in the future. It is hoped that the suggestion will assist the authority to add more measures in combatting the pandemic and for the public to be more cautious of committing misinformation and disinformation.

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