scholarly journals Intentional or inadvertent fake news sharing? Fact-checking warnings and users’ interaction with social media content

2020 ◽  
Author(s):  
Alberto Ardèvol-Abreu ◽  
Patricia Delponti ◽  
Carmen Rodríguez-Wangüemert
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Media Content ◽  
Fake News ◽  
Negative Effects ◽  
News Stories ◽  
Social Media Platforms ◽  
Fact Checking ◽  
False News ◽  
News Sharing

The main social media platforms have been implementing strategies to minimize fake news dissemination. These include identifying, labeling, and penalizing –via news feed ranking algorithms– fake publications. Part of the rationale behind this approach is that the negative effects of fake content arise only when social media users are deceived. Once debunked, fake posts and news stories should therefore become harmless. Unfortunately, the literature shows that the effects of misinformation are more complex and tend to persist and even backfire after correction. Furthermore, we still do not know much about how social media users evaluate content that has been fact-checked and flagged as false. More worryingly, previous findings suggest that some people may intentionally share made up news on social media, although their motivations are not fully explained. To better understand users’ interaction with social media content identified or recognized as false, we analyze qualitative and quantitative data from five focus groups and a sub-national online survey (N = 350). Findings suggest that the label of ‘false news’ plays a role –although not necessarily central– in social media users’ evaluation of the content and their decision (not) to share it. Some participants showed distrust in fact-checkers and lack of knowledge about the fact-checking process. We also found that fake news sharing is a two-dimensional phenomenon that includes intentional and unintentional behaviors. We discuss some of the reasons why some of social media users may choose to distribute fake news content intentionally.

Spiritualism and the Resurgence of Fake News

2020 ◽  
pp. 222-237
Author(s):  
Kristy A. Hesketh
Keyword(s):  
Social Media ◽  
Mass Media ◽  
Fake News ◽  
News Stories ◽  
News Reports ◽  
The World ◽  
Spirit World ◽  
Social Media Platforms ◽  
Media Platform ◽  
False News

This chapter explores the Spiritualist movement and its rapid growth due to the formation of mass media and compares these events with the current rise of fake news in the mass media. The technology of cheaper publications created a media platform that featured stories about Spiritualist mediums and communications with the spirit world. These articles were published in newspapers next to regular news creating a blurred line between real and hoax news stories. Laws were later created to address instances of fraud that occurred in the medium industry. Today, social media platforms provide a similar vessel for the spread of fake news. Online fake news is published alongside legitimate news reports leaving readers unable to differentiate between real and fake articles. Around the world countries are actioning initiatives to address the proliferation of false news to prevent the spread of misinformation. This chapter compares the parallels between these events, how hoaxes and fake news begin and spread, and examines the measures governments are taking to curb the growth of misinformation.

scholarly journals Social Media and Fake News in the 2016 Election

2017 ◽  
Vol 31 (2) ◽  
pp. 211-236 ◽  
Author(s):  
Hunt Allcott ◽  
Matthew Gentzkow
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Fake News ◽  
News Stories ◽  
Social Media Networks ◽  
Data Archives ◽  
American Adult ◽  
2016 Election ◽  
False News ◽  
Election News

Following the 2016 US presidential election, many have expressed concern about the effects of false stories (“fake news”), circulated largely through social media. We discuss the economics of fake news and present new data on its consumption prior to the election. Drawing on web browsing data, archives of fact-checking websites, and results from a new online survey, we find: 1) social media was an important but not dominant source of election news, with 14 percent of Americans calling social media their “most important” source; 2) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared 8 million times; 3) the average American adult saw on the order of one or perhaps several fake news stories in the months around the election, with just over half of those who recalled seeing them believing them; and 4) people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks.

scholarly journals Trends in the diffusion of misinformation on social media

2019 ◽  
Vol 6 (2) ◽  
pp. 205316801984855 ◽  
Author(s):  
Hunt Allcott ◽  
Matthew Gentzkow ◽  
Chuan Yu
Keyword(s):  
Social Media ◽  
Relative Magnitude ◽  
Democratic Institutions ◽  
Fake News ◽  
User Interactions ◽  
News Stories ◽  
News Websites ◽  
Social Media Platforms

In recent years, there has been widespread concern that misinformation on social media is damaging societies and democratic institutions. In response, social media platforms have announced actions to limit the spread of false content. We measure trends in the diffusion of content from 569 fake news websites and 9540 fake news stories on Facebook and Twitter between January 2015 and July 2018. User interactions with false content rose steadily on both Facebook and Twitter through the end of 2016. Since then, however, interactions with false content have fallen sharply on Facebook while continuing to rise on Twitter, with the ratio of Facebook engagements to Twitter shares decreasing by 60%. In comparison, interactions with other news, business, or culture sites have followed similar trends on both platforms. Our results suggest that the relative magnitude of the misinformation problem on Facebook has declined since its peak.

scholarly journals Designing Granoolars Brand Promotion with Social Media Mix Approach as A Brand Awareness Strategy

2021 ◽  
Vol 1 (7) ◽  
pp. 857-874
Author(s):  
Aura Nebula Safinatunnajah ◽  
Pujiyanto ◽  
Joni Agung Sudarmanto
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Design Principle ◽  
Distribution Channel ◽  
Brand Awareness ◽  
Media Content ◽  
Social Media Platforms ◽  
Transformation Stage ◽  
Brand Promotion ◽  
Media Mix

Abstract: Granoolars is a newly established business in the food industry that needs more brand awareness from the target consumers. Promotional content is one of the approaches to reach the audience for recognition. Since the consumer is the value co-creator, a thorough investigation was highlighted on the characteristics that the targeted consumer seeks in an ad, both the verbal and visual aspects. Moreover, the distribution channel of social media that the respondents mostly use was also discussed. The purpose of this study was to comprehend and design the promotional content which the audience approves. The design process uses Matt Cooke methodology which consists of definition, divergence, and transformation stage. The study is a quantitative method using an online survey on 300 respondents. The SPSS data analysis was used for the descriptive statistics analysis. The findings proposed that the respondents prefer marketing content that has the ad value of credibility and informativeness. Moreover, visual of the content that implemented a strong design principle is favorable for the audience of this study. The distribution funnel being adopted are Instagram and Twitter as the most used social media platforms by the respondents. Keywords: brand promotion, social media content, brand awareness Abstrak: Granoolars adalah bisnis yang baru didirikan di industri makanan yang membutuhkan lebih banyak kesadaran merek dari target konsumennya. Konten promosi adalah salah satu pendekatan untuk menjangkau audiens untuk mendapatkan pengakuan merk. Sebab konsumen adalah value co-creator, penyelidikan menyeluruh difokuskan pada karakteristik yang dicari target konsumen dalam sebuah iklan, baik aspek verbal maupun visual. Selain itu, saluran distribusi media sosial yang paling banyak digunakan responden juga dibahas. Tujuan dari penelitian ini adalah untuk memahami dan merancang konten promosi yang disukai audiens. Proses perancangan menggunakan metodologi Matt Cooke yang terdiri dari tahap definisi, divergensi, dan transformasi. Penelitian ini menggunakan metode kuantitatif dengan menggunakan survei online terhadap 300 responden. Analisis data SPSS digunakan untuk analisis statistic deskriptif. Hasil penelitian menunjukkan bahwa responden lebih menyukai konten pemasaran yang memiliki nilai iklan kredibilitas dan keinformatifan. Selain itu, visual konten yang menerapkan prinsip desain yang kuat sangat disukai oleh audiens penelitian ini. Corong distribusi yang diadopsi adalah Instagram dan Twitter sebagai platform media sosial yang paling banyak digunakan oleh responden. Kata kunci: promosi brand, konten media sosial, kesadaran merek

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.

Survey on Fake News or Truth - Rumours Detection using Machine Learning

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Kalyani Deore ◽  
Leena Gaikwad ◽  
Rohit Dhamne ◽  
Vishal Agale ◽  
T. Bhaskar
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Machine Learning Algorithms ◽  
Modern World ◽  
Fake News ◽  
Misleading Information ◽  
Original Source ◽  
News Stories ◽  
False News ◽  
Communication Methods

This study is to help readers to understand detection of fake news using machine learning. The main purpose of the planned system is to build an application which identifies fake news stories from a bunch of news stories to make people aware of fake news rumours. With the help of machine learning algorithms, we can detect and separate out the fake news. Nowadays, it is become harder to identify the original source of news stories, like looking for a needle in a haystack. In the modern world, news is a kind of communication that keeps us up to date on the latest events, topics, and people in the wider globe. A society relies on news for a variety of reasons, the most important of which is informing its members about events taking on in and around them that might influence them. Oral and traditional media, as well as digital communication methods, altered videos, memes, unconfirmed marketing, and social media have all contributed to the spread of rumors. As nowadays many people use social media in many cases people get wrong and misleading information and people share those stories without verifying whether it is real or fake news stories. Spreading false information on social media has become a major problem these days. That is why we need a system that can tell us whether something is false news or not. Applications are: 1. Fake news may be detected on social media using this approach. 2. The system can be used to help news channels to broadcast only real and classified news. 3. Users can easily detect and eliminate fake articles that contain misinformation intended to mislead readers.

Detecting Fake News on Social Media

2021 ◽  
pp. 49-67
Author(s):  
Esra Bozkanat
Keyword(s):  
Social Media ◽  
The Internet ◽  
Control Mechanisms ◽  
Fake News ◽  
Media Type ◽  
Lack Of Control ◽  
Fact Checking ◽  
False News ◽  
The Impact ◽  
Interactive Medium

As Web 2.0 technologies have turned the Internet into an interactive medium, users dominate the field. With the spread of social media, the Internet has become much more user-oriented. In contrast to traditional media, social media's lack of control mechanisms makes the accuracy of spreading news questionable. This brings us to the significance of fact-checking platforms. This study investigates the antecedents of spreading false news in Turkey. The purpose of the study is to determine the features of fake news. For this purpose, teyit.org, the biggest fact-checking platform in Turkey, has been chosen for analysis. The current study shows fake news to be detectable based on four features: Propagation, User Type, Social Media Type, and Formatting. According to the logistic regression analysis, the study's model obtained 86.7% accuracy. The study demonstrates that Facebook increases the likelihood of news being fake compared to Twitter or Instagram. Emoji usage is also statistically significant in terms of increasing the probability of fake news. Unexpectedly, the impact of photos or videos was found statistically insignificant.

Deep learning analysis of social media content used by Bahraini women: WhatsApp in focus

2020 ◽  
pp. 135485652096691
Author(s):  
Mokhtar Elareshi ◽  
Abdul-Karim Ziani ◽  
Ahmad Al Shami
Keyword(s):  
Social Media ◽  
Deep Learning ◽  
Mobile Communication ◽  
Online Survey ◽  
Media Content ◽  
Learning Approach ◽  
News Stories ◽  
Mining Technique ◽  
Learning Analysis ◽  
Share Information

This article examines perceptions of social media use (e.g. the WhatsApp application), in particular looking at how Bahraini women use such technology and how mobile communication is used by such a segment of the population. Mobile devices are very accessible to Bahraini women and this needs even further study to learn ways of using applications for information and other things. This analysis is based on an online survey, conducted among 1137 Bahraini women, using a nonrepresentative sample (snowball). Such data were analyzed using a deep learning approach which utilizes, in particular, the Fuzzy Proximity Knowledge Mining technique to examine the provided answers. The study found that WhatsApp has enabled Bahraini women to communicate and share information with others. They spent 2–3 h daily sending and enjoying comics and entertainment clips and important and rare news stories. Social interaction, communication, and escapism featured strongly as the most popular reasons for using WhatsApp. Overall, WhatsApp served as a platform used to participate in social and communication activities.

scholarly journals Moderating with the Mob: Evaluating the Efficacy of Real-Time Crowdsourced Fact-Checking

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
William Godel ◽  
Zeve Sanderson ◽  
Kevin Aslett ◽  
Jonathan Nagler ◽  
Richard Bonneau ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Significant Variation ◽  
Political Knowledge ◽  
Third Party ◽  
News Stories ◽  
Social Media Platforms ◽  
Fact Checking ◽  
False News ◽  
Wisdom Of The Crowds

Reducing the spread of false news remains a challenge for social media platforms, as the current strategy of using third-party fact- checkers lacks the capacity to address both the scale and speed of misinformation diffusion. Research on the “wisdom of the crowds” suggests one possible solution: aggregating the evaluations of ordinary users to assess the veracity of information. In this study, we investigate the effectiveness of a scalable model for real-time crowdsourced fact-checking. We select 135 popular news stories and have them evaluated by both ordinary individuals and professional fact-checkers within 72 hours of publication, producing 12,883 individual evaluations. Although we find that machine learning-based models using the crowd perform better at identifying false news than simple aggregation rules, our results suggest that neither approach is able to perform at the level of professional fact-checkers. Additionally, both methods perform best when using evaluations only from survey respondents with high political knowledge, suggesting reason for caution for crowdsourced models that rely on a representative sample of the population. Overall, our analyses reveal that while crowd-based systems provide some information on news quality, they are nonetheless limited—and have significant variation—in their ability to identify false news.

scholarly journals Level of Acceptance of News Stories on Social Media Platforms Among Youth in Nigeria

2021 ◽  
Vol 37 (2) ◽  
pp. 210-225
Author(s):  
Festus Prosper Olise ◽  
Keyword(s):  
Social Media ◽  
Sampling Technique ◽  
Fake News ◽  
Mainstream Media ◽  
News Stories ◽  
Multi Stage ◽  
States Data ◽  
Social Media Platforms ◽  
Media Platform ◽  
And Gender

This study investigates the level of acceptance of news stories on social media platforms among youth in Nigeria following the assumption that the proliferation of news stories on social media promotes the circulation of both factual and fake news. The sample consisted of 600 youth; however, 583 validly participated in the study. The participants were equitably selected in six States in Nigeria that represented the six geo-political zones of the country. The multi-stage sampling technique was employed to evenly select the youth from the major cities/towns in the States. Data generated were analysed and presented through descriptive and inferential statistics using SPSS version 20 software. Results show that the youth accepted entertainment news stories more than any other type of news stories on social media platforms. The majority of the youth considered Twitter as the most acceptable social media platform for receiving news stories in Nigeria. Findings also revealed that despite their love to read news stories on social media platforms, the youth’s level of acceptance of it was low. Furthermore, the age and gender of the youth were found to directly influence their level of acceptance of news stories on social media platforms. The study concluded that the multi-dimensional inter-play that characterised the low level of acceptance of news stories on social media platforms among the youth in Nigeria does not portend ominous signs. Keywords: Acceptance, mainstream media, news stories, social media platforms, youth.

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