scholarly journals Distortions of political bias in crowdsourced misinformation flagging

2020 ◽  
Vol 17 (167) ◽  
pp. 20200020
Author(s):  
Michele Coscia ◽  
Luca Rossi
Keyword(s):  
Social Media ◽  
News Item ◽  
Real World Data ◽  
Media Environment ◽  
Political Bias ◽  
News Sources ◽  
Online Social Media ◽  
News Source ◽  
Social Media Platforms ◽  
Current Content

Many people view news on social media, yet the production of news items online has come under fire because of the common spreading of misinformation. Social media platforms police their content in various ways. Primarily they rely on crowdsourced ‘flags’: users signal to the platform that a specific news item might be misleading and, if they raise enough of them, the item will be fact-checked. However, real-world data show that the most flagged news sources are also the most popular and—supposedly—reliable ones. In this paper, we show that this phenomenon can be explained by the unreasonable assumptions that current content policing strategies make about how the online social media environment is shaped. The most realistic assumption is that confirmation bias will prevent a user from flagging a news item if they share the same political bias as the news source producing it. We show, via agent-based simulations, that a model reproducing our current understanding of the social media environment will necessarily result in the most neutral and accurate sources receiving most flags.

scholarly journals Fake News Detection on Social Media Using A Natural Language Inference Approach

2020 ◽  
Author(s):  
Amir Bidgoly ◽  
Hossein Amirkhani ◽  
Fariba Sadeghi
Keyword(s):  
Social Media ◽  
Natural Language ◽  
News Item ◽  
Support Vector ◽  
Statistical Features ◽  
Fake News ◽  
K Nearest Neighbors ◽  
News Sources ◽  
Online Social Media ◽  
Embedding Methods

Abstract Fake news detection is a challenging problem in online social media, with considerable social and political impacts. Several methods have already been proposed for the automatic detection of fake news, which are often based on the statistical features of the content or context of news. In this paper, we propose a novel fake news detection method based on Natural Language Inference (NLI) approach. Instead of using only statistical features of the content or context of the news, the proposed method exploits a human-like approach, which is based on inferring veracity using a set of reliable news. In this method, the related and similar news published in reputable news sources are used as auxiliary knowledge to infer the veracity of a given news item. We also collect and publish the first inference-based fake news detection dataset, called FNID, in two formats: the two-class version (FNID-FakeNewsNet) and the six-class version (FNID-LIAR). We use the NLI approach to boost several classical and deep machine learning models including Decision Tree, Naïve Bayes, Random Forest, Logistic Regression, k-Nearest Neighbors, Support Vector Machine, BiGRU, and BiLSTM along with different word embedding methods including Word2vec, GloVe, fastText, and BERT. The experiments show that the proposed method achieves 85.58% and 41.31% accuracies in the FNID-FakeNewsNet and FNID-LIAR datasets, respectively, which are 10.44% and 13.19% respective absolute improvements.

scholarly journals Neutral bots probe political bias on social media

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Wen Chen ◽  
Diogo Pacheco ◽  
Kai-Cheng Yang ◽  
Filippo Menczer
Keyword(s):  
Social Media ◽  
The Political ◽  
User Interactions ◽  
Political Bias ◽  
News Sources ◽  
Political Center ◽  
Social Media Platforms ◽  
Twitter Users ◽  
The Right ◽  
To Receive

AbstractSocial media platforms attempting to curb abuse and misinformation have been accused of political bias. We deploy neutral social bots who start following different news sources on Twitter, and track them to probe distinct biases emerging from platform mechanisms versus user interactions. We find no strong or consistent evidence of political bias in the news feed. Despite this, the news and information to which U.S. Twitter users are exposed depend strongly on the political leaning of their early connections. The interactions of conservative accounts are skewed toward the right, whereas liberal accounts are exposed to moderate content shifting their experience toward the political center. Partisan accounts, especially conservative ones, tend to receive more followers and follow more automated accounts. Conservative accounts also find themselves in denser communities and are exposed to more low-credibility content.

Understanding the Role of Online Media Platforms in Airport Capital Projects and Community Outreach

2021 ◽  
pp. 036119812199347
Author(s):  
Max Z. Li ◽  
Megan S. Ryerson
Keyword(s):  
Social Media ◽  
Best Practices ◽  
Community Outreach ◽  
Capital Projects ◽  
The Public ◽  
Online Social Media ◽  
Social Media Platforms ◽  
Project Phases ◽  
Media Channels ◽  
Common Content

Community outreach and engagement efforts are critical to an airport’s role as an ever-evolving transportation infrastructure and regional economic driver. As online social media platforms continue to grow in both popularity and influence, a new engagement channel between airports and the public is emerging. However, the motivations behind and effectiveness of these social media channels remain unclear. In this work, we address this knowledge gap by better understanding the advantages, impact, and best practices of this newly emerging engagement channel available to airports. Focusing specifically on airport YouTube channels, we first document quantitative viewership metrics, and examine common content characteristics within airport YouTube videos. We then conduct interviews and site visits with relevant airport stakeholders to identify the motivations and workflow behind these videos. Finally, we facilitate sample focus groups designed to survey public perceptions of the effectiveness and value of these videos. From our four project phases, to maximize content effectiveness and community engagement potential, we synthesize the following framework of action items, recommendations, and best practices: (C) Consistency and community; (O) Organizational structure; (M) Momentum; (B) Branding and buy-in; (A) Activity; (T) Two-way engagement; (E) Enthusiasm; and (D) Depth, or as a convenient initialism, our COMBATED framework.

A Survey of Computational Methods for Online Mental State Assessment on Social Media

2021 ◽  
Vol 2 (2) ◽  
pp. 1-31
Author(s):  
Esteban A. Ríssola ◽  
David E. Losada ◽  
Fabio Crestani
Keyword(s):  
Social Media ◽  
Mental Disorders ◽  
Mental State ◽  
Extraction Process ◽  
State Assessment ◽  
Future Research ◽  
Linguistic Markers ◽  
Online Social Media ◽  
Suicide Behaviour ◽  
Social Media Platforms

Mental state assessment by analysing user-generated content is a field that has recently attracted considerable attention. Today, many people are increasingly utilising online social media platforms to share their feelings and moods. This provides a unique opportunity for researchers and health practitioners to proactively identify linguistic markers or patterns that correlate with mental disorders such as depression, schizophrenia or suicide behaviour. This survey describes and reviews the approaches that have been proposed for mental state assessment and identification of disorders using online digital records. The presented studies are organised according to the assessment technology and the feature extraction process conducted. We also present a series of studies which explore different aspects of the language and behaviour of individuals suffering from mental disorders, and discuss various aspects related to the development of experimental frameworks. Furthermore, ethical considerations regarding the treatment of individuals’ data are outlined. The main contributions of this survey are a comprehensive analysis of the proposed approaches for online mental state assessment on social media, a structured categorisation of the methods according to their design principles, lessons learnt over the years and a discussion on possible avenues for future research.

Avenues to News and Diverse News Exposure Online: Comparing Direct Navigation, Social Media, News Aggregators, Search Queries, and Article Hyperlinks

2021 ◽  
pp. 194016122110091
Author(s):  
Magdalena Wojcieszak ◽  
Ericka Menchen-Trevino ◽  
Joao F. F. Goncalves ◽  
Brian Weeks
Keyword(s):  
Social Media ◽  
Search Engines ◽  
Direct Access ◽  
Data Set ◽  
Individual Level ◽  
News Sources ◽  
Internet Users ◽  
News Websites ◽  
The Us ◽  
Social Media Platforms

The online environment dramatically expands the number of ways people can encounter news but there remain questions of whether these abundant opportunities facilitate news exposure diversity. This project examines key questions regarding how internet users arrive at news and what kinds of news they encounter. We account for a multiplicity of avenues to news online, some of which have never been analyzed: (1) direct access to news websites, (2) social networks, (3) news aggregators, (4) search engines, (5) webmail, and (6) hyperlinks in news. We examine the extent to which each avenue promotes news exposure and also exposes users to news sources that are left leaning, right leaning, and centrist. When combined with information on individual political leanings, we show the extent of dissimilar, centrist, or congenial exposure resulting from each avenue. We rely on web browsing history records from 636 social media users in the US paired with survey self-reports, a unique data set that allows us to examine both aggregate and individual-level exposure. Visits to news websites account for about 2 percent of the total number of visits to URLs and are unevenly distributed among users. The most widespread ways of accessing news are search engines and social media platforms (and hyperlinks within news sites once people arrive at news). The two former avenues also increase dissimilar news exposure, compared to accessing news directly, yet direct news access drives the highest proportion of centrist exposure.

scholarly journals Towards nuanced universality: Developing a concept bible for public service online news production

2018 ◽  
Vol 34 (1) ◽  
pp. 74-87
Author(s):  
Jenni Hokka
Keyword(s):  
Social Media ◽  
Digital Media ◽  
Public Service ◽  
Online News ◽  
Ethnographic Study ◽  
General Level ◽  
Audience Segmentation ◽  
News Production ◽  
Media Environment ◽  
Social Media Platforms

With the advent of popular social media platforms, news journalism has been forced to re-evaluate its relation to its audience. This applies also for public service media that increasingly have to prove its utility through audience ratings. This ethnographic study explores a particular project, the development of ‘concept bible’ for the Finnish Broadcasting Company YLE’s online news; it is an attempt to solve these challenges through new journalistic practices. The study introduces the concept of ‘nuanced universality’, which means that audience groups’ different kinds of needs are taken into account on news production in order to strengthen all people’s ability to be part of society. On a more general level, the article claims that despite its commercial origins, audience segmentation can be transformed into a method that helps revise public service media principles into practices suitable for the digital media environment.

scholarly journals Selfies as expressively authentic identity performance

First Monday ◽  
2017 ◽  
Author(s):  
Linh Nguyen ◽  
Kim Barbour
Keyword(s):  
Social Media ◽  
Focus Group ◽  
Theoretical Frameworks ◽  
Self Identity ◽  
Face To Face ◽  
Digital World ◽  
Online Social Media ◽  
Social Media Platforms ◽  
The Individual ◽  
The University

This paper explores whether or not our online social media persona is viewed as authentic. The selfie is a fundamental part of the structure of the online identity for young people in today’s digital world. The relationship between an individual’s self-identity in the physical face-to-face environment was analysed and compared to a carefully constructed, modified virtual representation in a selfie posted on social media platforms. Data was obtained through four focus groups at the University of Adelaide. Two key theoretical frameworks provide a basis for this study: Erving Goffman’s concept of the self as a performance, and Charles Horton Cooley’s concept of the looking glass self. In examining the focus group discussions in light of these two frameworks as well as associated literature, we conclude that the authenticity of the selfie as a way of visualising a social media persona is subjective and dependent on the individual posting a selfie. Ultimately, authenticity involves a degree of subjectivity. It was on this basis that focus group participants argued that selfies could be considered authentic expressions of identity.

Investigating the effects of consistent visual identity on social media

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Harsandaldeep Kaur ◽  
Kanwal Roop Kaur
Keyword(s):  
Social Media ◽  
Online Marketing ◽  
Media Environment ◽  
Content Type ◽  
Visual Identity ◽  
Company Reputation ◽  
Social Media Platforms ◽  
Sphere Of Influence ◽  
The Impact ◽  
Practical Implications

Purpose Although the prominence of social media for companies is widely acknowledged, a close examination of the literature reveals a lack of empirical research pertaining to the effect of consistency specifically on social media. Therefore, the purpose of this paper is to fill the gap in social media communication concerning the effect of consistent visual identity on social media users. Design/methodology/approach The study executed an experiment 2 (corporate visual identity condition) × 2 (organization type) between subjects design to map the effects of consistent visual identity on social media users appreciation of the visual identity, attitude toward the company, reputation and intention to commit to a company on social media. Findings The results of the study indicated the significant effects of consistent visual identity on social media users over the inconsistent conditions of visual identity on all dependent variables. Furthermore, there were insignificant main effects of organization type on general judgment, credibility, distinctiveness and reputation of the company. Practical implications This study presents the effects of consistent visual identity on social media platforms. The research will help marketing academicians, graphic designers and social media practitioners in online marketing by using its practical implications to strategically positioning their corporate brand in a social media environment. Originality/value This study provides novel insights on the impact of consistency on social media users. This is the first study to determine the role of consistent visual identity in the social media environment. It thereby adds to the literature of visual identity by developing the sphere of influence of consistency and its effects toward the user’s attitude.

COVID-19 Vaccine Hesitancy on Social Media: Building a Public Twitter Dataset of Anti-vaccine Content, Vaccine Misinformation and Conspiracies (Preprint)

2021 ◽  
Author(s):  
Goran Muric ◽  
Yusong Wu ◽  
Emilio Ferrara
Keyword(s):  
Social Media ◽  
Data Collection ◽  
Herd Immunity ◽  
Application Programming Interface ◽  
Data Access ◽  
Vaccine Hesitancy ◽  
Global Public Health ◽  
News Sources ◽  
Online Social Media ◽  
Vaccination Campaigns

BACKGROUND False claims about COVID-19 vaccines can undermine public trust in ongoing vaccination campaigns, thus posing a threat to global public health. Misinformation originating from various sources has been spreading online since the beginning of the COVID-19 pandemic. Anti-vaccine activists have also begun to utilize platforms like Twitter to share their views. To properly understand the phenomenon of vaccine hesitancy through the lens of online social media, it is of greatest importance to gather the relevant data. OBJECTIVE In this paper, we describe a dataset of Twitter posts that exhibit a strong anti-vaccine stance. The dataset is made available to the research community via our AvaxTweets dataset GitHub repository. METHODS We started the ongoing data collection on October 18, 2020, leveraging the Twitter streaming application programming interface (API) to follow a set of specific anti-vaccine related keywords. Additionally, we collect the historical tweets of the set of accounts that engaged in spreading anti-vaccination narratives at some point during 2020. RESULTS Since the inception of our collection, we have published two collections: a) a streaming keyword-centered data collection with more than 1.8 million tweets, and b) a historical account-level collection with more than 135 million tweets. In this paper we present descriptive analyses showing the volume of activity over time, geographical distributions, topics, news sources, and inferred accounts’ political leaning. CONCLUSIONS The vaccine-related misinformation on social media may exacerbate the levels of vaccine hesitancy, hampering the progress toward vaccine-induced herd immunity, and potentially increase infections related to new COVID-19 variants. For these reasons, understanding vaccine hesitancy through the lens of social media is of paramount importance. Since data access is the first obstacle to attain that, we publish the dataset that can be used in studying anti-vaccine misinformation on social media and enable a better understanding of vaccine hesitancy.

Effects of Consumers' Social Media Participation on Consumer Behavior

2014 ◽  
pp. 1128-1152
Author(s):  
Ashish Kumar ◽  
Ram Bezawada
Keyword(s):  
Social Media ◽  
Social Media Marketing ◽  
The Internet ◽  
Media Environment ◽  
Digital Revolution ◽  
Digital Era ◽  
Online Social Media ◽  
The People ◽  
Marketing Activities ◽  
Search Marketing

Technological advancements have shaped and reshaped the marketing landscape from time to time. The digital revolution in particular has given rise to a new digital era that has changed this marketing landscape, perhaps permanently. One of the core technologies involved in defining this digital era is the Internet. The Internet has not only empowered the people by creating and disseminating information like never before but also has affected the way we conduct our businesses. Various business usages of the Internet in search engines, email, mobile, and social media have given rise to new ways of conducting marketing activities such as affiliate marketing, display advertisement, email marketing, search marketing, and social media marketing among others. The significance and the relevance of online social media marketing have made this particular digital channel a topical subject of the digital era. The effects of social media have been felt in influencing both seller and buyer behaviors. However, the focus of this chapter is to address two important aspects of consumer behaviors in an online digital social media environment. First, the authors propose a conceptual framework of consumers' social media participation. Second, the chapter discusses how this participation affects consumers' behaviors including their purchases. Finally, the authors present a few econometric challenges associated with modeling consumers' social media participation and quantifying its impact on their behaviors.

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