Echoes of covid misinformation

Public support for responses to the coronavirus pandemic has sharply diverged on partisan lines in many countries, with conservatives tending to oppose lockdowns, social distancing, mask mandates and vaccines, and liberals far more supportive. This polarization may arise from the way in which the attitudes of each side is echoed back to them, especially on social media. In this paper, I argue that echo chambers are not to blame for this polarization, even if they are causally responsible for it. They are not to blame, because belief calibration in an echo chamber is a rational process;moreover, the epistemically constitutive properties of echo chambers are not optional for epistemically social animals like us. There is no special problem of echo chambers;rather, there is a problem of misleading evidence (especially higher-order evidence). Accordingly, we ought to respond to misinformation about COVID neither by attempting to dismantle echo chambers nor by attempting to make people more rational, but rather by attempting to supplant unreliable higher-order evidence with better evidence.

Exploring the impact of social media exposure patterns on people?s belief in fake news during COVID-19: A cross-gender study

During COVID-19, fake news on social media seriously threatened public health. As a solution to this problem, this study examined how social media exposure patterns affect people being deeply harmed by fake news. Based on cognitive dissonance theory, this study investigated the effect of intentional and incidental exposure on belief in fake news through the mediating role of confirmation bias. The results show that intentional exposure positively influences confirmation bias and belief in fake news. Incidental exposure is the opposite. Our results also show that intentional exposure and confirmation bias negatively influence incidental exposure. Furthermore, these relationships remain unchanged by gender. This study provides theoretical and empirical contributions to reducing people's belief in fake news.

The Metaverse as a virtual form of data-driven smart cities: the ethics of the hyper-connectivity, datafication, algorithmization, and platformization of urban society.

Recent advances in computing and immersive technologies have provided Meta (formerly Facebook) with the opportunity to leapfrog or expedite its way of thinking and devising a global computing platform called the "Metaverse". This hypothetical 3D network of virtual spaces is increasingly shaping alternatives to the imaginaries of data-driven smart cities, as it represents ways of living in virtually inhabitable cities. At the heart of the Metaverse is a computational understanding of human users' cognition, emotion, motivation, and behavior that reduces the experience of everyday life to logic and calculative rules and procedures. This implies that human users become more knowable and manageable and their behavior more predictable and controllable, thereby serving as passive data points feeding the AI and analytics system that they have no interchange with or influence on. This paper examines the forms, practices, and ethics of the Metaverse as a virtual form of data-driven smart cities, paying particular attention to: privacy, surveillance capitalism, dataveillance, geosurveillance, human health and wellness, and collective and cognitive echo-chambers. Achieving this aim will provide the answer to the main research question driving this study: What ethical implications will the Metaverse have on the experience of everyday life in post-pandemic urban society? In terms of methodology, this paper deploys a thorough review of the current status of the Metaverse, urban informatics, urban science, and data-driven smart cities literature, as well as trends, research, and developments. We argue that the Metaverse will do more harm than good to human users due to the massive misuse of the hyper-connectivity, datafication, algorithmization, and platformization underlying the associated global architecture of computer mediation. It follows that the Metaverse needs to be re-cast in ways that re-orientate in how users are conceived; recognize their human characteristics; and take into account the moral values and principles designed to realize the benefits of socially disruptive technologies while mitigating their pernicious effects. This paper contributes to the academic debates in the emerging field of data-driven smart urbanism by highlighting the ethical implications posed by the Metaverse as speculative fiction that illustrates the concerns raised by the pervasive and massive use of advanced technologies in data-driven smart cities. In doing so, it seeks to aid policy-makers in better understanding the pitfalls of the Metaverse and their repercussions upon the wellbeing of human users and the core values of urban society. It also stimulates prospective research and further critical perspectives on this timely topic.

Exploring the echo chamber concept A linguistic perspective

Echo chambers have often been analyzed in social media studies as dysfunctions of communication fostering the polarization of debates and the spreading of conspiracy theories. On the other hand, from a linguistic perspective, very little research has been conducted on these themes. Our work aims to investigate the linguistic dimension of echo chambers, exploring them as ideological structures that are observable when ideological conflict occurs. Using word embedding and corpus-based discourse analysis, we investigate mediatic discourse on COVID-19 in the Coronavirus Corpus and in the Public Coronavirus Twitter Data Set. The analysis focuses on the semantic and pragmatic status of the word hoax, which emerges as a keyword characterizing the Twitter dataset. Our study shows how linguistic markers of ideological conflict can act as markers of position and affective/social identity. © 2022 John Benjamins Publishing Company.

Truth in an Age of Information

Many of the issues in the modern world are complex and multifaceted: migration, banking, not to mention climate change and Covid. Furthermore, social-media, which at first seemed to offer more reliable 'on the ground' citizen journalism, has instead become a seedbed of dis-information. Trust in media has plummeted, just when it has become essential. This is a problem, but also an opportunity for research in HCI that can make a real difference in the world. The majority of work in this area, from various disciplines including datascience, AI and HCI, is focused on combatting misinformation - fighting back against bad actors. However, we should also think about doing better - helping good actors to curate, disseminate and comprehend information better. There is exciting work in this area, but much still to do. Copyright © 2022 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

Cascade-based Echo Chamber Detection

Despite echo chambers in social media have been under considerable scrutiny, general models for their detection and analysis are missing. In this work, we aim to fill this gap by proposing a probabilistic generative model that explains social media footprints - -i.e., social network structure and propagations of information - -through a set of latent communities, characterized by a degree of echo-chamber behavior and by an opinion polarity. Specifically, echo chambers are modeled as communities that are permeable to pieces of information with similar ideological polarity, and impermeable to information of opposed leaning: this allows discriminating echo chambers from communities that lack a clear ideological alignment. To learn the model parameters we propose a scalable, stochastic adaptation of the Generalized Expectation Maximization algorithm, that optimizes the joint likelihood of observing social connections and information propagation. Experiments on synthetic data show that our algorithm is able to correctly reconstruct ground-truth latent communities with their degree of echo-chamber behavior and opinion polarity. Experiments on real-world data about polarized social and political debates, such as the Brexit referendum or the COVID-19 vaccine campaign, confirm the effectiveness of our proposal in detecting echo chambers. Finally, we show how our model can improve accuracy in auxiliary predictive tasks, such as stance detection and prediction of future propagations. © 2022 ACM.

State vs. anti-vaxxers: Analysis of Covid-19 echo chambers in Serbia

Times of uncertainty and fear were brought on by Covid-19. The ongoing pandemic is a fruitful ground for fake news, as citizens try to find explanations that fit into their worldviews. This process polarizes society and creates echo chambers amplified by recommender systems. Our main goal is to detect anti-vaxxer echo chambers in Serbia by analyzing online reactions to the recent detention of prominent anti-vaxxer Dr. Jovana Stojkovic. A content analysis of online comments is deployed in anti-regime left-leaning, anti-regime right-leaning, and pro-government media to explore attitudes towards a vaccination conspiracy theory, police action towards anti-vaxxers, and the government crisis response team. We clearly identify the anti-vaccine echo chamber among commentators of anti-regime right-leaning media (YouTube podcasts). Additionally, we describe attitudes expressed around issues related to vaccination. Limitations and implications for future research are discussed.

A Confirmation Bias View on Social Media Induced Polarisation During Covid-19.

Social media has played a pivotal role in polarising views on politics, climate change, and more recently, the Covid-19 pandemic. Social media induced polarisation (SMIP) poses serious challenges to society as it could enable 'digital wildfires' that can wreak havoc worldwide. While the effects of SMIP have been extensively studied, there is limited understanding of the interplay between two key components of this phenomenon: confirmation bias (reinforcing one's attitudes and beliefs) and echo chambers (i.e., hear their own voice). This paper addresses this knowledge deficit by exploring how manifestations of confirmation bias contributed to the development of 'echo chambers' at the height of the Covid-19 pandemic. Thematic analysis of data collected from 35 participants involved in supply chain information processing forms the basis of a conceptual model of SMIP and four key cross-cutting propositions emerging from the data that have implications for research and practice.

Epistemic Responsibility, Rights, and Duties During the Covid-19 Pandemic

We start by introducing the idea of echo chambers. Echo chambers are social and epistemic structures in which opinions, leanings, or beliefs about certain topics are amplified and reinforced due to repeated interactions within a closed system;that is, within a system that has a rather homogeneous sample of sources or people, which all share the same attitudes towards the topics in question. Echo chambers are a particularly dangerous phenomena because they prevent the critical assessment of sources and contents, thus leading the people living within them to deliberately ignore or exclude opposing views. In the second part of this paper, we argue that the reason for the appearance of echo chambers lies in the adoption of what we call ‘epistemic vices’. We examine which vices might be responsible for their emergence, and in doing so, we focus on a specific one;‘epistemic violence’. In assessing and evaluating the role of this epistemic vice, we note that it can be triggered by epistemic contexts characterized by high stakes that may turn ordinary intellectual virtues (such as skepticism) into vices (such as denialism). In the third part of this contribution, we suggest a way to deal with echo chambers. The solution focuses on advocating a responsibilist pedagogy of virtues and vices that -we claim- might be capable of preventing their emergence. [ FROM AUTHOR] Copyright of Social Epistemology is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Comparing the Impact of Social Media Regulations on News Consumption

Users online tend to consume information adhering to their system of beliefs and ignore dissenting information. During the COVID-19 pandemic, users get exposed to a massive amount of information about a new topic having a high level of uncertainty. In this article, we analyze two social media that enforced opposite moderation methods, Twitter and Gab, to assess the interplay between news consumption and content regulation concerning COVID-19. We compare the two platforms on about three million pieces of content, analyzing user interaction with respect to news articles. We first describe users' consumption patterns on the two platforms focusing on the political leaning of news outlets. Finally, we characterize the echo chamber effect by modeling the dynamics of users' interaction networks. Our results show that the presence of moderation pursued by Twitter produces a significant reduction of questionable content, with a consequent affiliation toward reliable sources in terms of engagement and comments. Conversely, the lack of clear regulation on Gab results in the tendency of the user to engage with both types of content, showing a slight preference for the questionable ones which may account for a dissing/endorsement behavior. Twitter users show segregation toward reliable content with a uniform narrative. Gab, instead, offers a more heterogeneous structure where users, independent of their leaning, follow people who are slightly polarized toward questionable news.

Reading between the lies: A classification scheme of types of reply to misinformation in public discussion threads

Online misinformation is a fiendish problem. Demonstrably false information propagates faster and more widely than truth and this has heralded a technological arms race. One possible mechanism for addressing misinformation is social: there is evidence seeing misinformation being challenged can ginoculate' a reader against it. To date, no research has examined how discussions sparked by misinformation play out;What are the different ways in which people reply to posts containing misinformation? How does the discussion flow in each case? Are there differences between platforms? We address these questions through an inductive qualitative analysis of discussion threads on three public discussion platforms (Twitter, YouTube and two news sites) and on three topics (COVID, Brexit and climate change). We present a classification scheme of types of replies to misinformation, and show that replies show different patterns between platforms. Knowing how people reply to posts that contain misinformation enriches our knowledge of ghuman misinformation interaction,' and provides an understanding of how socio-technical factors in platform design can reduce the risk of misinformation spreading. © 2022 ACM.

Civility, Trust, and Responding to Echo Chambers

Due to the rampant epistemic distrust present in echo chamber members towards outsiders, responding to echo chambers with civil debate is unlikely to lead to any agreement or compromise. Moreover, a civil response may contribute to the echo chamber's inflated sense of epistemic status, which is precisely what needs to be dismantled or diminished if agreement/compromise is to be made possible. When responding to particularly dangerous and resistant echo chambers, a moderately uncivil response may be warranted.

Echo chamber detection and analysis: A topology- and content-based approach in the COVID-19 scenario.

Social media allow to fulfill perceived social needs such as connecting with friends or other individuals with similar interests into virtual communities; they have also become essential as news sources, microblogging platforms, in particular, in a variety of contexts including that of health. However, due to the homophily property and selective exposure to information, social media have the tendency to create distinct groups of individuals whose ideas are highly polarized around certain topics. In these groups, a.k.a. echo chambers, people only "hear their own voice," and divergent visions are no longer taken into account. This article focuses on the study of the echo chamber phenomenon in the context of the COVID-19 pandemic, by considering both the relationships connecting individuals and semantic aspects related to the content they share over Twitter. To this aim, we propose an approach based on the application of a community detection strategy to distinct topology- and content-aware representations of the COVID-19 conversation graph. Then, we assess and analyze the controversy and homogeneity among the different polarized groups obtained. The evaluations of the approach are carried out on a dataset of tweets related to COVID-19 collected between January and March 2020.