scholarly journals Infodemic Pathways: Evaluating the Role That Traditional and Social Media Play in Cross-National Information Transfer

2021 ◽  
Vol 3 ◽  
Author(s):  
Aengus Bridgman ◽  
Eric Merkley ◽  
Oleg Zhilin ◽  
Peter John Loewen ◽  
Taylor Owen ◽  
...  
Keyword(s):  
Social Media ◽  
Information Transfer ◽  
Data Set ◽  
Social Media Networks ◽  
Massive Data Set ◽  
Information Spread ◽  
Twitter Users ◽  
Novel Coronavirus ◽  
National Information ◽  
Cross National

The COVID-19 pandemic has occurred alongside a worldwide infodemic where unprecedented levels of misinformation have contributed to widespread misconceptions about the novel coronavirus. Conspiracy theories, poorly sourced medical advice, and information trivializing the virus have ignored national borders and spread quickly. This information spread has occurred despite generally strong preferences for domestic national media and social media networks that tend to be geographically bounded. How, then, is (mis)information crossing borders so rapidly? Using social media and survey data, we evaluate the extent to which consumption and propagation patterns of domestic and international traditional news and social media can help inform theorizing about cross-national information spread. In a detailed case study of Canada, we employ a large multi-wave survey and a massive data set of Canadian Twitter users. We show that the majority of misinformation circulating on Twitter that is shared by Canadian accounts is retweeted from U.S.-based accounts. Moreover, exposure to U.S.-based media outlets is associated with COVID-19 misperceptions and increased exposure to U.S.-based information on Twitter is associated with an increased likelihood to post misinformation. We thus theorize and empirically identify a key globalizing infodemic pathway: disregard for national origin of social media posting.

scholarly journals Corrigendum: Infodemic Pathways: Evaluating the Role that Traditional and Social Media Play in Cross-National Information Transfer

2021 ◽  
Vol 3 ◽  
Author(s):  
Aengus Bridgman ◽  
Eric Merkley ◽  
Oleg Zhilin ◽  
Peter John Loewen ◽  
Taylor Owen ◽  
...  
Keyword(s):  
Social Media ◽  
Information Transfer ◽  
National Information ◽  
Cross National

scholarly journals Twitter, Telepractice, and the COVID-19 Pandemic: A Social Media Content Analysis

2021 ◽  
pp. 1-11
Author(s):  
Kristen Weidner ◽  
Joneen Lowman ◽  
Anne Fleischer ◽  
Kyle Kosik ◽  
Peyton Goodbread ◽  
...  
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Technology Implementation ◽  
Scale Up ◽  
Media Content Analysis ◽  
Data Set ◽  
Implementation Framework ◽  
Health Crisis ◽  
Wide Scale ◽  
Twitter Users

Purpose Telepractice was extensively utilized during the COVID-19 pandemic. Little is known about issues experienced during the wide-scale rollout of a service delivery model that was novel to many. Social media research is a way to unobtrusively analyze public communication, including during a health crisis. We investigated the characteristics of tweets about telepractice through the lens of an established health technology implementation framework. Results can help guide efforts to support and sustain telehealth beyond the pandemic context. Method We retrieved a historical Twitter data set containing tweets about telepractice from the early months of the pandemic. Tweets were analyzed using a concurrent mixed-methods content analysis design informed by the nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework. Results Approximately 2,200 Twitter posts were retrieved, and 820 original tweets were analyzed qualitatively. Volume of tweets about telepractice increased in the early months of the pandemic. The largest group of Twitter users tweeting about telepractice was a group of clinical professionals. Tweet content reflected many, but not all, domains of the NASSS framework. Conclusions Twitter posting about telepractice increased during the pandemic. Although many tweets represented topics expected in technology implementation, some represented phenomena were potentially unique to speech-language pathology. Certain technology implementation topics, notably sustainability, were not found in the data. Implications for future telepractice implementation and further research are discussed.

scholarly journals Incidental Effects of Automated Retweeting: An Exploratory Network Perspective on Bot Activity During Sri Lanka’s Presidential Election in 2015

2017 ◽  
Vol 37 (1) ◽  
pp. 57-65 ◽  
Author(s):  
Chamil Rathnayake ◽  
Wayne Buente
Keyword(s):  
Social Media ◽  
Presidential Election ◽  
Sri Lankan ◽  
Eigenvector Centrality ◽  
Data Set ◽  
Political Processes ◽  
User Expectations ◽  
Twitter Users ◽  
And Behavior

The role of automated or semiautomated social media accounts, commonly known as “bots,” in social and political processes has gained significant scholarly attention. The current body of research discusses how bots can be designed to achieve specific purposes as well as instances of unexpected negative outcomes of such use. We suggest that the interplay between social media affordances and user practices can result in incidental effects from automated agents. We examined a Twitter network data set with 1,782 nodes and 5,640 edges to demonstrate the engagement and outreach of a retweeting bot called Siripalabot that was popular among Sri Lankan Twitter users. The bot served the simple function of retweeting tweets with hashtags #SriLanka and #lk to its follower network. However, the co-use of #Sri Lanka and/or #lk with #PresPollSL, a hashtag used to discuss politics related to Sri Lanka’s presidential election in 2015, resulted in the bot incidentally amplifying the political voice of less engaged actors. The analysis demonstrated that the bot dominated the network in terms of engagement (out-degree) and the ability to connect distant clusters of actors (betweenness centrality) while more traditional actors, such as the main election candidates and news accounts, indicated more prestige (in-degree) and power (eigenvector centrality). We suggest that the study of automated agents should include designer intentions, the design and behavior of automated agents, user expectations, as well as unintended and incidental effects of interaction.

scholarly journals CROWD4EMS: A CROWDSOURCING PLATFORM FOR GATHERING AND GEOLOCATING SOCIAL MEDIA CONTENT IN DISASTER RESPONSE

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 331-340
Author(s):  
A. Ravi Shankar ◽  
J. L. Fernandez-Marquez ◽  
B. Pernici ◽  
G. Scalia ◽  
M. R. Mondardini ◽  
...  
Keyword(s):  
Social Media ◽  
Disaster Response ◽  
Task Force ◽  
Media Content ◽  
Data Set ◽  
Emergency Responders ◽  
Social Media Networks ◽  
Combining Data ◽  
Automatic Methods ◽  
Using Data

<p><strong>Abstract.</strong> Increase in access to mobile phone devices and social media networks has changed the way people report and respond to disasters. Community-driven initiatives such as Stand By Task Force (SBTF) or GISCorps have shown great potential by crowdsourcing the acquisition, analysis, and geolocation of social media data for disaster responders. These initiatives face two main challenges: (1) most of social media content such as photos and videos are not geolocated, thus preventing the information to be used by emergency responders, and (2) they lack tools to manage volunteers contributions and aggregate them in order to ensure high quality and reliable results. This paper illustrates the use of a crowdsourcing platform that combines automatic methods for gathering information from social media and crowdsourcing techniques, in order to manage and aggregate volunteers contributions. High precision geolocation is achieved by combining data mining techniques for estimating the location of photos and videos from social media, and crowdsourcing for the validation and/or improvement of the estimated location. The evaluation of the proposed approach is carried out using data related to the Amatrice Earthquake in 2016, coming from Flickr, Twitter and Youtube. A common data set is analyzed and geolocated by both the volunteers using the proposed platform and a group of experts. Data quality and data reliability is assessed by comparing volunteers versus experts results. Final results are shown in a web map service providing a global view of the information social media provided about the Amatrice Earthquake event.</p>

Renouvellement des formes langagières dans la communication sociale sur Twitter

2021 ◽  
Vol 9788879169776 ◽  
pp. 107-128
Author(s):  
Grégoire Lacaze
Keyword(s):  
Social Media ◽  
News Media ◽  
Political Leaders ◽  
Open Spaces ◽  
Digital Platforms ◽  
Social Media Networks ◽  
The Social ◽  
Geographical Distances ◽  
Twitter Users ◽  
Social Media Network

With the increasing development of social communication on social media networks, new linguistic forms have emerged thanks to the technological devices offered by digital platforms, which can be regarded as open spaces characterised by hypertextuality and polysemioticity. This research aims to analyse the typical features of the social media Twitter which is largely used by news media professionals and by political leaders for their official communication. As a sociotechnical digital communication platform, Twitter proves to be the most appropriate broadcast medium for live news since it tends to reduce social and geographical distances between Twitter users who can interact with each other by sending informal messages. Eventually, Twitter can often be viewed as the first social media network allowing transmedial quotations that circulate on other social networks.

scholarly journals When do party supporters abandon the party leader? The intraparty conflict of the Alternative for Germany

2019 ◽  
pp. 135406881985717
Author(s):  
Kai Jäger
Keyword(s):  
Social Media ◽  
Party Leader ◽  
Opinion Formation ◽  
Data Set ◽  
Organizational Reform ◽  
Social Media Networks ◽  
News Sources ◽  
Leadership Turnover ◽  
Intraparty Conflict ◽  
Alternative For Germany

Drawing on a unique panel data set of supporters of the Alternative for Germany (AfD), the study shows that programmatic differences between supporters of Frauke Petry and Bernd Lucke cannot sufficiently explain the crucial intraparty leadership contest of July 2015. Programmatic differences were minor in 2013 but became pronounced over time. Politically active supporters were disaffected with the old moderate leadership of Bernd Lucke, who pursued an organizational reform to reduce the influence of the rank-and-file. Social media also played a key role for the leadership turnover, as alternative news sources on social media were only politicized by the intraparty opposition. It is conceivable that the structure of social media networks influences opinion formation processes and internal affairs of right-wing populist parties in general, as their supporters tend to have low trust in mainstream news.

scholarly journals When governments spread lies, the fight is against two viruses: A study on the novel coronavirus pandemic in Brazil

2020 ◽  
Author(s):  
Priscila Biancovilli ◽  
Claudia Jurberg
Keyword(s):  
Social Media ◽  
Agenda Setting ◽  
Real Life ◽  
The Novel ◽  
False Information ◽  
Social Media Networks ◽  
The Media ◽  
Fact Checking ◽  
Media Frame ◽  
Novel Coronavirus

AbstractBackgroundOne of the challenges posed by the novel coronavirus pandemic is the infodemic risk, that is, a huge amount of information being published on the topic, along with misinformation and rumours. Around 100 million people in Brazil (50% of the inhabitants) are users of social media networks, and a substantial amount of false information about the disease circulates in these media.ObjectivesIn this study, we examine the agenda-setting, media frame and content of misinformation published on the topic.MethodsWe analysed all pieces of misinformation published by the Brazilian fact-checking service “Agência Lupa”, during six months of 2020. We used content analysis to classify the texts into categories, and three types of rumours were identified: Misleading content; fabricated content; false context.ResultsWe analysed 232 pieces of misinformation. Most were published on Facebook (76%), followed by Whatsapp, with 10% of total cases. Half of the stories (47%) are classified as “real-life”, that is, the focus is on everyday situations, or circumstances involving people. Regarding the type of misinformation, there is a preponderance of fabricated content, with 53% of total, followed by false context (34%) and misleading content (13%). Wrong information was mostly published in text format (47%). We discuss the influence that misinformation can have on the behaviour of the Brazilian population during the pandemic and how the media’s agenda-setting is influenced by false information published on social media.ConclusionsThis study shows that misinformation about COVID-19 in Brazil seem to help establish an agenda-setting in the country, and the media frame is aligned with President Bolsonaro’s political position.

scholarly journals Spatial Analysis of Disinformation in COVID-19 Related Tweets

2020 ◽  
Author(s):  
Amir Masoud Forati ◽  
Rina Ghose
Keyword(s):  
Social Media ◽  
Geographically Weighted Regression ◽  
Disease Incidence ◽  
Spatial Relationship ◽  
County Level ◽  
The Novel ◽  
Management Measures ◽  
The World ◽  
Twitter Users ◽  
Novel Coronavirus

Misinformation can amplify humanity's most significant challenges. As the novel coronavirus spreads across the world, concerns regarding the spreading of misinformation about it and also people downplaying the severity of it are also growing. This article investigates social media activity in May 2020, specifically Twitter, with respect to COVID-19, the themes of tweets, where the discussion is emerging from, disinformation shared about the virus, and its relationship with COVID-19 incidence rate at the state and county level. A geodatabase of all geotagged COVID-19 related tweets was compiled. Multiscale Geographically Weighted Regression was employed to examine the association between social media activity, population, and the spatial variability of disease incidence; our results suggest that MGWR could explain 96.7% of the variations. Moreover, Covid-19 related twitter dataset content analysis reveals a meaningful strong spatial relationship that exists between social media activity and known cases of COVID-19. Discourses analysis was conducted on tweets to index tweets downplaying the Pandemic or disseminating disinformation; the discourses analysis findings suggest that states in where twitter users spread more misinformation and showed more resistance to pandemic management measures in May are experiencing a surge in the number of cases in July.

Renouvellement des formes langagières dans la communication sociale sur Twitter

2021 ◽  
Vol 9788879169776 ◽  
pp. 107-128
Author(s):  
Grégoire Lacaze
Keyword(s):  
Social Media ◽  
News Media ◽  
Political Leaders ◽  
Open Spaces ◽  
Digital Platforms ◽  
Social Media Networks ◽  
The Social ◽  
Geographical Distances ◽  
Twitter Users ◽  
Social Media Network

With the increasing development of social communication on social media networks, new linguistic forms have emerged thanks to the technological devices offered by digital platforms, which can be regarded as open spaces characterised by hypertextuality and polysemioticity. This research aims to analyse the typical features of the social media Twitter which is largely used by news media professionals and by political leaders for their official communication. As a sociotechnical digital communication platform, Twitter proves to be the most appropriate broadcast medium for live news since it tends to reduce social and geographical distances between Twitter users who can interact with each other by sending informal messages. Eventually, Twitter can often be viewed as the first social media network allowing transmedial quotations that circulate on other social networks.

scholarly journals Network Connections and Neighbourhood Perception: Using Social Media Postings to Capture Attitudes among Twitter Users in Estonia

2017 ◽  
Vol 13 (1) ◽  
pp. 67-78 ◽  
Author(s):  
Daniel Baldwin Hess ◽  
Evan Iacobucci ◽  
Annika Väiko
Keyword(s):  
Social Media ◽  
Central And Eastern Europe ◽  
Empirical Method ◽  
Political Systems ◽  
Neural Network Analysis ◽  
Positive Perception ◽  
Data Set ◽  
Urban Neighbourhoods ◽  
The Subject ◽  
Twitter Users

Abstract The residential landscape of a city is key to its economic, social, and cultural functioning. Following the collapse of communist rule in the countries of Central and Eastern Europe (CEE) in the late 1980s and early 1990s, urban residential dynamics and household mobility have been critical to urban change under new economies and political systems. This article explores neighbourhood perception, which is a link in the chain to better explanation of socio-spatial processes (and their interruption by the socialist system). We use a novel data set – opinions expressed on one of social media (Twitter), and a novel empirical method – neural network analysis, to explore people’s current attitudes and perceptions about the neighbourhoods and districts in Tartu, Estonia. The findings suggest that Twitter comments about urban neighbourhoods display attitudinal and perceptual commentary, which is subdued compared to other subjects. The socialist goal of homogeneity in neighbourhoods is not reflected in present day perspectives about urban neighbourhoods, 25 years after the disintegration of the USSR. Ambivalence about neighbourhoods persists, but this ambivalence may be in flux. Older, formerly neglected neighbourhoods, the subject of positive perception on social media, are currently experiencing increased investment, and the observed trends in our data support a narrative of neighbourhood transition.

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