Likes, retweets, and polarization

Kaylor, Brian T.

doi:10.1177/0034637319851508

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…After examining the data, it turns out that the stringent health containment measures adopted globally, e.g., face masks, closures, travel bans, and social distancing, were highly polarizing and gained much attention online. Polarizing content, in general, is known to be retweeted more 17 and there is evidence of political polarization getting worse during COVID-19, partially attributable to the media’s problematic coverage of the pandemic 18 . All these factors coupled with people’s distrust in traditional media outlets increased their attention towards social media for information updates, thereby boosting the spread of such content.…”

Section: Resultsmentioning

confidence: 99%

Social status and novelty drove the spread of online information during the early stages of COVID-19

Photiou

Nicolaides

Dhillon

2021

Sci Rep

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Access to online information has been crucial throughout the COVID-19 pandemic. We analyzed more than eight million randomly selected Twitter posts from the first wave of the pandemic to study the role of the author’s social status (Health Expert or Influencer) and the informational novelty of the tweet in the diffusion of several key types of information. Our results show that health-related information and political discourse propagated faster than personal narratives, economy-related or travel-related news. Content novelty further accelerated the spread of these discussion themes. People trusted health experts on health-related knowledge, especially when it was novel, while influencers were more effective at propagating political discourse. Finally, we observed a U-shaped relationship between the informational novelty and the number of retweets. Tweets with average novelty spread the least. Tweets with high novelty propagated the most, primarily when they discussed political, health, or personal information, perhaps owing to the immediacy to mobilize this information. On the other hand, economic and travel-related information spread most when it was less novel, and people resisted sharing such information before it was duly verified.

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Section: Resultsmentioning

confidence: 99%

Social status and novelty drove the spread of online information during the early stages of COVID-19

Photiou

Nicolaides

Dhillon

2021

Sci Rep

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“…Second, SM use may amplify information processing and attentional biases. As discussed, platform algorithms typically compete for attention, connect like-minded users, and amplify sensationalist material that is trending (reinforcing, sensationalising) (Kaylor, 2019), which is by its very nature biased, e.g. catastrophising, magnifiying/minimising, overgeneralising, etc.…”

Section: Platform Features and Affordancesmentioning

confidence: 99%

A trans-diagnostic cognitive behavioural conceptualisation of the positive and negative roles of social media use in adolescents’ mental health and wellbeing

Tibber¹,

Silver

2022

tCBT

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Whilst research into the association between social media and mental health is growing, clinical interest in the field has been dominated by a lack of theoretical integration and a focus on pathological patterns of use. Here we present a trans-diagnostic cognitive behavioural conceptualisation of the positive and negative roles of social media use in adolescence, with a focus on how it interacts with common mental health difficulties. Drawing on clinical experience and an integration of relevant theory/literature, the model proposes that particular patterns of social media use be judged as helpful/unhelpful to the extent that they help/hinder the adolescent from satisfying core needs, particularly those relating to acceptance and belonging. Furthermore, it introduces several key interacting processes, including purposeful/habitual modes of engagement, approach/avoidance behaviours, as well as the potential for social media to exacerbate/ameliorate cognitive biases. The purpose of the model is to act as an aide for therapists to collaboratively formulate the role of social media in young people’s lives, with a view to informing treatment, and ultimately, supporting the development of interventions to help young people use social media in the service of their needs and values. Key learning aims (1) To gain an understanding of a trans-diagnostic conceptualisation of social media use and its interaction with common mental health difficulties in adolescence. (2) To gain an understanding of relevant research and theory underpinning the conceptualisation. (3) To gain an understanding of core processes and dimensions of social media use, and their interaction with common mental health difficulties in this age group, for the purpose of assessment and formulation. (4) To stimulate ideas about how to include adolescent service users’ online world(s) in treatment (where indicated), both with respect to potential risks to ameliorate and benefits to capitalise upon. (5) To stimulate and provide a framework for clinically relevant research in the field and the development of interventions to support young people to flourish online.

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“…También, pueden ser clasificados por su perfil político (Spohr, 2017;Auxier;Vitak, 2019). Así, el uso de las redes sociales, que ofrece más libertad y diversidad, está polarizando la sociedad, donde prima la velocidad sobre la precisión y se vierte una comunicación más agresiva (Kaylor, 2019). Las nuevas tecnologías dan lugar a problemáticas éticas (Gil de Zúñiga; Diehl, 2017).…”

Section: Introducción 1twitter Y Medios De Comunicaciónunclassified

Impacto de las emociones vertidas por diarios digitales en Twitter

García

Martínez

Carabel

2020

EPI

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The use of Twitter by newspapers is widespread and is a way to keep readers informed in real time. In this article, we analyze the discourse of the messages released by the ten main general information newspapers in Spain and the reactions they provoked on the social network. The objective is to analyze whether the emotional discourse of the news in each newspaper caused greater dissemination among and attention from users, as well as to determine the emotions and feelings expressed by them. To do so, news about important events such as court judgements, street riots, and general elections was followed between October and November 2019. A total of 124,897 tweets collected using machine-learning techniques were analyzed by the application of algorithms which allowed the determination of emotions and valences of feelings. We carried out statistical studies and produced graphs showing the dependence between emotional variables and positive or negative sentimental valence. The results showed that, in general, newspapers do not use an excessive amount of emotional speech with the aim of impacting their public. However, differences were found among the newspapers in terms of trying to encourage reader loyalty. The reaction of the users was more linked to the informative facts themselves and the emotions they provoked than to the type of emotional and/or polarized discourse. The day-to-day information determines to a large extent what is consumed by Twitter users, in which changing modes of speech are observed depending on the editorial line of each newspaper. Resumen El uso de Twitter por parte de los diarios de información está muy extendido y es una forma de tener a sus lectores informados casi en tiempo real. En este artículo analizamos el discurso de los mensajes vertidos por los diez principales diarios de información general en España y las reacciones que provocan en la red social. El objetivo de esta investigación es analizar si es el discurso emocional de las noticias de cada diario el que provoca mayor difusión y atención por parte de los usuarios, así como conocer las emociones y sentimientos vertidos temporalmente en los mismos. Para ello se hizo un seguimiento entre octubre y noviembre de 2019 de noticias que incluyen acontecimientos importantes como sentencias, altercados o la celebración de elecciones generales. Mediante el empleo de técnicas de machine learning se analizaron con la aplicación de algoritmos 124.897 tweets, lo que permitió determinar las emociones y valencias, así como desarrollar estudios estadísticos y gráficos de dependencia entre variables emocionales y de valencia sentimental positiva o negativa. Los resultados evidencian que en general, no se emplean excesivos discursos emocionales que busquen impactar. Sin embargo, sí que se aprecian diferencias de uso emocional y de sentimientos entre los diarios que pretenden la fidelización del lector. Por contra se encuentra que la reacción de los usuarios está más ligada al hecho informativo en sí y a las emociones que les provocan, que al tipo de discurso emocional y/o polarizado. El día a día informativo determina en gran medida qué se consume por parte de los usuarios de la red social, en la que se aprecian discursos cambiantes en función de la línea editorial de cada diario.

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Likes, retweets, and polarization

Cited by 6 publications

References 5 publications

Social status and novelty drove the spread of online information during the early stages of COVID-19

Social status and novelty drove the spread of online information during the early stages of COVID-19

A trans-diagnostic cognitive behavioural conceptualisation of the positive and negative roles of social media use in adolescents’ mental health and wellbeing

Impacto de las emociones vertidas por diarios digitales en Twitter

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