Understanding news engagement on social media: A media repertoire approach
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ABSTRACT:
SUBMITTER: Dvir-Gvirsman S
PROVIDER: S-EPMC9315192 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundSocial media is widely used as a source of news and information regarding COVID-19. However, the abundance of misinformation on social media platforms has raised concerns regarding the spreading infodemic. Accordingly, many have questioned the utility and impact of social media news use on users' engagement with (mis)information.ObjectiveThis study offers a conceptual framework for how social media news use influences COVID-19 misinformation engagement. More specifically, we examined how news consumption on social media leads to COVID-19 misinformation sharing by inducing belief in such misinformation. We further explored if the effects of social media news use on COVID-19 misinformation engagement depend on individual differences in cognition and personality traits.MethodsWe used data from an online survey panel administered by a survey agency (Qualtrics) in Singapore. The survey was conducted in March 2022, and 500 respondents answered the survey. All participants were older than 21 years and provided consent before taking part in the study. We used linear regression, mediation, and moderated mediation analyses to explore the proposed relationships between social media news use, cognitive ability, personality traits, and COVID-19 misinformation belief and sharing intentions.ResultsThe results suggested that those who frequently used social media for news consumption were more likely to believe COVID-19 misinformation and share it on social media. Further probing the mechanism suggested that social media news use translated into sharing intent via the perceived accuracy of misinformation. Simply put, social media news users shared COVID-19 misinformation because they believed it to be accurate. We also found that those with high levels of extraversion than those with low levels were more likely to perceive the misinformation to be accurate and share it. Those with high levels of neuroticism and openness than those with low levels were also likely to perceive the misinformation to be accurate. Finally, it was observed that personality traits did not significantly influence misinformation sharing at higher levels of cognitive ability, but low cognitive users largely drove misinformation sharing across personality traits.ConclusionsThe reliance on social media platforms for news consumption during the COVID-19 pandemic has amplified, with dire consequences for misinformation sharing. This study shows that increased social media news consumption is associated with believing and sharing COVID-19 misinformation, with low cognitive users being the most vulnerable. We offer recommendations to newsmakers, social media moderators, and policymakers toward efforts in limiting COVID-19 misinformation propagation and safeguarding citizens.
| S-EPMC9533200 | biostudies-literature
Project description:IntroductionNews media play an important role in raising public awareness, framing public opinions, affecting policy formulation, and acknowledgment of public health issues. Traditional qualitative content analysis for news sentiments and focuses are time-consuming and may not efficiently convey sentiments nor the focuses of news media.MethodsWe used descriptive statistics and state-of-art text mining to conduct sentiment analysis and topic modeling, to efficiently analyze over 3 million Reuters news articles during 2007-2017 for identifying their coverage, sentiments, and focuses for public health issues. Based on the top keywords from public health scientific journals, we identified 10 major public health issues (i.e., "air pollution," "alcohol drinking," "asthma," "depression," "diet," "exercise," "obesity," "pregnancy," "sexual behavior," and "smoking").ResultsThe news coverage for seven public health issues, "Smoking," "Exercise," "Alcohol drinking," "Diet," "Obesity," "Depression," and "Asthma" decreased over time. The news coverage for "Sexual behavior," "Pregnancy," and "Air pollution" fluctuated during 2007-2017. The sentiments of the news articles for three of the public health issues, "exercise," "alcohol drinking," and "diet" were predominately positive and associated such as "energy." Sentiments for the remaining seven public health issues were mainly negative, linked to negative terms, e.g., diseases. The results of topic modeling reflected the media's focus on public health issues.ConclusionsText mining methods may address the limitations of traditional qualitative approaches. Using big data to understand public health needs is a novel approach that could help clinical and translational science awards programs focus on community-engaged research efforts to address community priorities.
| S-EPMC8057471 | biostudies-literature
Project description:Background: Social media is ubiquitous as a tool for collaboration, networking, and dissemination. However, little is known about use of social media platforms by pulmonary and critical care medicine fellowship programs.Objective: We identify and characterize pulmonary and critical care fellowship programs using Twitter and Instagram, as well as the posting behaviors of their social media accounts.Methods: We identified all adult and pediatric pulmonary, critical care medicine (CCM), and combined pulmonary and critical care medicine (PCCM) programs in the United States using the Electronic Residency Application Service. We searched for Twitter profiles for each program between January 1, 2018, and September 30, 2018. Tweets and Twitter interactions were classified into the following three types: social, clinical, or medical education (MedEd) related. We collected data about content enhancements of tweets, including the use of pictures, graphics interchange format or videos, hashtags, links, and tagging other accounts. The types of tweets, content enhancement characteristics, and measures of engagement were analyzed for association with number of followers.Results: We assessed 341 programs, including 163 PCCM, 36 adult CCM, 20 adult pulmonary, 67 pediatric CCM, and 55 pediatric pulmonary programs. Thirty-three (10%) programs had Twitter accounts. Of 1,903 tweets by 33 of the 341 programs with Twitter accounts, 476 (25%) were MedEd related, 733 (39%) were clinical, and 694 (36%) were social. The median rate of tweets per month was 1.65 (interquartile range [IQR], 0.4-6.65), with 55% programs tweeting more than monthly. Accounts tweeting more often had significantly more followers than those tweeting less frequently (median, 240 followers; 25-75% IQR, 164-388 vs. median, 107 followers; 25-75% IQR, 13-188; P = 0.006). Higher engagement with clinical and social Twitter interactions (tweets, retweets, likes, and comments) was associated with more followers but not for the MedEd-related Twitter interactions. All types of content enhancements (pictures, graphics interchange format/videos, links, and tagging) were associated with a higher number of followers, except for hashtags.Conclusion: Despite the steadily increasing use of social media in medicine, only 10% of the pulmonary and critical care fellowship programs in the United States have Twitter accounts. Social and clinical content appears to gain traction online; however, additional evaluation is needed on how to effectively engage audiences with MedEd content.
| S-EPMC8357066 | biostudies-literature
Project description:How does the credibility we attribute to media sources influence our opinions and judgments derived from news? Participants read headlines about the social behavior of depicted unfamiliar persons from websites of trusted or distrusted well-known German news media. As a consequence, persons paired with negative or positive headlines were judged more negative or positive than persons associated with neutral information independent of source credibility. Likewise, electrophysiological signatures of slow and controlled evaluative brain activity revealed a dominant influence of emotional headline contents regardless of credibility. Modulations of earlier brain responses associated with arousal and reflexive emotional processing show an effect of negative news and suggest that distrusted sources may even enhance the impact of negative headlines. These findings demonstrate that though we may have distinct perceptions about the credibility of media sources, information processing and social judgments rely on the emotional content of headlines, even when they stem from sources we distrust.
| S-EPMC7943368 | biostudies-literature
Project description:Topic modeling is an active research area with several unanswered questions. The focus of recent research in this area is on the use of a vector embedding representation of the input text with both generative and evolutionary topic modeling techniques. Unfortunately, it is hard to compare different techniques when the underlying data and preprocessing steps that were used to develop the models are not available. This paper presents two secondary datasets that can help address this gap. These datasets are derived from two primary datasets. The first consists of 8145 posts from the r/Cancer health forum and the second consists of 18,294 messages submitted to 20 different news groups. The same preprocessing procedure is applied to both datasets by removing punctuation, stop words and high frequency words. Each dataset is then clustered using three different topic modeling techniques: pPSO, ETM and NVDM and three topic numbers: 10, 20, 30. In addition, for pPSO two text embeddings representation are considered: sBERT and Skipgram. The secondary datasets were originally developed in support of a comparative analysis of the aforementioned topic modeling techniques in a study titled "Comparing PSO-based Clustering over Contextual Vector Embeddings to Modern Topic Modeling" submitted to the Journal of Information Processing and Management. The present paper provides a detailed description of the two secondary datasets including the unique identifier that can be used to retrieve the original documents, the pre-processing scripts, the topic keywords generated by the three topic modeling techniques with varying topic numbers and embedding representations. As such, the datasets allow direct comparison with other topic modeling techniques. To further facilitate this process, the algorithm underlying the evolutionary topic modeling technique, pPSO, proposed by the authors is also provided.
| S-EPMC9289850 | biostudies-literature
Project description:We analyze social media activity during one of the largest protest mobilizations in US history to examine ideological asymmetries in the posting of news content. Using an unprecedented combination of four datasets (tracking offline protests, social media activity, web browsing, and the reliability of news sources), we show that there is no evidence of unreliable sources having any prominent visibility during the protest period, but we do identify asymmetries in the ideological slant of the sources shared on social media, with a clear bias towards right-leaning domains. These results support the "amplification of the right" thesis, which points to the structural conditions (social and technological) that lead to higher visibility of content with a partisan bent towards the right. Our findings provide evidence that right-leaning sources gain more visibility on social media and reveal that ideological asymmetries manifest themselves even in the context of movements with progressive goals.
| S-EPMC9896954 | biostudies-literature
Project description:Highlights • Social media, fake news, and COVID-19.• Misinformation on social media has fuelled panic regarding the COVID-19.• Altruism is the strongest predictor of fake news sharing on COVID-19.• Socialization, information seeking and pass time predict fake news sharing.• Entertainment is not associated with sharing fake news on COVID-19. Fake news dissemination on COVID-19 has increased in recent months, and the factors that lead to the sharing of this misinformation is less well studied. Therefore, this paper describes the result of a Nigerian sample (n = 385) regarding the proliferation of fake news on COVID-19. The fake news phenomenon was studied using the Uses and Gratification framework, which was extended by an “altruism” motivation. The data were analysed with Partial Least Squares (PLS) to determine the effects of six variables on the outcome of fake news sharing. Our results showed that altruism was the most significant factor that predicted fake news sharing of COVID-19. We also found that social media users’ motivations for information sharing, socialisation, information seeking and pass time predicted the sharing of false information about COVID-19. In contrast, no significant association was found for entertainment motivation. We concluded with some theoretical and practical implications.
| S-EPMC7390799 | biostudies-literature
Project description:There has been growing concern about the role social media plays in political polarization. We investigated whether out-group animosity was particularly successful at generating engagement on two of the largest social media platforms: Facebook and Twitter. Analyzing posts from news media accounts and US congressional members (n = 2,730,215), we found that posts about the political out-group were shared or retweeted about twice as often as posts about the in-group. Each individual term referring to the political out-group increased the odds of a social media post being shared by 67%. Out-group language consistently emerged as the strongest predictor of shares and retweets: the average effect size of out-group language was about 4.8 times as strong as that of negative affect language and about 6.7 times as strong as that of moral-emotional language-both established predictors of social media engagement. Language about the out-group was a very strong predictor of "angry" reactions (the most popular reactions across all datasets), and language about the in-group was a strong predictor of "love" reactions, reflecting in-group favoritism and out-group derogation. This out-group effect was not moderated by political orientation or social media platform, but stronger effects were found among political leaders than among news media accounts. In sum, out-group language is the strongest predictor of social media engagement across all relevant predictors measured, suggesting that social media may be creating perverse incentives for content expressing out-group animosity.
| S-EPMC8256037 | biostudies-literature
Project description:The COVID-19 pandemic made explicit the issues of communicating science in an information ecosystem dominated by social media platforms. One of the fundamental communication challenges of our time is to provide the public with reliable content and contrast misinformation. This paper investigates how social media can become an effective channel to promote engagement and (re)build trust. To measure the social response to quality communication, we conducted an experimental study to test a set of science communication recommendations on Facebook and Twitter. The experiment involved communication practitioners and social media managers from select countries in Europe, applying and testing such recommendations for five months. Here we analyse their feedback in terms of adoption and show that some differences emerge across platforms, topics, and recommendation categories. To evaluate these recommendations' effect on users, we measure their response to quality content, finding that the median engagement is generally higher, especially on Twitter. The results indicate that quality communication strategies may elicit positive feedback on social media. A data-driven and co-designed approach in developing counter-strategies is thus promising in tackling misinformation.
| S-EPMC9560150 | biostudies-literature
Project description:There has been a surge in vaccine hesitancy following the Coronavirus pandemic. This study measured the prevalence of and identified factors associated with vaccine hesitancy and social media use. An online survey was administered (n = 1050) between May and July 2021. Chi-square tests were used to examine bivariate associations with vaccine hesitancy (partially vaccinated and unvaccinated participants). Logistic regression was used to identify associations between social media use and vaccine hesitancy. Chi-square tests showed women (69.7% vs 28.2% men, padjusted = .002), African American participants (52.3% vs 17.8% white, padjusted < .001), high school diploma (54.4% vs 38.6% college degree, padjusted < .001), political unaffiliated (15.8% vs 14.5% republican, padjusted < .001), Muslim (10.0% vs 0% Jewish, padjusted < .001), and never married/single (53.9% vs 17.0% married, padjusted < .001) were more likely to be vaccine hesitant. Controlling for all demographic variables (age, race, gender, and education), more frequent use of social media for reading news was associated with lower vaccine hesitancy (OR 0.35, 99% CI 0.20, 0.63, p < 0.001). However, using social media as a source of vaccine information without any other trusted source (health department, doctor, CDC,) was associated with higher odds of being vaccine hesitant (OR 2.00, 99% CI 1.15, 3.46, p = 0.001). People who use social media without referencing trusted sources may be particularly vulnerable to disinformation or vaccine hesitant persons are more likely exposed to non-trusted social media sites as their only information source.
| S-EPMC8947854 | biostudies-literature