scholarly journals Can Fabricated Data be Ignored when it is Detected?

2021 ◽  
Author(s):  
Jennifer Trueblood ◽  
Adam T Ramsey
Keyword(s):  
Social Media ◽  
Information Sharing ◽  
Quantitative Information ◽  
Total N ◽  
Gaussian Distributions ◽  
Warning Cues

As information sharing via social media increases, individuals are increasingly exposed to misinformation that they may utilize when forming beliefs. Over five experiments (total N=819), we investigated whether people could ignore quantitative information when they judged for themselves that it had been fabricated. Participants recruited online viewed sets of values sampled from Gaussian distributions to estimate the underlying means. They attempted to ignore fabricated data, which were outlier values inserted into the value sequences. Results indicated participants were able to detect outliers, and that higher detection confidence was associated with greater estimate accuracy. However, even when participants were most confident that they detected fabricated data, their estimates were still biased in the direction of the outlier. The addition of visual warning cues and different task scenarios did not fully eliminate systematic over- and under-estimation. These findings suggest individuals may incorporate fabricated data they meant to ignore when forming beliefs.

scholarly journals Source Trust and COVID-19 Information Sharing: The Mediating Roles of Emotions and Beliefs About Sharing

2020 ◽  
pp. 109019812098476
Author(s):  
Linqi Lu ◽  
Jiawei Liu ◽  
Y. Connie Yuan ◽  
Kelli S. Burns ◽  
Enze Lu ◽  
...  
Keyword(s):  
Social Media ◽  
Information Sharing ◽  
Health Information ◽  
News Media ◽  
Health Professionals ◽  
Government Agencies ◽  
Specific Information ◽  
Academic Institutions ◽  
Source Trust ◽  
Health Information Sharing

Health information sharing has become especially important during the COVID-19 (coronavirus disease 2019) pandemic because people need to learn about the disease and then act accordingly. This study examines the perceived trust of different COVID-19 information sources (health professionals, academic institutions, government agencies, news media, social media, family, and friends) and sharing of COVID-19 information in China. Specifically, it investigates how beliefs about sharing and emotions mediate the effects of perceived source trust on source-specific information sharing intentions. Results suggest that health professionals, academic institutions, and government agencies are trusted sources of information and that people share information from these sources because they think doing so will increase disease awareness and promote disease prevention. People may also choose to share COVID-19 information from news media, social media, and family as they cope with anxiety, anger, and fear. Taken together, a better understanding of the distinct psychological mechanisms underlying health information sharing from different sources can help contribute to more effective sharing of information about COVID-19 prevention and to manage negative emotion contagion during the pandemic.

The influence of public health information sharing on social media during the early COVID-19 outbreak

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chiao-Chieh Chen ◽  
Yu-Ping Chiu
Keyword(s):  
Social Media ◽  
Information Sharing ◽  
Health Information ◽  
Content Type ◽  
Related Information ◽  
Activity Effect ◽  
Network Cluster ◽  
Public Health Information ◽  
Health Information Sharing

PurposeSocial media have become famous platform to search and share the COVID-19-related information. The objective of this research is to bridge the gap by proposing the effects of network cluster and transmitter activity on information sharing process.Design/methodology/approachData were collected by using Facebook application, which was available for 14 days (May 1–14) in 2020. These data were analyzed to determine the influence of the network cluster and transmitter activity.FindingsThe results showed that network cluster is positively related to transmitter activity on social media. In addition, transmitter activity partially mediated the effect of network cluster on the extent of information liked and shared. That is, transmitter activity can affect COVID-19-related information sharing on Facebook, and the activity effect is plausible and should become stronger as social network become denser.Originality/valueThis study has contributed to the knowledge of health information sharing in social media and has generated new opportunities for research into the role of network cluster. As social media is firmly entrenched in society, researches that improve the experience or quality for users is potentially impactful.

Strategies for improving recruitment of pregnant women to clinical research: An evaluation of social media versus traditional offline methods in Vancouver, Canada (Preprint)

2021 ◽  
Author(s):  
Kelsey M Cochrane ◽  
Jennifer A Hutcheon ◽  
Crystal D Karakochuk
Keyword(s):  
Social Media ◽  
Pregnant Women ◽  
Conversion Rate ◽  
Performance Metrics ◽  
Demographic Characteristics ◽  
Recruitment Strategy ◽  
Media Campaigns ◽  
Total N ◽  
Cost Rate ◽  
Time Of Year

BACKGROUND Social media is an effective alternative to offline methods for participant recruitment to research. However, the effectiveness of social media compared with offline strategies among pregnant women is unclear. Further, it is unclear whether recruitment strategy alters demographic characteristics of participants. OBJECTIVE We aimed to estimate recruitment rates from social media and offline methods and to explore the whether participant demographics differed according to recruitment strategy in a clinical nutrition trial that recruited 60 healthy pregnant women in Vancouver, Canada. METHODS Facebook was used to run 9 social media campaigns, 10-18 days each (15-weeks total) and costing $50-$100 CAD ($675 CAD total). Offline methods were used concurrently over 64-weeks. A total of $300 CAD was spent on printing. Demographic characteristics of those recruited via each method was compared using bivariate statistics. Cost, rate of recruitment and conversion rate in each group was calculated. Performance metrics of social media campaigns, including reach, impressions, clicks, inquiries, and enrollments, were recorded. Linear regression was used to explore the association between metrics and dollars spent per campaign. RESULTS In total, n=481 inquiries were received (n=51 [11%] via offline methods; n=430 [89%] via social media). Enrollees (n=60) included n=24 (40%) and n=36 (60%) via offline and social media methods, respectively. Gestational weeks was provided by n=251 women (52%) upon inquiry (mean ± SD gestational weeks was 13.3 ± 4.7 and 13.2 ± 5.6 in the offline and social media groups, respectively, P=.96). There were no statistically significant differences in age (33 ± 3.2 and 33 ± 3.6, P=.67), ethnicity (58% and 56% Caucasian, P=.97), education (88% and 78% had University-level education, P=.64), household income (58% and 47% >$100,000 CAD/year, P=.26), pre-pregnancy BMI (22.2 ± 2.6 and 23.4 ± 2.8, P=.11), or parity (75% and 72% nulliparous, P=.81); results are presented for offline and social media, respectively. Direct cost/enrollee was $13 and $19 in those who were recruited via offline and social media methods, respectively (however, this does not include cost of labour). Rate of recruitment was ~6x faster via social media than offline methods, however, the conversion rate was higher via offline methods than social media (47% versus 8%). Overall, campaign metrics (reach, impressions, clicks, and inquiries) improved over time. Amount spent per campaign (controlling for campaign duration) was significantly associated with improved clicks (P=.01), and inquiries (P=.04), but not enrollments (P=.19). CONCLUSIONS Social media was more efficient and effective for recruitment of pregnant women than offline methods. We gained numerous insights for optimization of social media campaigns (dollars spent, attribution setting, photo testing, automatic optimization) to increase clicks and inquiries, however this does not necessarily increase enrollments, which was more dependent on study specific factors (e.g. time of year, study design, and intervention). CLINICALTRIAL ClinicalTrials.gov (identifier: NCT04022135). Registered on July-14-2019. https://clinicaltrials.gov/ct2/show/NCT04022135

The effect of emotional positivity of brand-generated social media messages on consumer attention and information sharing

2022 ◽  
Vol 140 ◽  
pp. 49-61
Author(s):  
João S. Oliveira ◽  
Kemefasu Ifie ◽  
Martin Sykora ◽  
Eleni Tsougkou ◽  
Vitor Castro ◽  
...  
Keyword(s):  
Social Media ◽  
Information Sharing ◽  
Media Messages ◽  
Consumer Attention

scholarly journals Beyond “fake news”: The role of analytic thinking in the detection of inaccuracy and partisan bias in news headlines

2019 ◽  
Author(s):  
Robert M Ross ◽  
David Gertler Rand ◽  
Gordon Pennycook
Keyword(s):  
Social Media ◽  
Fake News ◽  
Analytic Thinking ◽  
Total N ◽  
Partisan Bias ◽  
News Content ◽  
Political Bias ◽  
Political Partisanship ◽  
News Headlines

Why is misleading partisan content believed and shared? An influential account posits that political partisanship pervasively biases reasoning, such that engaging in analytic thinking exacerbates motivated reasoning and, in turn, the acceptance of hyperpartisan content. Alternatively, it may be that susceptibility to hyperpartisan misinformation is explained by a lack of reasoning. Across two studies using different subject pools (total N = 1977), we had participants assess true, false, and hyperpartisan headlines taken from social media. We found no evidence that analytic thinking was associated with increased polarization for either judgments about the accuracy of the headlines or willingness to share the news content on social media. Instead, analytic thinking was broadly associated with an increased capacity to discern between true headlines and either false or hyperpartisan headlines. These results suggest that reasoning typically helps people differentiate between low and high quality news content, rather than facilitating political bias.

scholarly journals Network structure and patterns of information diversity on Twitter

2016 ◽  
Author(s):  
Jesse Conan Shore ◽  
Jiye Baek ◽  
Chrysanthos Dellarocas
Keyword(s):  
Social Media ◽  
Information Sharing ◽  
Cross Section ◽  
Network Structure ◽  
The Political ◽  
Cross Sectional ◽  
News Sources ◽  
Echo Chambers ◽  
Information Diversity

Social media have great potential to support diverse information sharing, but there is widespread concern that platforms like Twitter do not result in communication between those who hold contradictory viewpoints. Because users can choose whom to follow, prior research suggests that social media users exist in "echo chambers" or become polarized. We seek evidence of this in a complete cross section of hyperlinks posted on Twitter, using previously validated measures of the political slant of news sources to study information diversity. Contrary to prediction, we find that the average account posts links to more politically moderate news sources than the ones they receive in their own feed. However, members of a tiny network core do exhibit cross-sectional evidence of polarization and are responsible for the majority of tweets received overall due to their popularity and activity, which could explain the widespread perception of polarization on social media.

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