About the Essence of Trust: Tell the Truth and Let Me Choose—I Might Trust You

Gille, Felix

doi:10.3389/ijph.2022.1604592

Cited by 3 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite extensive discussions within different disciplines, the concept of trust remains vague, and the trust constructs are diversified [ 20 ]. Each discipline focuses on different aspects or features of trust.…”

Section: Introductionmentioning

confidence: 99%

Exploring Political Mistrust in Pandemic Risk Communication: Mixed-Method Study Using Social Media Data Analysis

Unlu,

Truong,

Tammi

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

Background This research extends prior studies by the Finnish Institute for Health and Welfare on pandemic-related risk perception, concentrating on the role of trust in health authorities and its impact on public health outcomes. Objective The paper aims to investigate variations in trust levels over time and across social media platforms, as well as to further explore 12 subcategories of political mistrust. It seeks to understand the dynamics of political trust, including mistrust accumulation, fluctuations over time, and changes in topic relevance. Additionally, the study aims to compare qualitative research findings with those obtained through computational methods. Methods Data were gathered from a large-scale data set consisting of 13,629 Twitter and Facebook posts from 2020 to 2023 related to COVID-19. For analysis, a fine-tuned FinBERT model with an 80% accuracy rate was used for predicting political mistrust. The BERTopic model was also used for superior topic modeling performance. Results Our preliminary analysis identifies 43 mistrust-related topics categorized into 9 major themes. The most salient topics include COVID-19 mortality, coping strategies, polymerase chain reaction testing, and vaccine efficacy. Discourse related to mistrust in authority is associated with perceptions of disease severity, willingness to adopt health measures, and information-seeking behavior. Our findings highlight that the distinct user engagement mechanisms and platform features of Facebook and Twitter contributed to varying patterns of mistrust and susceptibility to misinformation during the pandemic. Conclusions The study highlights the effectiveness of computational methods like natural language processing in managing large-scale engagement and misinformation. It underscores the critical role of trust in health authorities for effective risk communication and public compliance. The findings also emphasize the necessity for transparent communication from authorities, concluding that a holistic approach to public health communication is integral for managing health crises effectively.

show abstract

Section: Introductionmentioning

confidence: 99%

Exploring Political Mistrust in Pandemic Risk Communication: Mixed-Method Study Using Social Media Data Analysis

Unlu,

Truong,

Tammi

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

show abstract

Triangle of Trust in Cancer Care? The Physician, the Patient, and Artificial Intelligence Chatbot

Turner

2023

Cancer Biotherapy and Radiopharmaceuticals

View full text Add to dashboard Cite

Exploring Political Mistrust in Pandemic Risk Communication: Mixed-Method Study Using Social Media Data Analysis (Preprint)

Unlu,

Truong,

Tammi

et al. 2023

Preprint

View full text Add to dashboard Cite

UNSTRUCTURED This research paper investigates the role of trust in health authorities during pandemics, with a specific focus on the temporospatial variance of trust levels and their impact on public health outcomes. The study builds upon a prior study on pandemic-related risk perception in Finland, further exploring twelve identified sub-categories of political mistrust. Using a large-scale dataset of social media interactions over three years (2020-2023), we interrogate the dynamics of political trust, pinpointing areas of mistrust accumulation, fluctuations over time, and changes in topic significance. The dataset consists of 13,629 Twitter and Facebook posts related to COVID-19, obtained using academictwitteR package and Facepager application. We utilize a fine-tuned FinBERT model, achieving an 80% accuracy in predicting political mistrust. Additionally, the BERTopic model is employed for topic modelling, demonstrating superior performance in identifying key themes in the mistrust discourse. Our analysis identifies 43 topics, with the most prominent including COVID-19 mortality, coping strategies, PCR testing, and vaccine efficacy. The study also categorizes these topics into nine major themes, revealing an underlying mistrust in the response of the Finnish Institute for Health and Welfare (THL) to the pandemic. Notably, we uncover that public trust correlates with perceptions of disease severity, information-seeking behavior, and the willingness to adopt health measures. Our findings also underscore the distinctive user profiles across social media platforms and their susceptibility to misinformation. This research highlights the efficacy of computational methods such as natural language processing in managing large-scale user engagement and tracking misinformation during health crises. It also underlines the significance of trust in health authorities for effective risk communication and compliance with health measures. The spread of conspiracy theories emphasizes the need for transparent communication from authorities. In conclusion, our findings reinforce the importance of a holistic approach to public health communication and the central role of trust in managing health crises.

show abstract

About the Essence of Trust: Tell the Truth and Let Me Choose—I Might Trust You

Cited by 3 publications

References 9 publications

Exploring Political Mistrust in Pandemic Risk Communication: Mixed-Method Study Using Social Media Data Analysis

Exploring Political Mistrust in Pandemic Risk Communication: Mixed-Method Study Using Social Media Data Analysis

Triangle of Trust in Cancer Care? The Physician, the Patient, and Artificial Intelligence Chatbot

Exploring Political Mistrust in Pandemic Risk Communication: Mixed-Method Study Using Social Media Data Analysis (Preprint)

Contact Info

Product

Resources

About