scholarly journals Evaluating Rumor Debunking Effectiveness During the COVID-19 Pandemic Crisis: Utilizing User Stance in Comments on Sina Weibo

2021 ◽  
Vol 9 ◽  
Author(s):  
Xin Wang ◽  
Fan Chao ◽  
Guang Yu
Keyword(s):  
Public Health ◽  
Social Media ◽  
Combination Method ◽  
Annotation Scheme ◽  
Sina Weibo ◽  
Combination Methods ◽  
Effective Combination ◽  
Urgent Task ◽  
Text Classifiers ◽  
Effectiveness Index

Background: The spread of rumors related to COVID-19 on social media has posed substantial challenges to public health governance, and thus exposing rumors and curbing their spread quickly and effectively has become an urgent task. This study aimed to assist in formulating effective strategies to debunk rumors and curb their spread on social media.Methods: A total of 2,053 original postings and 100,348 comments that replied to the postings of five false rumors related to COVID-19 (dated from January 20, 2020, to June 28, 2020) belonging to three categories, authoritative, social, and political, on Sina Weibo in China were randomly selected. To study the effectiveness of different debunking methods, a new annotation scheme was proposed that divides debunking methods into six categories: denial, further fact-checking, refutation, person response, organization response, and combination methods. Text classifiers using deep learning methods were built to automatically identify four user stances in comments that replied to debunking postings: supporting, denying, querying, and commenting stances. Then, based on stance responses, a debunking effectiveness index (DEI) was developed to measure the effectiveness of different debunking methods.Results: The refutation method with cited evidence has the best debunking effect, whether used alone or in combination with other debunking methods. For the social category of Car rumor and political category of Russia rumor, using the refutation method alone can achieve the optimal debunking effect. For authoritative rumors, a combination method has the optimal debunking effect, but the most effective combination method requires avoiding the use of a combination of a debunking method where the person or organization defamed by the authoritative rumor responds personally and the refutation method.Conclusion: The findings provide relevant insights into ways to debunk rumors effectively, support crisis management of false information, and take necessary actions in response to rumors amid public health emergencies.

scholarly journals Exploring Urban Spatial Features of COVID-19 Transmission in Wuhan Based on Social Media Data

2020 ◽  
Vol 9 (6) ◽  
pp. 402 ◽  
Author(s):  
Zhenghong Peng ◽  
Ru Wang ◽  
Lingbo Liu ◽  
Hao Wu
Keyword(s):  
Public Health ◽  
Social Media ◽  
Urban Space ◽  
Elderly Population ◽  
Early Stage ◽  
The Elderly ◽  
Preventive Strategy ◽  
Sina Weibo ◽  
Spatial Features ◽  
Distribution Features

During the early stage of the COVID-19 outbreak in Wuhan, there was a short run of medical resources, and Sina Weibo, a social media platform in China, built a channel for novel coronavirus pneumonia patients to seek help. Based on the geo-tagging Sina Weibo data from February 3rd to 12th, 2020, this paper analyzes the spatiotemporal distribution of COVID-19 cases in the main urban area of Wuhan and explores the urban spatial features of COVID-19 transmission in Wuhan. The results show that the elderly population accounts for more than half of the total number of Weibo help seekers, and a close correlation between them has also been found in terms of spatial distribution features, which confirms that the elderly population is the group of high-risk and high-prevalence in the COVID-19 outbreak, needing more attention of public health and epidemic prevention policies. On the other hand, the early transmission of COVID-19 in Wuhan could be divide into three phrases: Scattered infection, community spread, and full-scale outbreak. This paper can help to understand the spatial transmission of COVID-19 in Wuhan, so as to propose an effective public health preventive strategy for urban space optimization.

scholarly journals Suicide Risk and Protective Factors in Online Support Forum Posts: Annotation Scheme Development and Validation Study (Preprint)

2020 ◽  
Author(s):  
Stevie Chancellor ◽  
Steven A Sumner ◽  
Corinne David-Ferdon ◽  
Tahirah Ahmad ◽  
Munmun De Choudhury
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Social Media ◽  
Protective Factors ◽  
Suicide Risk ◽  
Risk And Protective Factors ◽  
Prior Work ◽  
Annotation Scheme ◽  
Social Media Data ◽  
Media Data

BACKGROUND Online communities provide support for individuals looking for help with suicidal ideation and crisis. As community data are increasingly used to devise machine learning models to infer who might be at risk, there have been limited efforts to identify both risk and protective factors in web-based posts. These annotations can enrich and augment computational assessment approaches to identify appropriate intervention points, which are useful to public health professionals and suicide prevention researchers. OBJECTIVE This qualitative study aims to develop a valid and reliable annotation scheme for evaluating risk and protective factors for suicidal ideation in posts in suicide crisis forums. METHODS We designed a valid, reliable, and clinically grounded process for identifying risk and protective markers in social media data. This scheme draws on prior work on construct validity and the social sciences of measurement. We then applied the scheme to annotate 200 posts from r/SuicideWatch—a Reddit community focused on suicide crisis. RESULTS We documented our results on producing an annotation scheme that is consistent with leading public health information coding schemes for suicide and advances attention to protective factors. Our study showed high internal validity, and we have presented results that indicate that our approach is consistent with findings from prior work. CONCLUSIONS Our work formalizes a framework that incorporates construct validity into the development of annotation schemes for suicide risk on social media. This study furthers the understanding of risk and protective factors expressed in social media data. This may help public health programming to prevent suicide and computational social science research and investigations that rely on the quality of labels for downstream machine learning tasks.

scholarly journals Suicide Risk and Protective Factors in Online Support Forum Posts: Annotation Scheme Development and Validation Study

10.2196/24471 ◽  
2021 ◽  
Vol 8 (11) ◽  
pp. e24471
Author(s):  
Stevie Chancellor ◽  
Steven A Sumner ◽  
Corinne David-Ferdon ◽  
Tahirah Ahmad ◽  
Munmun De Choudhury
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Social Media ◽  
Protective Factors ◽  
Suicide Risk ◽  
Risk And Protective Factors ◽  
Prior Work ◽  
Annotation Scheme ◽  
Social Media Data ◽  
Media Data

Background Online communities provide support for individuals looking for help with suicidal ideation and crisis. As community data are increasingly used to devise machine learning models to infer who might be at risk, there have been limited efforts to identify both risk and protective factors in web-based posts. These annotations can enrich and augment computational assessment approaches to identify appropriate intervention points, which are useful to public health professionals and suicide prevention researchers. Objective This qualitative study aims to develop a valid and reliable annotation scheme for evaluating risk and protective factors for suicidal ideation in posts in suicide crisis forums. Methods We designed a valid, reliable, and clinically grounded process for identifying risk and protective markers in social media data. This scheme draws on prior work on construct validity and the social sciences of measurement. We then applied the scheme to annotate 200 posts from r/SuicideWatch—a Reddit community focused on suicide crisis. Results We documented our results on producing an annotation scheme that is consistent with leading public health information coding schemes for suicide and advances attention to protective factors. Our study showed high internal validity, and we have presented results that indicate that our approach is consistent with findings from prior work. Conclusions Our work formalizes a framework that incorporates construct validity into the development of annotation schemes for suicide risk on social media. This study furthers the understanding of risk and protective factors expressed in social media data. This may help public health programming to prevent suicide and computational social science research and investigations that rely on the quality of labels for downstream machine learning tasks.

Auswirkungen der Corona-Pandemie auf die Maßnahmen zur Suchtprävention der Bundeszentrale für gesundheitliche Aufklärung (BZgA)

2020 ◽  
Vol 66 (5) ◽  
pp. 259-264
Author(s):  
Michaela Goecke
Keyword(s):  
Public Health ◽  
Social Media ◽  
Junge Erwachsene ◽  
Bundeszentrale Für Gesundheitliche Aufklärung

Zusammenfassung. Abstract: Hintergrund: Die Bundeszentrale für gesundheitliche Aufklärung (BZgA) ist als Fachbehörde unter anderem für die Umsetzung nationaler Programme zur Suchtprävention zuständig. Die jährlichen Arbeitsprogramme werden mit dem Bundesministerium für Gesundheit abgestimmt und sehen aktuell vor dem Hintergrund der Public-Health-Relevanz Schwerpunkte in der Prävention der legalen Substanzen Tabak und Alkohol vor. Vorrangige Zielgruppen sind Jugendliche und junge Erwachsene, da sich bei ihnen riskante Konsummuster entwickeln und festigen können. Die Präventionsprogramme der BZgA umfassen schulische Angebote, Webportale, Social Media und Printmedien wie Informationsbroschüren. Aktuelle Situation: Die Corona-Pandemie hat Einfluss genommen auf die Suchtprävention der BZgA. Zu nennen ist die thematische Verzahnung im Kontext von Corona und ein veränderter inhaltlicher Beratungsbedarf – telefonisch und online. Auch die durch die Corona-Pandemie bedingten Kontaktbeschränkungen während des „Lockdowns“ sowie die neuen Rahmenbedingungen für ein persönliches Miteinander haben die Suchtprävention verändert. Interaktive Präventionsangebote in Schulen wurden ebenso wie die Unterstützung von Mitmachaktionen in Sportvereinen oder die Durchführung von Peer-Programmen ausgesetzt. Dafür rückte die Nutzung digitaler Möglichkeiten sowohl bei der Umsetzung von suchtpräventiven Angeboten als auch in der Kooperation und Vernetzung mit den Ländern in einen neuen Fokus. Die Corona-Krise kann perspektivisch auch eine Chance für mehr Digitalisierung in der Suchtprävention werden.

Exploring the Nexus between Online Alcohol Posters and Alcohol Drinking among Kenya’s Higher Vocational College students

2020 ◽  
Author(s):  
Joseph Malechwanzi
Keyword(s):  
Public Health ◽  
College Students ◽  
Social Media ◽  
Substance Abuse ◽  
Alcohol Drinking ◽  
Alcoholic Beverage ◽  
Vocational College ◽  
Drinking Habits ◽  
Higher Vocational College ◽  
Unrestricted Access

Alcohol drinking among young people is a major global public health concern. The situation has been aggravated further by the advent of the internet and subsequent development of social media as a tool for online alcohol marketing. Measures that aim at reducing substance abuse is a stride towards “2030 Agenda” for sustainable development goal number 3 set by the United Nation General Assembly. In this goal, attention is not only drawn to health and wellbeing but also to prevention and treatment of substance abuse. This descriptive study sought to find out the prevalence of alcohol advertisements on social media and its possible influence on alcohol drinking among Kenya’s higher vocational college students. Based on a field survey conducted in Nairobi (n=209), this study established that there was heavy presence of alcohol advertisements on social media scene in Kenya. Although statistically, there was huge gender disparity, the final results showed that there was significant association between alcohol ads on social media and college student’s possible alcohol drinking habits. This study concludes that there was heavy presence of alcohol ads on social media, and the likelihood of youth having unrestricted access to the alcoholic beverage products. This could have a far-reaching implication on their alcohol drinking habits. Therefore, the study recommends the stakeholders in public health promotions to formulate policies aimed at mitigating against the challenges posed by unrestricted access to online alcohol ads by the youth in order to prevent them from being lured into early alcohol drinking by the alcoholic beverage makers.　 Keywords: Alcohol abuse; Influence; Online ads; Youth; Kenya

Examining the accuracy of estimated smartphone use: How well-being and usage level predict discrepancies between estimated and actual use

2019 ◽  
Author(s):  
Craig Sewall ◽  
Daniel Rosen ◽  
Todd M. Bear
Keyword(s):  
Public Health ◽  
Social Media ◽  
Life Satisfaction ◽  
Mobile Device ◽  
Screen Time ◽  
Well Being ◽  
Actual Use ◽  
Smartphone Use ◽  
Usage Level

The increasing ubiquity of mobile device and social media (SM) use has generated a substantial amount of research examining how these phenomena may impact public health. Prior studies have found that mobile device and SM use are associated with various aspects of well-being. However, a large portion of these studies relied upon self-reported estimates to measure amount of use, which can be inaccurate. Utilizing Apple’s “Screen Time” application to obtain actual iPhone and SM use data, the current study examined the accuracy of self-reported estimates, how inaccuracies bias relationships between use and well-being (depression, loneliness, and life satisfaction), and the degree to which inaccuracies were predicted by levels of well-being. Among a sample of 393 iPhone users, we found that: a.) participants misestimated their weekly overall iPhone and SM use by 22.1 and 16.6 hours, respectively; b.) the correlations between estimated use and well-being variables were consistently stronger than the correlations between actual use and well-being variables; and c.) the amount of inaccuracy in estimated use is associated with levels of participant well-being as well as amount of use. These findings suggest that estimates of device/SM use may be biased by factors that are fundamental to the relationships being investigated. **This manuscript is currently under review**

Trend of Parental Refusal or Delay of Childhood Vaccinations

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Meagan Marie Daoust
Keyword(s):  
Public Health ◽  
Social Media ◽  
Healthcare System ◽  
Educational Context ◽  
Health Consequences ◽  
Missed Opportunities ◽  
The Public ◽  
Health Related ◽  
Parental Refusal

The healthcare trend of parental refusal or delay of childhood vaccinations will be investigated through a complex Cynefin Framework component in an economic and educational context, allowing patterns to emerge that suggest recommendations of change for the RN role and healthcare system. As a major contributing factor adding complexity to this trend, social media is heavily used for health related knowledge, making it is difficult to determine which information is most trustworthy. Missed opportunities for immunization can result, leading to economic and health consequences for the healthcare system and population. Through analysis of the powerful impact social media has on this evolving trend and public health, an upstream recommendation for RNs to respond with is to utilize reliable social media to the parents’ advantage within practice. The healthcare system should focus on incorporating vaccine-related education into existing programs and classes offered to parents, and implementing new vaccine classes for the public.

RepPer: Perception of Psychiatric Disorders on Twitter in French (Preprint)

2020 ◽  
Author(s):  
Sarah Delanys ◽  
Farah Benamara ◽  
Véronique Moriceau ◽  
François Olivier ◽  
Josiane Mothe
Keyword(s):  
Social Media ◽  
Psychiatric Disorders ◽  
Digital Technology ◽  
Psychotic Disorders ◽  
Negative Polarity ◽  
Machine Learning Algorithms ◽  
Annotation Scheme ◽  
Word Use ◽  
Wide Range ◽  
Initial Dataset

BACKGROUND With the advent of digital technology and specifically user generated contents in social media, new ways emerged for studying possible stigma of people in relation with mental health. Several pieces of work studied the discourse conveyed about psychiatric pathologies on Twitter considering mostly tweets in English and a limited number of psychiatric disorders terms. This paper proposes the first study to analyze the use of a wide range of psychiatric terms in tweets in French. OBJECTIVE Our aim is to study how generic, nosographic and therapeutic psychiatric terms are used on Twitter in French. More specifically, our study has three complementary goals: (1) to analyze the types of psychiatric word use namely medical, misuse, irrelevant, (2) to analyze the polarity conveyed in the tweets that use these terms (positive/negative/neural), and (3) to compare the frequency of these terms to those observed in related work (mainly in English ). METHODS Our study has been conducted on a corpus of tweets in French posted between 01/01/2016 to 12/31/2018 and collected using dedicated keywords. The corpus has been manually annotated by clinical psychiatrists following a multilayer annotation scheme that includes the type of word use and the opinion orientation of the tweet. Two analysis have been performed. First a qualitative analysis to measure the reliability of the produced manual annotation, then a quantitative analysis considering mainly term frequency in each layer and exploring the interactions between them. RESULTS One of the first result is a resource as an annotated dataset . The initial dataset is composed of 22,579 tweets in French containing at least one of the selected psychiatric terms. From this set, experts in psychiatry randomly annotated 3,040 tweets that corresponds to the resource resulting from our work. The second result is the analysis of the annotations; it shows that terms are misused in 45.3% of the tweets and that their associated polarity is negative in 86.2% of the cases. When considering the three types of term use, 59.5% of the tweets are associated to a negative polarity. Misused terms related to psychotic disorders (55.5%) are more frequent to those related to mood disorders (26.5%). CONCLUSIONS Some psychiatric terms are misused in the corpora we studied; which is consistent with the results reported in related work in other languages. Thanks to the great diversity of studied terms, this work highlighted a disparity in the representations and ways of using psychiatric terms. Moreover, our study is important to help psychiatrists to be aware of the term use in new communication media such as social networks which are widely used. This study has the huge advantage to be reproducible thanks to the framework and guidelines we produced; so that the study could be renewed in order to analyze the evolution of term usage. While the newly build dataset is a valuable resource for other analytical studies, it could also serve to train machine learning algorithms to automatically identify stigma in social media.

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