scholarly journals Impact of Courseware App’s during pandemic: social media diminishes Social Distancing

2021 ◽  
Vol 3 (Special Issue 7S) ◽  
pp. 65-69
Author(s):  
Aayesha Sagir Khan ◽  
Sagir Ahmed Khan ◽  
Samar Alnmer
Keyword(s):  
Social Media ◽  
Social Distancing

Corona Virus (COVID-19) Awareness Assessment - A Survey Study Amongst the Indian Population

2020 ◽  
Author(s):  
Gabriela Fernandes
Keyword(s):  
Health Care ◽  
Social Media ◽  
Health Care Workers ◽  
Indian Population ◽  
Age Groups ◽  
Survey Study ◽  
Social Distancing ◽  
Corona Virus ◽  
Care Workers ◽  
Amount Of Knowledge

Aim: The aim of this survey study was to assess the level of awareness amongst Indian population regarding the COVID-19. Method: A survey was conducted amongst 745 individuals to assess their level of awareness regarding COVID-19 and steps to be taken for its prevention. Result: The results revealed that a considerable percentage of individuals learned about the pandemic through social media and news and were aware of the mode of spread of the virus and also steps to be taken to prevent it from spreading. But considerable percentage of people was also not fully aware regarding the age groups this virus will be affecting. Conclusion: Upon understanding the percentage of people not aware about the age groups this virus will be affecting, keeping in mind good amount of knowledge amongst individuals about maintaining hygiene and social distancing, this survey would help the health care workers to create awareness regarding the effect of this virus on different age groups to help prevent carelessness amongst youth in following the regime.

The Effects of Different Kernels in SVM Sentiment Analysis on Mass Social Distancing

2020 ◽  
Vol 9 (2) ◽  
pp. 161
Author(s):  
Komang Dhiyo Yonatha Wijaya ◽  
Anak Agung Istri Ngurah Eka Karyawati
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Kernel Method ◽  
Idle Time ◽  
Linear Kernel ◽  
Social Distancing ◽  
The Social ◽  
Negative Sentiment ◽  
F Measure ◽  
Kernel Yield

During this pandemic, social media has become a major need as a means of communication. One of the social medias used is Twitter by using messages referred to as tweets. Indonesia currently undergoing mass social distancing. During this time most people use social media in order to spend their idle time However, sometimes, this result in negative sentiment that used to insult and aimed at an individual or group. To filter that kind of tweets, a sentiment analysis was performed with SVM and 3 different kernel method. Tweets are labelled into 3 classes of positive, neutral, and negative. The experiments are conducted to determine which kernel is better. From the sentiment analysis that has been performed, SVM linear kernel yield the best score Some experiments show that the precision of linear kernel is 57%, recall is 50%, and f-measure is 44%

scholarly journals Mining and Validating Social Media for COVID-19-Related Human Behaviors between January and July; An Infodemiology Study (Preprint)

2021 ◽  
Author(s):  
Ashlynn R. Daughton ◽  
Courtney Diane Shelley ◽  
Martha Barnard ◽  
Dax Gerts ◽  
Chrysm Watson Ross ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Ground Truth ◽  
The United States ◽  
Training Data ◽  
Long Term Effects ◽  
Social Distancing ◽  
Human Behaviors ◽  
Mobility Data ◽  
The Impact

BACKGROUND Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which can build trust and adherence to subsequent behavioral messaging. Monitoring the psychological impacts of an outbreak, as well as public adherence to such messaging is also important for minimizing long term effects of an outbreak. OBJECTIVE We used social media data to identify human behaviors relevant to COVID-19 transmission and the perceived impacts of COVID-19 on individuals as a first step toward real time monitoring of public perceptions to inform public health communications. METHODS We develop a coding schema for 6 categories and 11 subcategories, which includes both a wide number of behaviors, as well codes focused on the impacts of the pandemic (e.g., economic and mental health impacts). We use this to develop training data and develop supervised learning classifiers for classes with sufficient labels. Classifiers that perform adequately are applied to our remaining corpus and temporal and geospatial trends are assessed. We compare the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. RESULTS We apply our labeling schema to ~7200 tweets. The worst performing classifiers have F1 scores of only 0.18-0.28 when trying to identify tweets about monitoring symptoms and testing. Classifiers about social distancing, however, are much stronger with F1 scores of 0.64-0.66. We applied the social distancing classifiers to over 228 million tweets. We show temporal patterns consistent with real-world events, and show correlations of up to -0.5 between social distancing signals on Twitter and ground-truth mobility throughout the United States. CONCLUSIONS Behaviors discussed on Twitter are exceptionally varied. Twitter can provide useful information for parameterizing models that incorporate human behavior as well as informing public health communication strategies by describing awareness of and compliance with suggested behaviors. CLINICALTRIAL N/A

scholarly journals Towards Combating Pandemic-Related Misinformation in Social Media

2021 ◽  
pp. 140-158
Author(s):  
Isa Inuwa-Dutse
Keyword(s):  
Social Media ◽  
Public Discourse ◽  
Preventive Measures ◽  
State Of The Art ◽  
Fake News ◽  
Social Distancing ◽  
The Public ◽  
Toxic Impact ◽  
Online Social Media ◽  
Social Media Platforms

Conventional preventive measures during pandemics include social distancing and lockdown. Such measures in the time of social media brought about a new set of challenges – vulnerability to the toxic impact of online misinformation is high. A case in point is COVID-19. As the virus propagates, so does the associated misinformation and fake news about it leading to an infodemic. Since the outbreak, there has been a surge of studies investigating various aspects of the pandemic. Of interest to this chapter are studies centering on datasets from online social media platforms where the bulk of the public discourse happens. The main goal is to support the fight against negative infodemic by (1) contributing a diverse set of curated relevant datasets; (2) offering relevant areas to study using the datasets; and (3) demonstrating how relevant datasets, strategies, and state-of-the-art IT tools can be leveraged in managing the pandemic.

scholarly journals Threat, Coping, and Social Distance Adherence During COVID-19: Cross-Continental Comparison Using an Online Cross-Sectional Survey

10.2196/23019 ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. e23019
Author(s):  
Abrar Al-Hasan ◽  
Jiban Khuntia ◽  
Dobin Yim
Keyword(s):  
United States ◽  
Social Media ◽  
South Korea ◽  
Information Source ◽  
The United States ◽  
Seemingly Unrelated Regression ◽  
Social Distancing ◽  
Unrelated Regression ◽  
And Coping ◽  
Appraisal Processes

Background Social distancing is an effective preventative policy for COVID-19 that is enforced by governments worldwide. However, significant variations are observed in adherence to social distancing across individuals and countries. Due to the lack of treatment, rapid spread, and prevalence of COVID-19, panic and fear associated with the disease causes great stress. Subsequent effects will be a variation around the coping and mitigation strategies for different individuals following different paths to manage the situation. Objective This study aims to explore how threat and coping appraisal processes work as mechanisms between information and citizens’ adherence to COVID-19–related recommendations (ie, how the information sources and social media influence threat and coping appraisal processes with COVID-19 and how the threat and coping appraisal processes influence adherence to policy guidelines). In addition, this study aims to explore how citizens in three different countries (the United States, Kuwait, and South Korea), randomly sampled, are effectively using the mechanisms. Methods Randomly sampled online survey data collected by a global firm in May 2020 from 162 citizens of the United States, 185 of Kuwait, and 71 of South Korea were analyzed, resulting in a total sample size of 418. A seemingly unrelated regression model, controlling for several counterfactuals, was used for analysis. The study’s focal estimated effects were compared across the three countries using the weighted distance between the parameter estimates. Results The seemingly unrelated regression model estimation results suggested that, overall, the intensity of information source use for the COVID-19 pandemic positively influenced the threat appraisal for the disease (P<.001). Furthermore, the intensity of social media use for the COVID-19 pandemic positively influenced the coping appraisal for the disease (P<.001). Higher COVID-19 threat appraisal had a positive effect on social distancing adherence (P<.001). Higher COVID-19 coping appraisal had a positive effect on social distancing adherence (P<.001). Higher intensity of COVID-19 knowledge positively influenced social distancing adherence (P<.001). There were country-level variations. Broadly, we found that the United States had better results than South Korea and Kuwait in leveraging the information to threat and coping appraisal to the adherence process, indicating that individuals in countries like the United States and South Korea may be more pragmatic to appraise the situation before making any decisions. Conclusions This study’s findings suggest that the mediation of threat and coping strategies are essential, in varying effects, to shape the information and social media strategies for adherence outcomes. Accordingly, coordinating public service announcements along with information source outlets such as mainstream media (eg, TV and newspaper) as well as social media (eg, Facebook and Twitter) to inform citizens and, at the same time, deliver balanced messages about the threat and coping appraisal is critical in implementing a staggered social distancing and sheltering strategy.

scholarly journals Changes in public response associated with various COVID-19 restrictions in Ontario, Canada: an observational study using social media time series data

2021 ◽  
Author(s):  
Antony Chum ◽  
Andrew Nielsen ◽  
Zachary Bellows ◽  
Eddie Farrell ◽  
Pierre-Nicolas Durette ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Public Opinion ◽  
News Media ◽  
School Closure ◽  
Series Data ◽  
Social Distancing ◽  
Public Response ◽  
Collective Attention ◽  
Positive Sentiment

Background: News media coverage of anti-mask protests, COVID-19 conspiracies, and pandemic politicization has overemphasized extreme views, but does little to represent views of the general public. Investigating the public’s response to various pandemic restrictions can provide a more balanced assessment of current views, allowing policymakers to craft better public health messages in anticipation of poor reactions to controversial restrictions. Objective: Using data from social media, this study aims to understand the changes in public opinion associated with the implementation of COVID-19 restrictions (e.g. business and school closure, regional lockdown differences, additional public health restrictions such as social distancing and masking). Methods: COVID-related tweets in Ontario (n=1,150,362) were collected based on keywords between March 12 to Oct 31 2020. Sentiment scores were calculated using the VADER algorithm for each tweet to represent its negative to positive emotion. Public health restrictions were identified using government and news media websites, and dynamic regression models with ARIMA errors were used to examine the association between public health restrictions and changes in public opinion over time (i.e. collective attention, aggregate positive sentiment, and level of disagreement) controlling for the effects of confounders (i.e. daily COVID-19 case counts, holidays, COVID-related official updates). Results: In addition to expected direct effects (e.g. business closure led to decreased positive sentiment and increased disagreements), the impact of restriction on public opinion is contextually driven. For example, the negative sentiment associated with business closures was reduced with higher COVID-19 case counts. While school closure and other restrictions (e.g. masking, social distancing, and travel restrictions) generated increased collective attention, they did not have an effect on aggregate sentiment or the level of disagreement (i.e. sentiment polarization). Partial (region-targeted) lockdowns were associated with better public response (i.e. higher number of tweets with net positive sentiment and lower levels of disagreement) compared to province-wide lockdowns. Conclusions: Our study demonstrates the feasibility of a rapid and flexible method of evaluating the public response to pandemic restrictions using near real-time social media data. This information can help public health practitioners and policymakers anticipate public response to future pandemic restrictions, and ensure adequate

COVID-19, Social Distancing, & Adolescent Mental Health on Twitter: An Online Content Analysis (Preprint)

2020 ◽  
Author(s):  
Reese Haley Hyzer ◽  
Joshua J Jerisha
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Content Analysis ◽  
Adolescent Mental Health ◽  
Health Impact ◽  
National Sample ◽  
Health Condition ◽  
Online Content ◽  
Social Distancing ◽  
Significant Difference

BACKGROUND In the early days of the coronavirus disease 2019 (COVID-19) crisis, high engagement with pandemic-related social media was correlated with a 22.6% increase in anxiety and a 48.3% increase in depression. Before the start of the pandemic, young people were already at an elevated risk of anxiety and depression, with 20% of college students reporting at least one mental health condition. Currently, it is unclear what role COVID-19 messaging on social media has played in the adolescent mental health response to the pandemic. OBJECTIVE The purpose of this study was to explore co-occurrences between mentions of social distancing and mental health on Twitter, as well as linguistic elements of these posts. METHODS Our study was an online content analysis on Twitter. Tweets with hashtag #COVID19 were sampled from March 2020 and April 2020. Social media demographics were determined for both months. These Tweets were then evaluated for individual and co-occurrence mentions of social distancing and mental health. The presence of media (images, videos, or hyperlinks) was also recorded. The Linguistic Inquiry and Word Count (LIWC) program we used measured the prevalence of language under the categories of anxiety, anger, sadness, and risk, as well as the usage of 1st person singular pronouns and 1st person plural pronouns. Additionally, overall emotional tone was determined for both datasets. Descriptive statistics were used to analyze social media demographics and post content. LIWC scores between March and April were compared with independent t-tests. RESULTS A national sample of 100 Tweets with hashtag #COVID19 were collected. 50 Tweets were sampled from March 2020 and April 2020 respectively. Among March Tweets, 44% (n = 22) referenced social distancing, 48% (n = 24) referenced mental health, and 22% (n = 11) referenced both. Among April Tweets, 54% (n = 27) referenced social distancing, 22% (n = 11) referenced mental health, and 12% (n = 6) referenced both. The mean LIWC scores between March and April decreased 1.46 points for singular pronouns (p = 0.0271). There was no significant difference between March and April Tweets in the LIWC scores for anxiety, anger, sadness, risk, and plural pronouns. CONCLUSIONS Between March and April, we found that references to social distancing became more frequent, while references to mental health decreased. Likewise, singular pronoun usage decreased significantly. These findings do not imply a diminished mental health impact, but rather suggest an increased focus on collective action over individual sentiment. Future studies should utilize interviews and focus groups to further examine the relevant mental health implications among individual adolescents.

Visual Stories of COVID-19 Social-Physical Distancing From Tagged Social Imagery

2021 ◽  
pp. 245-284
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Social Media ◽  
Medical Science ◽  
Personal Privacy ◽  
Social Distancing ◽  
Manual Analysis

“Social distancing,” combined with self-quarantining and self-isolating, are some of the few initial defensive stances for naïve humanity against a highly transmissible and contagious lethal pathogen, until more high-powered medical science-based interventions (therapeutics, vaccines) are available. “Social distancing” refers to various approaches: the physical distancing of people from each other, the wearing of face masks in public, the washing of hands to avoid contaminants from others' microbes, and others. On social media, social imagery labeled “social distancing” (by both folk tagging and automated machine tagging) may be studied to better understand the surprise of transitioning from modern hypersociality (oversharing, high connectance, lessened senses of personal privacy) to sudden social-physical distancing with only the mitigations of electronic connectivity. This work takes a systematized manual analysis of social imagery to better understand social-physical distancing in a present-day pandemic.

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