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

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 ◽  
Social Distancing ◽  
Public Response ◽  
Collective Attention ◽  
Positive Sentiment ◽  
Negative 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 resources are dedicated to addressing increases in negative sentiment and levels of disagreement in the face of scientifically informed, but controversial, restrictions.

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

scholarly journals Blurred Shots: Investigating the Information Crisis Around Vaccination in Italy

2020 ◽  
pp. 000276422091024
Author(s):  
Alessandro Lovari ◽  
Valentina Martino ◽  
Nicola Righetti
Keyword(s):  
Public Health ◽  
Social Media ◽  
Public Opinion ◽  
Public Relations ◽  
Health Communication ◽  
News Media ◽  
Media Coverage ◽  
Social Consequences ◽  
Combining Data ◽  
Italian Context

This article aims at exploring a case of information crisis in Italy through the lens of vaccination-related topics. Such a controversial issue, dividing public opinion and political agendas, has received diverse information coverage and public policies over time in the Italian context, whose situation appears quite unique compared with other countries because of a strong media spectacularization and politicization of the topic. In particular, approval of the “Lorenzin Decree,” increasing the number of mandatory vaccinations from 4 to 10, generated a nationwide debate that divided public opinion and political parties, triggering a complex informative crisis and fostering the perception of a social emergency on social media. This resulted in negative stress on lay publics and on the public health system. The study adopted an interdisciplinary framework, including political science, public relations, and health communication studies, as well as a mixed-method approach, combining data mining techniques related to news media coverage and social media engagement, with in-depth interviews to key experts, selected among researchers, journalists, and communication managers. The article investigates reasons for the information crisis and identifies possible solutions and interventions to improve the effectiveness of public health communication and mitigate the social consequences of misinformation around vaccination.

scholarly journals Psychological Analysis of Jokowi’s First 100 Days and Nawacita from Text in Twitter

2018 ◽  
Vol 21 (3) ◽  
pp. 173
Author(s):  
Indro Adinugroho ◽  
Smitha Sjahputri ◽  
Judotens Budiarto ◽  
Roby Muhamad
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Human Behavior ◽  
Strategic Plan ◽  
Political Issues ◽  
Public Response ◽  
The Public ◽  
Psychological Analysis ◽  
Valence And Arousal ◽  
Negative Sentiment

In recent days, the public often uses social media such as Twitter for delivering critics; appreciation and campaign related to Government and political issues. The existence of Twitter is changing human behavior rapidly. This study aims to identify Twitter as a medium to generate public opinion concerning two political issues, the 7th Indonesian President first 100 days and public response towards his strategic plan, Nawacita. Method applied in this study is a combination of contemporary research instruments that combines technology and psychology. In this study, the authors examined conversation on Twitter by using Tracker and Algoritma Kata (AK, words algorithm). Tracker is used to collecting conversation on twitter regarding Jokowi’s first 100 days and Nawacita, whereas AK is applied to identify valence and arousal in each tweet collected by Tracker. The finding shows the domination of positive tweets in every week. However, there is a moment where the number of positive tweets was close to negative tweets. In Nawacita issue, law reformation and enforcement was the issue that has highest negative sentiment among others.

scholarly journals Social Bots’ Sentiment Engagement in Health Emergencies: A Topic-Based Analysis of the COVID-19 Pandemic Discussions on Twitter

2020 ◽  
Vol 17 (22) ◽  
pp. 8701 ◽  
Author(s):  
Wen Shi ◽  
Diyi Liu ◽  
Jing Yang ◽  
Jing Zhang ◽  
Sanmei Wen ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Public Opinion ◽  
Sentiment Analysis ◽  
Healthcare System ◽  
Health Risks ◽  
Emotional Support ◽  
Social Distancing ◽  
The Us ◽  
Almost All

During the COVID-19 pandemic, when individuals were confronted with social distancing, social media served as a significant platform for expressing feelings and seeking emotional support. However, a group of automated actors known as social bots have been found to coexist with human users in discussions regarding the coronavirus crisis, which may pose threats to public health. To figure out how these actors distorted public opinion and sentiment expressions in the outbreak, this study selected three critical timepoints in the development of the pandemic and conducted a topic-based sentiment analysis for bot-generated and human-generated tweets. The findings show that suspected social bots contributed to as much as 9.27% of COVID-19 discussions on Twitter. Social bots and humans shared a similar trend on sentiment polarity—positive or negative—for almost all topics. For the most negative topics, social bots were even more negative than humans. Their sentiment expressions were weaker than those of humans for most topics, except for COVID-19 in the US and the healthcare system. In most cases, social bots were more likely to actively amplify humans’ emotions, rather than to trigger humans’ amplification. In discussions of COVID-19 in the US, social bots managed to trigger bot-to-human anger transmission. Although these automated accounts expressed more sadness towards health risks, they failed to pass sadness to humans.

scholarly journals ANALISIS SENTIMEN CALON PRESIDEN DAN WAKIL PRESIDEN PERIODE 2019-2024 PASCA DEBAT PILPRES DI TWITTER

2019 ◽  
Vol 2 (1) ◽  
pp. 21
Author(s):  
Rizka Ardiansyah
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Presidential Election ◽  
Social Networking Sites ◽  
Vice President ◽  
Presidential Candidate ◽  
Presidential Candidates ◽  
The Public ◽  
Positive Sentiment ◽  
Negative Sentiment

Social networking sites, such as Twitter and Facebook are one of the important spaces for political engagement. Twitter or Facebook have become common elements in political campaigns and elections, especially for Indonesia’s presidential election 2019. for the period 2019 - 2024 there are two presidential and vice presidential candidates namely Ir. H. Joko Widodo - Prof. Dr. K.H. Ma'ruf Amin and Lieutenant General (Ret.) H. Prabowo Subianto - H. Sandiaga Uno. B.B.A., M.B.A. the two candidates who ran for the election triggered a lot of related public opinion where the most suitable candidate to become the president of the next period. Public opinion is generally one of the determining factors for presidential candidates who will later win the election. Presidential candidate debate is the efforts of the election commission to facilitate the presidential candidates to introduce their work programs to the public while building public opinion that they are the right people to become leaders of the next period. Although of course, this is not the only major factor that shapes public opinion. The purpose of this study is to summarize the opinions of the people voiced through social media related to the election of candidates for the Indonesian President and Vice President for the period 2019-2024 post debate on the presidential election. While the benefit is to help the community so that they can understand in a broader context such as what the public opinion about presidential candidates, especially on social media Twitter. The results of this study were presidential candidate Joko Widodo - Makruf Amin obtained a 25% positive sentiment, 4.5% negative sentiment and 70.5% neutral sentiment. while the Prabowo Subianto - Sandiaga Uno pair received a 5.1% positive sentiment, 2.5% negative sentiment and 92.4% neutral sentiment.

scholarly journals The Causes and Consequences of COVID-19 Misperceptions: Understanding the Role of News and Social Media

2020 ◽  
Author(s):  
Aengus Bridgman ◽  
Eric Merkley ◽  
Peter John Loewen ◽  
Taylor Owen ◽  
Derek Ruths ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
News Media ◽  
Media Consumption ◽  
Social Distancing ◽  
Social Media Platforms ◽  
The Relationship

We investigate the relationship between media consumption, misinformation, and important attitudes and behaviours during the COVID-19 pandemic in Canada. We find that comparatively more misinformation circulates on social media platforms, while traditional news media tend to reinforce public health recommendations like social distancing. We find that exposure to social media is associated with misperceptions about COVID-19 while the inverse is true for news media. These misperceptions are in turn associated with lower compliance with social distancing measures. We thus draw a link from misinformation on social media to behaviours and attitudes that potentially magnify the scale and lethality of COVID-19.

scholarly journals Trends in Patient, Physician, and Public Perception of Ulnar Collateral Ligament Reconstruction Using Social Media Analytics

2021 ◽  
Vol 9 (3) ◽  
pp. 232596712199005
Author(s):  
Jonathan S. Yu ◽  
James B. Carr ◽  
Jacob Thomas ◽  
Julianna Kostas ◽  
Zhaorui Wang ◽  
...  
Keyword(s):  
Social Media ◽  
Public Perception ◽  
Ulnar Collateral Ligament ◽  
Return To Play ◽  
Social Media Analytics ◽  
Care Providers ◽  
Collateral Ligament ◽  
The Past ◽  
Positive Sentiment ◽  
Negative Sentiment

Background: Social media posts regarding ulnar collateral ligament (UCL) injuries and reconstruction surgeries have increased in recent years. Purpose: To analyze posts shared on Instagram and Twitter referencing UCL injuries and reconstruction surgeries to evaluate public perception and any trends in perception over the past 3 years. Study Design: Cross-sectional study. Methods: A search of a 3-year period (August 2016 and August 2019) of public Instagram and Twitter posts was performed. We searched for >22 hashtags and search terms, including #TommyJohn, #TommyJohnSurgery, and #tornUCL. A categorical classification system was used to assess the sentiment, media format, perspective, timing, accuracy, and general content of each post. Post popularity was measured by number of likes and comments. Results: A total of 3119 Instagram posts and 267 Twitter posts were included in the analysis. Of the 3119 Instagram posts analyzed, 34% were from patients, and 28% were from providers. Of the 267 Twitter posts analyzed, 42% were from patients, and 16% were from providers. Although the majority of social media posts were of a positive sentiment, over the past 3 years, there was a major surge in negative sentiment posts (97% increase) versus positive sentiment posts (9% increase). Patients were more likely to focus their posts on rehabilitation, return to play, and activities of daily living. Providers tended to focus their posts on education, rehabilitation, and injury prevention. Patient posts declined over the past 3 years (–28%), whereas provider posts increased substantially (110%). Of posts shared by health care providers, 4% of posts contained inaccurate or misleading information. Conclusion: The majority of patients who post about their UCL injury and reconstruction on social media have a positive sentiment when discussing their procedure. However, negative sentiment posts have increased significantly over the past 3 years. Patient content revolves around rehabilitation and return to play. Although patient posts have declined over the past 3 years, provider posts have increased substantially with an emphasis on education.

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 Analysis of Social Media Users Sentiments against Omnibus Law Based on Hashtags on Twitter

SISTEMASI ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 197
Author(s):  
Okta Fanny ◽  
Heri Suroyo
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Main Topic ◽  
Accuracy Score ◽  
Test Results ◽  
Bayes Classifier ◽  
The Public ◽  
Average Accuracy ◽  
Positive Sentiment ◽  
Negative Sentiment

From the research that has been done, it can be concluded that Sentiment Analysis can be used to know the sentiment of the public, especially Twitter netizens against omnibus law. After the sentiment analysis, it looks neutral artmen with the largest percentage of 55%, then positive sentiment by 35% and negative sentiment by 10%. The results of the analysis showed that the Naïve Bayes Classifier method provides classification test results with accuracy in Hashtag Pro with an average accuracy score of 92.1%, precision values with an average of 94.8% and recall values with an average of 90.7%. While Hashtag Counter For data classification, with an average accuracy value of 98.3%, precision value with an average of 97.6% and recall value with an average of 98.7%. The result of text cloud analysis conducted on a combination of hashtags both Hashtag pros and Hashtags cons, the dominant word appears is Omnibus Law which means that all hashtags in scrap is really discussing the main topic that is about Omnibus Law

Communicating During an Outbreak or Public Health Investigation

2019 ◽  
pp. 243-260 ◽  
Author(s):  
Abbigail J. Tumpey ◽  
David Daigle ◽  
Glen Nowak
Keyword(s):  
Public Health ◽  
At Risk ◽  
Social Media ◽  
News Media ◽  
Effective Communication ◽  
Crisis Response ◽  
Communication Strategy ◽  
The Public ◽  
The Media

Effective communication during an outbreak or public health investigation is crucial for fostering adoption of public health recommendations and minimizing or preventing harm. During outbreaks, a comprehensive communication strategy integrating news media, social media, and partner engagement is essential for reaching affected persons and for keeping everyone informed about public health actions and recommendations. The strategies outlined in this chapter are the foundation for rapidly and effectively conveying information and public health recommendations to the persons at risk, the media, and the different entities involved in the response. Regardless of the public health event’s cause, core communication actions and steps will be similar; however, in every outbreak or public health investigation, perceptions and needs will vary among target audiences, partners (i.e., persons or organizations that can play a role in the crisis response), and persons or organizations with a connection or interest in the outbreak (stakeholders).

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