Public Attitudes During the Second Lockdown: Sentiment and Topic Analyses Using Tweets From Ontario, Canada

Tsao, Shu-Feng; MacLean, Alexander; Chen, Helen; Li, Lianghua; Yang, Yang; Butt, Zahid A

doi:10.3389/ijph.2022.1604658

Cited by 11 publications

(6 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A similar study that focused on performing sentiment analysis of Tweets originating from multiple countries was performed by Dubey [56]. In addition to the above, several studies focused on performing sentiment analysis of Tweets about COVID-19 originating from different countries such as the United Kingdom [57][58][59][60][61][62], United States [59,60,[63][64][65][66][67], Canada [68][69][70][71][72], India [73][74][75][76][77], Australia [78][79][80], and Brazil [81][82][83].…”

Section: Recent Work That Focused On Sentiment Analysis Of Tweets Abo...mentioning

confidence: 99%

Analysis of Public Discourse on Twitter involving COVID-19 and MPox: Findings from Sentiment Analysis and Text Analysis

Thakur¹

2023

Preprint

View full text Add to dashboard Cite

Mining and analysis of the Big Data of Twitter conversations have been of significant interest to the scientific community in the fields of healthcare, epidemiology, big data, data science, computer science, and their related areas, as can be seen from several works in the last few years that focused on sentiment analysis and other forms of text analysis of Tweets related to Ebola, E-Coli, Dengue, Human papillomavirus (HPV), Middle East Respiratory Syndrome (MERS), Measles, Zika virus, H1N1, influenza-like illness, swine flu, flu, Cholera, Listeriosis, cancer, Liver Disease, Inflammatory Bowel Disease, kidney disease, lupus, Parkinson's, Diphtheria, and West Nile virus. The recent outbreaks of COVID-19 and MPox have served as "catalysts" for Twitter usage related to seeking and sharing information, views, opinions, and sentiments involving both these viruses. While there have been a few works published in the last few months that focused on performing sentiment analysis of Tweets related to either COVID-19 or MPox, none of the prior works in this field thus far involved analysis of Tweets focusing on both COVID-19 and MPox at the same time. With an aim to address this research gap, a total of 61,862 Tweets that focused on Mpox and COVID-19 simultaneously, posted between May 7, 2022, to March 3, 2023, were studied to perform sentiment analysis and text analysis. The findings of this study are manifold. First, the results of sentiment analysis show that almost half the Tweets (the actual percentage is 46.88%) had a negative sentiment. It was followed by Tweets that had a positive sentiment (31.97%) and Tweets that had a neutral sentiment (21.14%). Second, this paper presents the top 50 hashtags that were used in these Tweets. Third, it presents the top 100 most frequently used words that are featured in these Tweets. The findings of text analysis show that some of the commonly used words involved directly referring to either or both viruses. In addition to this, the presence of words such as "Polio", "Biden", "Ukraine", "HIV", "climate", and "Ebola" in the list of the top 100 most frequent words indicate that topics of conversations on Twitter in the context of COVID-19 and MPox also included a high level of interest related to other viruses, President Biden, and Ukraine. Finally, a comprehensive comparative study that involves a comparison of this work with 49 prior works in this field is presented to uphold the scientific contributions and relevance of the same.

show abstract

Section: Recent Work That Focused On Sentiment Analysis Of Tweets Abo...mentioning

confidence: 99%

Analysis of Public Discourse on Twitter involving COVID-19 and MPox: Findings from Sentiment Analysis and Text Analysis

Thakur¹

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Social media have increasingly gained popularity as platforms for individuals and communities to seek and share health information. In that regard, Twitter boasts an impressive user base of approximately 368 million monthly active individuals who share a common interest in discussing common health topics, such as COVID-19, cancer, influenza, mental health, vaccination, and smoking [1][2][3][4][5][6][7]. Although Twitter can be incredibly informative and engaging for health seekers, it can also be a breeding ground for misinformation [5].…”

Section: Introductionmentioning

confidence: 99%

“…In that regard, Twitter boasts an impressive user base of approximately 368 million monthly active individuals who share a common interest in discussing common health topics, such as COVID-19, cancer, influenza, mental health, vaccination, and smoking [1][2][3][4][5][6][7]. Although Twitter can be incredibly informative and engaging for health seekers, it can also be a breeding ground for misinformation [5]. In this context, misinformation indicates an umbrella term covering a range of false or misleading content, such as misinformation, mal-information, disinformation, fake news, and conspiracy theories [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Fluoride-Free Content on Twitter: Topic Modeling Study

Lotto¹,

Hussain²,

Kaur³

et al. 2023

J Med Internet Res

Self Cite

View full text Add to dashboard Cite

Background Although social media has the potential to spread misinformation, it can also be a valuable tool for elucidating the social factors that contribute to the onset of negative beliefs. As a result, data mining has become a widely used technique in infodemiology and infoveillance research to combat misinformation effects. On the other hand, there is a lack of studies that specifically aim to investigate misinformation about fluoride on Twitter. Web-based individual concerns on the side effects of fluoridated oral care products and tap water stimulate the emergence and propagation of convictions that boost antifluoridation activism. In this sense, a previous content analysis–driven study demonstrated that the term fluoride-free was frequently associated with antifluoridation interests. Objective This study aimed to analyze “fluoride-free” tweets regarding their topics and frequency of publication over time. Methods A total of 21,169 tweets published in English between May 2016 and May 2022 that included the keyword “fluoride-free” were retrieved by the Twitter application programming interface. Latent Dirichlet allocation (LDA) topic modeling was applied to identify the salient terms and topics. The similarity between topics was calculated through an intertopic distance map. Moreover, an investigator manually assessed a sample of tweets depicting each of the most representative word groups that determined specific issues. Lastly, additional data visualization was performed regarding the total count of each topic of fluoride-free record and its relevance over time, using Elastic Stack software. Results We identified 3 issues by applying the LDA topic modeling: “healthy lifestyle” (topic 1), “consumption of natural/organic oral care products” (topic 2), and “recommendations for using fluoride-free products/measures” (topic 3). Topic 1 was related to users’ concerns about leading a healthier lifestyle and the potential impacts of fluoride consumption, including its hypothetical toxicity. Complementarily, topic 2 was associated with users’ personal interests and perceptions of consuming natural and organic fluoride-free oral care products, whereas topic 3 was linked to users’ recommendations for using fluoride-free products (eg, switching from fluoridated toothpaste to fluoride-free alternatives) and measures (eg, consuming unfluoridated bottled water instead of fluoridated tap water), comprising the propaganda of dental products. Additionally, the count of tweets on fluoride-free content decreased between 2016 and 2019 but increased again from 2020 onward. Conclusions Public concerns toward a healthy lifestyle, including the adoption of natural and organic cosmetics, seem to be the main motivation of the recent increase of “fluoride-free” tweets, which can be boosted by the propagation of fluoride falsehoods on the web. Therefore, public health authorities, health professionals, and legislators should be aware of the spread of fluoride-free content on social media to create and implement strategies against their potential health damage for the population.

show abstract

“…Seeking information can help people to cope with uncertainty and risks accentuated by these unprecedented times [3,4]. Establishing what kind of information people encounter in their media environment on a daily basis presents a necessary first step to understanding a range of subsequent processes, such as knowledge acquisition or attitude formation [5], mental health and wellbeing [6], trust [7,8], and attitudes towards specific measures to contain the spread of the virus [5,9].…”

Section: Introductionmentioning

confidence: 99%

Covering the Crisis: Evolution of Key Topics and Actors in COVID-19 News Coverage in Switzerland

Ort¹,

Rohrbach²,

Diviani

et al. 2023

Int J Public Health

View full text Add to dashboard Cite

Objectives: The goal of this study is to map the share of COVID-related news articles over time, to investigate key subtopics and their evolution throughout the pandemic, and to identify key actors and their relationship with different aspects of the discourse around the pandemic.Methods: This study uses a large-scale automated content analysis to conduct a within-country comparison of news articles (N = 1,171,114) from two language regions of Switzerland during the first 18 months of the pandemic.Results: News media coverage of the pandemic largely mirrors key epidemiological developments in terms of the volume and content of coverage. Key actors in COVID-related reporting tend to be included in news articles that relate to their respective area of expertise.Conclusion: Balanced news coverage of the pandemic facilitates effective dissemination of pandemic-related information by health authorities.

show abstract

Public Attitudes During the Second Lockdown: Sentiment and Topic Analyses Using Tweets From Ontario, Canada

Cited by 11 publications

References 26 publications

Analysis of Public Discourse on Twitter involving COVID-19 and MPox: Findings from Sentiment Analysis and Text Analysis

Analysis of Public Discourse on Twitter involving COVID-19 and MPox: Findings from Sentiment Analysis and Text Analysis

Analysis of Fluoride-Free Content on Twitter: Topic Modeling Study

Covering the Crisis: Evolution of Key Topics and Actors in COVID-19 News Coverage in Switzerland

Contact Info

Product

Resources

About