Rozita Dara
Biographic Data
| ID | 6909953 |
|---|---|
| NAME | Rozita Dara |
| GIVEN NAMES | Rozita |
| FAMILY NAME | Dara |
| SIGNATURE | DARA R |
| AFFILIATIONS | University of Guelph |
| ORCID | 0000-0002-3728-0275 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Credibility of vaccine-related content on Twitter during Covid-19 pandemic
During national COVID-19 vaccine campaigns, people continuously engaged on Twitter to receive updates on the latest public health information, and to discuss and share their experiences. During this time, the spread of misinformation was widespread, which threatened the uptake of vaccines. It is therefore critical to understand the reasons behind vaccine misinformation and strategies to mitigate it. The current research aimed to understand the co…
Canadian Covid-19 Crisis Communication on Twitter: Mixed Methods Research Examining Tweets from Government, Politicians, and Public Health for Crisis Communication Guiding Principles and Tweet Engagem…
To foster trust on social media during a crisis, messages should implement key guiding principles, including call to action, clarity, conversational tone, compassion and empathy, correction of misinformation, and transparency. This study describes how crisis actors used guiding principles in COVID-19 tweets, and how the use of these guiding principles relates to tweet engagement. Original, English language tweets from 10 federal level government,…
Trust and Engagement on Twitter During the Management of Covid-19 Pandemic: The Effect of Gender and Position
During the COVID-19 pandemic, health and political leaders have attempted to update citizens using Twitter. Here, we examined the difference between environments that social media has provided for male/female or health/political leaders to interact with people during the COVID-19 pandemic. The comparison was made based on the content of posts and public responses to those posts as well as user-level and post-level metrics. Our findings suggest th…
Prediction of Covid-19 Waves Using Social Media and Google Search: A Case Study of the US and Canada
The ongoing COVID-19 pandemic has posed a severe threat to public health worldwide. In this study, we aimed to evaluate several digital data streams as early warning signals of COVID-19 outbreaks in Canada, the US and their provinces and states. Two types of terms including symptoms and preventive measures were used to filter Twitter and Google Trends data. We visualized and correlated the trends for each source of data against confirmed cases fo…
The Politics of Digital Agricultural Technologies: A Preliminary Review
Digital technologies are being developed and adopted across the agro‐food system, from farm to fork. Within decision‐making spaces, however, little attention is being paid to political factors arising from such technological developments. This review draws from critical social sciences to examine emerging technologies and big data systems in agriculture and assesses some key issues arising in the field. We begin with an introduction and review of…
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The Politics of Digital Agricultural Technologies: A Preliminary Review
Digital technologies are being developed and adopted across the agro‐food system, from farm to fork. Within decision‐making spaces, however, little attention is being paid to political factors arising from such technological developments. This review draws from critical social sciences to examine emerging technologies and big data systems in agriculture and assesses some key issues arising in the field. We begin with an introduction and review of…
Prediction of Covid-19 Waves Using Social Media and Google Search: A Case Study of the US and Canada
The ongoing COVID-19 pandemic has posed a severe threat to public health worldwide. In this study, we aimed to evaluate several digital data streams as early warning signals of COVID-19 outbreaks in Canada, the US and their provinces and states. Two types of terms including symptoms and preventive measures were used to filter Twitter and Google Trends data. We visualized and correlated the trends for each source of data against confirmed cases fo…
Canadian Covid-19 Crisis Communication on Twitter: Mixed Methods Research Examining Tweets from Government, Politicians, and Public Health for Crisis Communication Guiding Principles and Tweet Engagem…
To foster trust on social media during a crisis, messages should implement key guiding principles, including call to action, clarity, conversational tone, compassion and empathy, correction of misinformation, and transparency. This study describes how crisis actors used guiding principles in COVID-19 tweets, and how the use of these guiding principles relates to tweet engagement. Original, English language tweets from 10 federal level government,…
Trust and Engagement on Twitter During the Management of Covid-19 Pandemic: The Effect of Gender and Position
During the COVID-19 pandemic, health and political leaders have attempted to update citizens using Twitter. Here, we examined the difference between environments that social media has provided for male/female or health/political leaders to interact with people during the COVID-19 pandemic. The comparison was made based on the content of posts and public responses to those posts as well as user-level and post-level metrics. Our findings suggest th…
Credibility of vaccine-related content on Twitter during Covid-19 pandemic
During national COVID-19 vaccine campaigns, people continuously engaged on Twitter to receive updates on the latest public health information, and to discuss and share their experiences. During this time, the spread of misinformation was widespread, which threatened the uptake of vaccines. It is therefore critical to understand the reasons behind vaccine misinformation and strategies to mitigate it. The current research aimed to understand the co…
Medicine (4 works) · Misinformation and Its Impacts (4 works) · Political science (4 works) · Social media (4 works) · Computer Science (3 works) · Pandemic (3 works) · Public health (3 works) · Sociology (3 works) · Misinformation (2 works) · Politics (2 works)