The Online Vaccine Debate: Study of A Visual Analytics System
Online debates, specifically the ones about public health issues (e.g., vaccines, medications, and nutrition), occur frequently and intensely, and are having an impact on our world. Many public health topics are debated online, one of which is the efficacy and morality of vaccines. When people exami...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-01-01
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| Series: | Informatics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9709/7/1/3 |
| _version_ | 1819147525262671872 |
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| author | Anton Ninkov Kamran Sedig |
| author_facet | Anton Ninkov Kamran Sedig |
| author_sort | Anton Ninkov |
| collection | DOAJ |
| description | Online debates, specifically the ones about public health issues (e.g., vaccines, medications, and nutrition), occur frequently and intensely, and are having an impact on our world. Many public health topics are debated online, one of which is the efficacy and morality of vaccines. When people examine such online debates, they encounter numerous and conflicting sources of information. This information forms the basis upon which people take a position on such debates. This has profound implications for public health. It necessitates a need for public health stakeholders to be able to examine online debates quickly and effectively. They should be able to easily perform sense-making tasks on the vast amount of online information, such as sentiments, online presence, focus, or geographic locations. In this paper, we report the results of a user study of a visual analytic system (VAS), and whether and how this VAS can help with such sense-making tasks. Specifically, we report a usability evaluation of VINCENT (VIsual aNalytiCs systEm for investigating the online vacciNe debaTe), a VAS previously described. To help the reader, we briefly discuss VINCENT’s design in this paper as well. VINCENT integrates webometrics, natural language processing, data visualization, and human-data interaction. In the reported study, we gave users tasks requiring them to make sense of the online vaccine debate. Thirty-four participants were asked to perform these tasks by investigating data from 37 vaccine-focused websites. Half the participants were given access to the system, while the other half were not. Selected study participants from both groups were subsequently asked to be interviewed by the study administrator. Examples of questions and issues discussed with interviewees were: how they went about completing specific tasks, what they meant by some of the feedback they provided, and how they would have performed on the tasks if they had been placed in the other group. Overall, we found that VINCENT was a highly valuable resource for users, helping them make sense of the online vaccine debate much more effectively and faster than those without the system (e.g., users were able to compare websites similarities, identify emotional tone of websites, and locate websites with a specific focus). In this paper, we also identify a few issues that should be taken into consideration when developing VASes for online public health debates. |
| first_indexed | 2024-12-22T13:31:12Z |
| format | Article |
| id | doaj.art-107b399b054448faa7cd1bf7eb2381ae |
| institution | Directory Open Access Journal |
| issn | 2227-9709 |
| language | English |
| last_indexed | 2024-12-22T13:31:12Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Informatics |
| spelling | doaj.art-107b399b054448faa7cd1bf7eb2381ae2022-12-21T18:24:10ZengMDPI AGInformatics2227-97092020-01-0171310.3390/informatics7010003informatics7010003The Online Vaccine Debate: Study of A Visual Analytics SystemAnton Ninkov0Kamran Sedig1NSIGHT Lab, Middlesex College, Western University, London, ON N6A 3K7, CanadaNSIGHT Lab, Middlesex College, Western University, London, ON N6A 3K7, CanadaOnline debates, specifically the ones about public health issues (e.g., vaccines, medications, and nutrition), occur frequently and intensely, and are having an impact on our world. Many public health topics are debated online, one of which is the efficacy and morality of vaccines. When people examine such online debates, they encounter numerous and conflicting sources of information. This information forms the basis upon which people take a position on such debates. This has profound implications for public health. It necessitates a need for public health stakeholders to be able to examine online debates quickly and effectively. They should be able to easily perform sense-making tasks on the vast amount of online information, such as sentiments, online presence, focus, or geographic locations. In this paper, we report the results of a user study of a visual analytic system (VAS), and whether and how this VAS can help with such sense-making tasks. Specifically, we report a usability evaluation of VINCENT (VIsual aNalytiCs systEm for investigating the online vacciNe debaTe), a VAS previously described. To help the reader, we briefly discuss VINCENT’s design in this paper as well. VINCENT integrates webometrics, natural language processing, data visualization, and human-data interaction. In the reported study, we gave users tasks requiring them to make sense of the online vaccine debate. Thirty-four participants were asked to perform these tasks by investigating data from 37 vaccine-focused websites. Half the participants were given access to the system, while the other half were not. Selected study participants from both groups were subsequently asked to be interviewed by the study administrator. Examples of questions and issues discussed with interviewees were: how they went about completing specific tasks, what they meant by some of the feedback they provided, and how they would have performed on the tasks if they had been placed in the other group. Overall, we found that VINCENT was a highly valuable resource for users, helping them make sense of the online vaccine debate much more effectively and faster than those without the system (e.g., users were able to compare websites similarities, identify emotional tone of websites, and locate websites with a specific focus). In this paper, we also identify a few issues that should be taken into consideration when developing VASes for online public health debates.https://www.mdpi.com/2227-9709/7/1/3public healthvisual analyticswebometricsnatural language processingvaccine debatedata visualizationhuman-data interaction |
| spellingShingle | Anton Ninkov Kamran Sedig The Online Vaccine Debate: Study of A Visual Analytics System Informatics public health visual analytics webometrics natural language processing vaccine debate data visualization human-data interaction |
| title | The Online Vaccine Debate: Study of A Visual Analytics System |
| title_full | The Online Vaccine Debate: Study of A Visual Analytics System |
| title_fullStr | The Online Vaccine Debate: Study of A Visual Analytics System |
| title_full_unstemmed | The Online Vaccine Debate: Study of A Visual Analytics System |
| title_short | The Online Vaccine Debate: Study of A Visual Analytics System |
| title_sort | online vaccine debate study of a visual analytics system |
| topic | public health visual analytics webometrics natural language processing vaccine debate data visualization human-data interaction |
| url | https://www.mdpi.com/2227-9709/7/1/3 |
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