Sentiment visualization techniques are information visualization approaches that focus on representing the results of sentiment analysis and opinion mining methods. Sentiment visualization techniques have been becoming more and more popular in the past few years, as demonstrated by recent surveys. Many techniques exist, and a lot of researchers and practitioners design their own. But the question of usability of these various techniques still remains generally unsolved, as the existing research typically addresses individual design alternatives for a particular technique implementation only. Multiple surveys and evaluations exist that argue for the importance of investigating the usability of such techniques further. This work focuses on evaluating the effectiveness, and efficiency of common visual representations for low-level visualization tasks in the context of sentiment visualization. It shows what previous work has already been done by other researchers and discusses the current state of the art. It further describes a task-based user study for various tasks, carried out as an online survey and taking the task completion time and error rate into account for most questions. This study is used for evaluating sentiment visualization techniques on their usability with regard to several sentiment and emotion datasets. This study shows that each visual representation and visual variable has its own weaknesses and strengths with respect to different tasks, which can be used as guidelines for future work in this area.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-107673 |
| Date | January 2021 |
| Creators | Bouchama, Samir |
| Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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