Evaluation of opinion visualization techniques

Abstract

In this article, we are reporting the findings of a usability study of opinion mining systems' visualizations. The objectives of this study are to first to rank the visualizations of the opinion mining systems and second to identify important visualization metrics. A questionnaire survey was designed to ask users their level of agreement or disagreement about the 11 selected visualizations against a set of information visualization metrics on a Likert scale. The data were collected by conducting seminars and using a web-based online questionnaire (N = 146). The collected data were analyzed using descriptive statistics and an independent sample t-test to rank the visualizations and investigate differences between perceptions of the two groups of respondents (the participants of the seminars and the online questionnaire), respectively. The results revealed that simple, eye pleasing, easy to understand, user-friendly visualizations with less pre-knowledge required rated higher than others. It is concluded that the participants of the online questionnaire mostly required more pre-knowledge to comprehend the visualizations as compared to the participants of the seminars. The important information visualization metrics are eye pleasing, easy to understand, user-friendly, informative design, usefulness, and representation style. The results of this study could aid in the design and development of visualizations for opinion mining systems.

The State of the Art in Sentiment Visualization

“…Shamim et al . [SBT15] have already raised the issue of evaluating sentiment visualization techniques including the perception aspects—this problem presents interesting opportunities for future research.…”

“…Shamim et al . [SBT15] provide an overview of 11 techniques and classify them according to visual metaphor. However, the focus of that work is not on categorization, but rather on evaluation: the authors conduct a study to compare the techniques with regard to metrics such as user‐friendliness or usefulness.…”

“…By our estimate, that work c 2017 The Authors Computer Graphics Forum published by John Wiley & Sons Ltd. mentions around 35 peer-reviewed sentiment visualization techniques. Shamim et al [SBT15] provide an overview of 11 techniques and classify them according to visual metaphor. However, the focus of that work is not on categorization, but rather on evaluation: the authors conduct a study to compare the techniques with regard to metrics such as user-friendliness or usefulness.…”

“…The existing work investigating complex representations (for instance, [TKT*00, WBWK00, YN05]) refrains from providing exact definitions of such. Shamim et al [SBT15] have already raised the issue of evaluating sentiment visualization techniques including the perception aspects-this problem presents interesting opportunities for future research.…”

A Conceptual Knowledge Visualisation Framework for Transfer of Knowledge: An Organisational Context

“…Utilisation of recognisable and familiar visual images associated with real-world experiences, ensure that visualisation elements are recognised rather than recalled [22,39] Legend Provides the information required for clarifying and explaining the knowledge visualisation meaning and interpretation [36,[41][42][43] Knowledge transfer cognitive process…”