## 6 Evaluation
### Evaluation 3: Reaction Time Test on Adding Constellation Visualization Function  
**Purpose and Method of Measuring Reaction Time:** This research proceeds with a comparison between its final visualization map and previous visualization maps [6; 7; 8]. The final visualization in this study was formed by combining clustered (colored) nodes based on sentiment words, the sentiment word MDS map indicating locations of sentiments, and the constellation metaphor applied to sentiment words. This comparison test was designed to determine whether there was any difference in reaction time spent when selecting the node for each visualization. Visualizations applied in this test consisted of three different types: visualizations 1 to 3. Table 9, Table 10 and Figure 13 present further details of these types. Test subjects were divided into three groups, one for each version of the visualization. In this study, visualization scenes were divided into four quadrants. Subjects were given 30 s to observe each quadrant of the visualization. Thus, the total observation time was 120 s. Meanwhile, subjects were allowed to discover the content and structure of \"CosMovis\" freely. They were asked questions (e.g., on which part of the map is the movie cluster that stirs touching and sad feelings located?) on complex sentiments included in six polygons. Reaction time for recognizing the location of the complex sentiment was then measured. College students currently studying data visualization with \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Question** & **P-Value** & **Equal Variance** & **_T-Value_** & **P-Value** & **
\begin{tabular}{c} **P-Value/Alternative** \\ **Hypothesis Adoption** \\ \end{tabular} \\ \hline
1\_1\_1\_2 & 0.08203 & Heteroscedasticity & 4.8295 & 0.00003 ** & Adopt ** \\
2\_1\_2\_2 & 0.5064 & Heteroscedasticity & 7.2038 & 0.0000001 ** & Adopt ** \\
3\_1\_3\_2 & 0.2327 & Heteroscedasticity & 4.7609 & 0.000032 ** & Adopt ** \\
4\_1\_4\_4\_2 & 0.07771 & Heteroscedasticity & 4.3814 & 0.00011 ** & Adopt ** \\
5\_1\_5\_2 & 0.0026 & Equal variance & 4.9205 & 0.000036 ** & Adopt * \\ \hline \hline \end{tabular}  
* 90% Confidence level, ** 95% Confidence level (a: Heatmap group/b: No heatmap group)/ (Left–Right: Compare Left and Right).  
\end{table} 
Table 7: Results of the independent \(t\)-test analysis. Reproduced with permission from [8]; published by [Journal of The Korea Society of Computer and Information], 2016. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Question** & **95\% Confidence** & **Provide** & **Non-Provide** \\ \hline
1\_1\_1\_2 & 1.12855\textless{} \(\mu\) \(\leq\)2.771445 & **5.45** & 3.5 \\
2\_1\_2\_2 & 1.86879\textless{} \(\mu\) \(\leq\)3.33121 & **5.95** & 3.35 \\
3\_1\_3\_2 & 1.118809\textless{} \(\mu\) \(\leq\)2.781191 & **5.8** & 3.85 \\
4\_1\_4\_2 & 0.9908482\textless{} \(\mu\) \(\leq\)2.7091518 & **5.65** & 3.8 \\
5\_1\_5\_2 & 1.254113\textless{} \(\mu\) \(\leq\)3.045887 & **5.75** & 3.6 \\ \hline \hline \end{tabular}  
(Left–Right: Compare Left and Right).  
\end{table} 
Table 8: Details of statements with alternative hypothesis. Reproduced with permission from [8]; published by [Journal of The Korea Society of Computer and Information], 2016. **ANOVA per group:** To analyze the variance of data pertaining to multiple groups, this study conducted two-way ANOVA. Two-way ANOVA can be used when a data set is comprised of two independent variables and one dependent variable in order to verify the existence of a significant difference in variance among different groups caused by changes in an independent variable [41]. This study collected data through a closed testing method in which a series of 1:1 individual tests were undertaken. We used questionnaires and measured reaction times of the three groups that were given different versions of visualization for accurately locating the complex sentiment suggested by the six polygons.