## 6 Evaluation
### Evaluation 3: Reaction Time Test on Adding Constellation Visualization Function
Results of two-way ANOVA are presented in Table 11.  
We reviewed the difference in reaction time among groups given different versions of visualization maps and six kinds of polygon questions. The visualization map-based test result revealed an \(F\)-Value of 278.387 and a \(P\)-Value of \(2\times 10^{-16}\) lower than alpha value of 0.05, leading us to discard the null hypothesis (no difference exists in reaction time to different polygon questions among groups) and adopt the alternative hypothesis (a difference exists in reaction time to different polygon questions among groups). In the polygon-based test, two-way ANOVA yielded an \(F\)-Value of 37.74 and a \(P\)-Value of \(2.16\times 10^{-9}\), lower than the threshold alpha value of 0.05. Therefore, we replaced the null hypothesis (no difference exists in reaction time among groups given different versions of polygon-based visualization) with the alternative hypothesis (a difference exists in reaction time among groups given different versions of polygon-based visualization). Finally, we analyzed the difference in reaction time among nested groups with different polygon-visualization and obtained an \(F\)-Value of 0.056 and a \(P\)-Value of 0.814, both of which were larger than the alpha value of 0.05. Thus, we accepted the null hypothesis (a difference exists in reaction time among nested groups given different versions of polygon-visualization), forgoing the alternative hypothesis (no difference exists in reaction time among nested groups given different versions of polygon-visualization). Based on ANOVA test results, we concluded that a significant difference satisfying the 95% confidence level existed among the groups provided with different versions of the visualization and among different questions of the test. In order to further delve into the makeup of such differences, a post-hoc analysis was conducted using a Boxplot. Results are shown in Figure 14.  
The post-hoc analysis using boxplot revealed that the first group's (given the first version of the visualization) reaction time in solving questions to find complex sentiment clusters was the longest. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **DF** & **Sum Sq** & **Mean Sq** & **\(F\)-Value** & **Pr(\textgreater{}F)** \\ \hline Group & 1 & 618.5 & 618.5 & 278.387 & \(2\times 10^{-16}\) ** \\ \hline Question & 1 & 83.8 & 83.8 & 37.74 & \(2.16\times 10^{-9}\) ** \\ \hline Question: Group & 1 & 0.1 & 0.1 & 0.056 & 0.814 \\ \hline Residuals & 356 & 790.9 & 2.2 & & \\ \hline \hline \end{tabular}  
* 90% Confidence level, ** 95% Confidence level.  
\end{table} 
Table 11: Results of the two-way ANOVA. Figure 13: (**upper**) First visualization: network; (**middle**) second visualization: network + MDS (**lower**) third visualization: network + MDS + constellation metaphor. They spent an average of 12.01 s to complete the task. The second group (given the second version of the visualization) took 10.41 s on average to locate the sentiment cluster, showing a reduction of 1.6 s compared to the first group. The third group (given the third version of the visualization) had the shortest reaction time in problem-solving recording, with an average of 8.8 s. Based on these results, it can be concluded that using the final visualization form which combines clustered (colored) nodes, the sentiment word MDS map, and the constellation metaphor can help users better understand the visualization relative to the first two versions while minimizing the reaction time, thereby facilitating the use of visualization.