| Summary: | 碩士 === 國立交通大學 === 工業工程與管理系所 === 102 === Abstract
A good graph drawing enables fast reading and understanding of the information represented in the graph, hence numerous scholars study the aesthetics of graph drawing. Earlier works were only limited to ask participants to interpret graph designed by scholars. Later works require participants to rearrange the nodes in the initial graph drawings in order to represent the best layout. Recent works have asked participants to draw the graphs on a tablet PC according to adjacency list and task so that it allows participants to freely express their interpretation. However, weighted vertices were not considered in recent works. Weighted vertices refer to the assignment of weights to nodes in a graph to reflect the differences in importance of each node. Weighted vertices can be applied to many real world scenarios. For example, cities can be assigned weights based on their varying levels of importance where large cities are of greater importance than small cities. Larger cities are assigned with greater weights so that it could represent the actual relationship between the cities. Therefore, the work presented here builds on the prior work and the application of weighted vertices. We not only focus on how should vertices with high-weight be presented in the graph, but also design four-part experiments to detect the occurrence of the learning effect. After completing the experiments, we discussed four aspects on the graph drawings generated by users. First, we analyze the characteristics of the final graph drawings such as edge crossings and grid drawings. Second, we analyze the process of graph creation and participants’ strategies for creating the graph. Third, we analyze the drawing preferences of participants through the questionnaires. Fourth, we divide participants into two groups according to different attributes and analyze the difference between the groups on the above aspects. The results indicate that minimizing the number of edge crossings is still the most important aesthetic for users in this work and participants prefer the aesthetic of grid drawings in the condition that weight-vertices exists in graph drawings. It suggests that two aesthetics of minimizing number of edge crossings and grid drawings should be the main consideration for designing the graph drawing software. Finally, we verified that learning effect existed apparently when participants created several graph drawings.
Keywords： Graph drawing aesthetics, vertex-weighted, learning effect, user-sketched graph drawings, visualization
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