{'fraction_non_alphanumeric': 0.0156794425087108, 'fraction_numerical': 0.002613240418118467, 'mean_word_length': 5.313186813186813, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Use of Computer Graphics and Cluster Analysis in Aiding Relational Judgment

Two experiments were conducted to investigate the use of computer graphics and cluster analysis in aiding human relational judgment. The experimental stimuli were similarity matrices from real-world data sources. The experimental tasks required subjects to detect the number of clusters or to judge the similarity between a designated pair of objects in the displayed matrix. Each matrix was either ordered randomly or arranged according to the results of cluster analysis. In the first experiment each matrix was displayed in one of four schemes: number scheme, color scheme, size scheme, or three-dimensional (3D) vertical line scheme. In the second experiment the matrices were displayed as 3D vertical lines with or without surface contour. The results indicated that the cluster-ordered displays greatly facilitated cluster detection performance in all but the 3D line scheme. Matrix ordering had no effect on the value judgment task. The perceptual compatibility principle and theories of perceptual grouping provided predictions and were tested in this experiment.