{'fraction_non_alphanumeric': 0.01639344262295082, 'fraction_numerical': 0.001366120218579235, 'mean_word_length': 6.048076923076923, '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}}
Enhancing explainability of social recommendation using 2D graphs and word cloud visualizations

Explainability is an important desired property of recommendation systems. We consider a graph-based recommendation approach, which generates detailed explanations to users in the form of labelled connecting relational paths and present a visualization interface intended to convey such detailed relational information in clear and intuitive manner. As initial evaluation, we performed a user study at an academic conference, recommending participants the users may be interested to meet (using rsr.cloud). The feedbacks were enthusiastic, indicating that the proposed visualizations of relational explanations are engaging and useful.