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CHI Conference on Human Factors in Computing Systems Extended Abstracts
Explanations are well-known to improve recommender systems' transparency. These explanations may be local, explaining individual recommendations, or global, explaining the recommender model overall. Despite their widespread use, there has been little investigation into the relative benefts of the two explanation approaches. We conducted a 30-participant exploratory study and a 30-participant controlled user study with a research-paper recommender to analyze how providing local, global, or bothdoi:10.1145/3491101.3519795 fatcat:4sqgxlfbcffaddwxwucmngmquq