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Abstract

A mobile device-enabled experience sampling study was conducted in which 44 participants answered questions about their music experiences 5 times a day for 2 weeks. Data regarding 4 aspects of their music-related psychological traits-"music involvement," "musical identity," "preference diversity," and "preference openness"-were also collected through a background questionnaire. A classification of music access modes was proposed based on the circumstances that lead to a music listening experience. A mixed regression analysis revealed several significant interaction effects between psychological traits and the mode of music access on music enjoyment. Foremost among these was a positive interaction effect between preference openness and the playing of a known track triggered by musical cues, and that between preference diversity and exposure to new music played by others. Individuals with a strong musical identity tended to enjoy music played of their own volition without any apparent triggers. Furthermore, a multimodal logistic regression analysis also revealed the relationships between these psychological traits and the likelihood of different music access modes. Preference diversity significantly increased the likelihood of music listening triggered by need arousal. The results support the proposition that users' music-related psychological traits should be considered in personalized recommendation strategies.

Source

Journal of the Association for Information Science and Technology. 71(2020) no.5, S.540-552

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Abstract

To date, most studies in scientometric map and track the main topics in a knowledge domain by measuring publications in core journals or keyword searches in databases. The present study instead proposes a novel metrics in which a knowledge domain is mapped and tracked via articles that cite the same openly accessible dataset. We retrieved 1,537 journal articles citing the National Longitudinal Study of Adolescent to Adult Health (Add-Health) as the basis for an investigation of the major research topics associated with this dataset and how they evolved over time. To identify the primary research interests associated with the dataset, co-word network modularity analysis was used. Another novel aspect of this study is that it juxtaposes the research topics identified by the co-word approach with those generated by topic modeling: an approach that complements network modularity analysis, and allows for cross-referencing between the results of these two methods. Keyness analysis was also performed to identify significant keywords in different time periods, which enables tracing of research interests in Add-Health as they evolve. The methodological implications of using data citation as the basis for delineating a knowledge domain and techniques for its mapping are also discussed.

Source

Journal of the Association for Information Science and Technology. 74(2023) no.1, S.81-98

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Abstract

In response to calls for recommender systems to balance accuracy and alternative measures such as diversity and novelty, we propose that recommendation strategies should be applied adaptively according to users' preference traits. Psychological scales for "preference diversity" and "openness to novelty" were developed to measure users' willingness to accept diverse and novel recommendations, respectively. To validate the scales empirically, a user study was conducted in which 293 regular moviegoers were asked to judge a set of 220 movies representing both mainstream and "long-tail" appeals. The judgment task involved indicating and rating movies they had seen, heard of but not seen, and not known previously. Correlatoin analyses were then conducted between the participants' preference diversity and openness to novelty scores with the diversity and novelty of their past movie viewing profile and movies they had not seen before but shown interest in. Preference diversity scores were shown to be significantly related to the diversity of the movies they had seen. Higher preference diversity scores were also associated with greater diversity in favored unknown movies. Similarly, participants who scored high on the openness to novelty scale had viewed more little-known movies and were generally interested in less popular movies as well as movies that differed from those they had seen before. Implications of these psychological traits for recommendation strategies are also discussed.

Source

Journal of the Association for Information Science and Technology. 73(2022) no.9, S.1222-1235