The streaming era has introduced more than a plentitude of new cultural content-filled platforms. It introduced new ways of searching, listening, and sharing (Tepper & Hargittai, 2009), and new ways of shaping culture, identity, connections, and socialization while overcoming traditional fostering environments like parental education, peer groups, and communities (Bourdieu, 1996). While music is still highly social and can invigorate gatherings with friends and family, personal consumption has become increasingly dependent on algorithms as shapers of taste (Hesmondhalgh, 2022). In fact, competition between music platforms has shifted from content and affordability to capturing the user by focusing on their emotional needs and preferences to retain their use (Hracs & Webster, 2021). However, media-based socialization occurs, not amid consumption, but rather through online communication and exchange of content (Steigler, 2018), making sharing and taste-influencing an important part of current socialization (Vaizman, 2022).

Also affected by the streaming era, amateur musicianship became entangled with informal distant learning, which was further affected by COVID-19 social distancing. Distance has been bridged by online learning options, including communities of learning experiences and performance (Cayari, 2014, 2015; Waldron 2011, 2013). However, the abundance of “do-it-yourself” options has encouraged social detachment, dependent help-seeking opportunities, and teacher-student relationships neglections – all affecting learning abilities and possibly augmented during COVID-19 (Harpaz & Vaizman, 2023).

Socialization is at the core of learning, especially through engagement with art, via the creation of communities, and by close educational circles from family to educators (Bourdieu, 1996). Music platforms’ algorithms, as well as movie/TV ones, have affected the human influential role on the entertainment and art consumer (Vaizman, 2023). To further assess the effects of the streaming era on socialization, this study focuses on musical relationships – taste fostering as expressed by music mentoring preferences of consumers, and music consumption habits. The relations between those were explored while considering two personal characteristics – open-mindedness and savoring art.

Open-mindedness refers to a person’s mental openness to experience new things, as opposed to being involved in social actions (Soto & John, 2017). Savoring art is how Lee et al. (2021) describe a person’s tendency to appreciate art, to need it, as opposed to consuming or attending artistic events. Introduced during the pandemic, it is well suited for exploring the need for art in times of social distance (characterizing the streaming era) and the need for self-cultivation (Harpaz et al., 2023).

To the best of our knowledge, the relationship between open-mindedness and savoring art and music consumption preferences has not yet been tested. In the present study, we chose to focus on music mentoring preferences (MMP) and music consumption habits (MCH(.

MMP refers to music consumers’ tendency to rely on human vs. algorithmic music mentors, as recommenders of new content, whether passively or actively (Vaizman, 2023). MCH refers to routine conduct around music: private listening, social listening, discussing music, and attending musical events. Based on the literature suggesting that artists are open to experience (Schultz, 2022), and that music students have the tendency to prefer a network of music mentors, while non-music students rely more on algorithmic mentorship (Vaizman, 2023), hypotheses were formed under two dimensions: (1) correlations between music consumption and psychological characteristics, and (2) differences between amateur musicians and non-musicians regarding the tested variables.

1)     A positive correlation exists between both open-mindedness and savoring art, and MCH.

2)     A positive correlation exists between both open-mindedness and savoring art, and MMP, excluding Algorithmic Passive preference.

3)     Amateur musicians would score higher than non-musicians on both open-mindedness and savoring art.

4)     Amateur musicians would score higher than non-musicians on MCH and MMP.

Method Participants 495 Participants from the US were collected by Prolific, an online research platform that recruits worldwide participants for surveys. The age range varies between 18 and 39 (M age=24.5, SD=4.3). Among the participants, 193 (39%) were amateur musicians and 306 (61%) non-musicians, 49.8% were males and 46.8% were females and the other 3.4% indicated the gender as ‘other’. Measures The participants answered background questionnaires (age, SES, sex, family status, employment, amateur musicianship) and the following scales: The open-mindedness questionnaire (Soto & John, 2017), twelve-item scale, Cronbach’s α in the current sample, 0.87. Savoring art scale (Lee et al., 2021) is a six-item scale, Cronbach’s α=0.80 in the current sample. MMP questionnaire (Vaizman and Harpaz, in-press), is a 22-item scale, composed of four sub-scales describing preferences for influential figures that expose the listener to new musical content: Human Active (Proactively contacting another person to receive recommendations for new listening content, or actively using musical content recommended by another person/s); Human Passive (consuming musical content passively by exposure to music played by others in social situations); Algorithmic Active (actively using music apps to search for new content(; Algorithmic Passive (passively using music apps’ algorithmically generated suggestions without intervention). Cronbach’s α=0.92, 0.60, 0.84, 0.73, respectively. MCH questionnaire (Vaizman and Harpaz, in-press) is a 22-item scale, composed of four sub-scales describing different modes of music consumption: Private Listening, Social Listening, Discussing Music, and (attending) Musical Events. Cronbach’s α=0.84, 0.86, 0.92, 0.93, respectively. Procedure After receiving approval from the Institutional Ethics Committee, data collection was carried out in March 2023, through an online link of the research questionnaires uploaded on the Prolific platform. Participation in the study, and answering the questionnaire, took about 10 minutes. The participants received payment for filling out the questionnaires. Participation was voluntary and withdrawal from the study was optional at any time. The anonymity of the participants was fully preserved. SPSS 25 was used to analyze the findings.

The first hypothesis was confirmed when positive statistically significant correlations were found between both open-mindedness and savoring art and all sub-categories of MCH (see Tables 1 and 2 for non and amateur musicians’ correlations respectively). This suggests that being open-minded and appreciating art are related to music consumption in both private and social forms, including discussing music. At this point, it’s unclear whether the psychological characteristics affect the conduct or vice versa, whether listening with others, discussing music, and attending concerts may affect a person’s tendency toward art and open-mindedness, and further research is needed. Hypothesis two was also confirmed when positive correlations were found between both open-mindedness and savoring art and MMP, while no correlations or negative ones were found with a preference for Algorithmic Passive (see Tables 1 and 2 in the appendix). These suggest that while open-mindedness and art appreciation relate to active search and a network of mentorship, the opposite might be reflected in the preference for algorithmically generated suggestions as a form of mentorship. The differences between amateur and non-musicians were also confirmed (hypothesis 3), and partially confirmed (hypothesis 4), when the musicians’ means were significantly higher on all variables, except in the preference for algorithmic mentorship (see Table 3 in the appendix). These suggest that being a musician is related mainly to social relations regarding music listening, whether in the form of recommendations or consumption, and further support findings that connect musicianship and mentoring preferences (Vaizman, 2023). The lack of differences in preference for algorithmic suggestions might point to app use that reflects current times, but not musicianship. Further research is needed to determine the causality between the study variables, and whether other listening habits and tendencies are related to socialization and education towards art appreciation in the streaming era.

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