Acoustic Features Influence Musical Choices Across Multiple Genres

Barone, Michael D.; Bansal, Jotthi; Woolhouse, Matthew

doi:10.3389/fpsyg.2017.00931

Cited by 9 publications

(11 citation statements)

References 41 publications

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“…), the musical is able to connect with audiences that may be less familiar with hip-hop or rap (Kajikawa, 2018). Music researchers have also established that audiences are much more likely to engage with music that shares the acoustic features of their preferred main genre (Barone et al, 2017). Further, different cultures and languages create unique communication structures, patterns and rhythms which often directly influence what is known as the prosodic patterns of speech that are then directly reflected in music from these cultural groups (Barone et al, 2017).…”

Section: Redefining Mainstream Culturementioning

confidence: 99%

Who Lives, Who Dies, Who Tells Your Story? Hamilton As A Case Study For Musical Mnemonics

Guillen¹

2022

Preprint

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The study of musical mnemonics arose as an attempt to understand why and how music triggers the human brain in such profound ways. Decades of scholarly research have uncovered the complex interplay between music and human brain processes in ways that are able to elicit unique responses, particularly in individuals suffering from neurodegenerative diseases, learning disabilities, or other sensory anomalies. Previous research has demonstrated that music has inherent structures capable of improving retention, recall, language decoding, general cognitive processes, and in some ways, intelligence. These heightened brain processes have been found to be particularly well suited in enhancing learning capabilities in academic settings. However, there is a significant gap in the literature about how musical mnemonics are employed and engaged within live entertainment, such as musicals, to create dynamic cognitive experiences, as well its applications and efficacy within learning environments (i.e., modulated history instruction supplemented with arts-based field trips)

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Section: Redefining Mainstream Culturementioning

confidence: 99%

Who Lives, Who Dies, Who Tells Your Story? Hamilton As A Case Study For Musical Mnemonics

Guillen¹

2022

Preprint

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“…Another strand of research on modeling users' music preferences leverages content features, e.g., acoustic features. It has been shown that the distribution of acoustic features of a user's preferred genre substantially influences the user's choice of music within other genres [28]. Also, acoustic features have been utilized to model users' preferences under different contextual conditions, in order to refine recommendation quality [29].…”

Section: Related Workmentioning

confidence: 99%

Support the underground: characteristics of beyond-mainstream music listeners

et al. 2021

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Music recommender systems have become an integral part of music streaming services such as Spotify and Last.fm to assist users navigating the extensive music collections offered by them. However, while music listeners interested in mainstream music are traditionally served well by music recommender systems, users interested in music beyond the mainstream (i.e., non-popular music) rarely receive relevant recommendations. In this paper, we study the characteristics of beyond-mainstream music and music listeners and analyze to what extent these characteristics impact the quality of music recommendations provided. Therefore, we create a novel dataset consisting of Last.fm listening histories of several thousand beyond-mainstream music listeners, which we enrich with additional metadata describing music tracks and music listeners. Our analysis of this dataset shows four subgroups within the group of beyond-mainstream music listeners that differ not only with respect to their preferred music but also with their demographic characteristics. Furthermore, we evaluate the quality of music recommendations that these subgroups are provided with four different recommendation algorithms where we find significant differences between the groups. Specifically, our results show a positive correlation between a subgroup’s openness towards music listened to by members of other subgroups and recommendation accuracy. We believe that our findings provide valuable insights for developing improved user models and recommendation approaches to better serve beyond-mainstream music listeners.

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“…Various metadata about users are also housed in the database, including user ID, total number of downloads and user country. Because of its size and the nature of the data it contains, the database is an excellent tool for cultural and social investigations relating to music [23][24][25][26].…”

Section: Description Of the Datamentioning

confidence: 99%

Modelling song popularity as a contagious process

2021

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Popular songs are often said to be ‘contagious’, ‘infectious’ or ‘viral’. We find that download count time series for many popular songs resemble infectious disease epidemic curves. This paper suggests infectious disease transmission models could help clarify mechanisms that contribute to the ‘spread’ of song preferences and how these mechanisms underlie song popularity. We analysed data from MixRadio, comprising song downloads through Nokia cell phones in Great Britain from 2007 to 2014. We compared the ability of the standard susceptible–infectious–recovered (SIR) epidemic model and a phenomenological (spline) model to fit download time series of popular songs. We fitted these same models to simulated epidemic time series generated by the SIR model. Song downloads are captured better by the SIR model, to the same extent that actual SIR simulations are fitted better by the SIR model than by splines. This suggests that the social processes underlying song popularity are similar to those that drive infectious disease transmission. We draw conclusions about song popularity within specific genres based on estimated SIR parameters. In particular, we argue that faster spread of preferences for Electronica songs may reflect stronger connectivity of the ‘susceptible community’, compared with the larger and broader community that listens to more common genres.

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Acoustic Features Influence Musical Choices Across Multiple Genres

Cited by 9 publications

References 41 publications

Who Lives, Who Dies, Who Tells Your Story? Hamilton As A Case Study For Musical Mnemonics

Who Lives, Who Dies, Who Tells Your Story? Hamilton As A Case Study For Musical Mnemonics

Support the underground: characteristics of beyond-mainstream music listeners

Modelling song popularity as a contagious process

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