UNDERSTANDING MUSIC TRACK POPULARITY IN A SOCIAL NETWORK

Thousands of music tracks are uploaded to the Internet every day through websites and social networks that focus on music. While some content has been popular for decades, some tracks that have just been released have been ignored. What makes a music track popular? Can the duration of a music track’s popularity be explained and predicted? By analysing data on the performance of a music track on the ranking charts, coupled with the creation of machine-generated music semantics constructs and a variety of other track, artist and market descriptors, this research tests a model to assess how track popularity and duration on the charts are determined. The dataset has 78,000+ track ranking observations from a streaming music service. The importance of music semantics constructs (genre, mood, instrumental, theme) for a track, and other non-musical factors, such as artist reputation and social information, are assessed. These may influence the staying power of music tracks in online social networks. The results show it is possible to explain chart popularity duration and the weekly ranking of music tracks. This research emphasizes the power of data analytics for knowledge discovery and explanation that can be achieved with a combination of machine-based and econometrics-based approaches

Universality of preference behaviors in online music-listener bipartite networks: A Big Data analysis

We investigate the formation of musical preferences of millions of users of the NetEase Cloud Music (NCM), one of the largest online music platforms in China. We combine the methods from complex networks theory and information sciences within the context of Big Data analysis to unveil statistical patterns and community structures underlying the formation and evolution of musical preference behaviors. Our analyses address the decay patterns of music influence, users' sensitivity to music, age and gender differences, and their relationship to regional economic indicators. Employing community detection in user-music bipartite networks, we identified eight major cultural communities in the population of NCM users. Female users exhibited higher within-group variability in preference behavior than males, with a major transition occurring around the age of 25. Moreveor, the musical tastes and the preference diversity measures of women were also more strongly associated with economic factors. However, in spite of the highly variable popularity of music tracks and the identified cultural and demographic differences, we observed that the evolution of musical preferences over time followed a power-law-like decaying function, and that NCM listeners showed the highest sensitivity to music released in their adolescence, peaking at the age of 13. Our findings suggest the existence of universal properties in the formation of musical tastes but also their culture-specific relationship to demographic factors, with wide-ranging implications for community detection and recommendation system design in online music platforms.Comment: 23 pages, 15 Figures, 4 Table

Physiological arousal response to differing musical genres

Music is a complex medium that has social, psychological, and physiological implications. Music elicits early emotional responses (arousal) in the sympathetic nervous system, that later become consciously recognized emotions. We investigated how music genre effects physiological arousal by measuring participant skin conductance level (SCL). Physiological responses of 19 participants (3 male, mean age 23 years) were recorded by way of the iWorx 214 Psychophysiology Teaching Kit. The stimuli were four different genres of music: classical, Dubstep, Celtic, and big band (swing). Stimuli were presented to participants in one of four counterbalanced blocks. Participants\u27 highest SCL matched their reported genre preference 31.57% of the time. Contrary to our hypothesis, participants did not have a higher SCL for their preferred music, leading us to hypothesize that people habituate to their musical preference. The most significant result was that participants were able to accurately describe their emotional arousal to a musical stimulus. Thus, participants were able to recognize their physiological reaction to musical genres

Distances in the field : mapping similarity and familiarity in the production, curation and consumption of Australian art music

This thesis provides a timely intervention in the investigation of cultural fields by employing traditional and new data analytics to expand our understanding of fields as multi-dimensional sites of production, curation and consumption. Through a case study of contemporary Australian art music, the research explores the multiple ways in which the concept of ‘distance’ contributes to how we conceive of and engage with fields of artistic practice. While the concept of distance has often been an implicit or axiomatic concern for cultural sociology, this thesis foregrounds how it can be used to analyse fields from multiple perspectives, at multiple scales of enquiry and using diverse methodologies. In doing so, it distinguishes between notions of distance in the related concepts of similarity and familiarity. In the former, the relative proximities of cultural producers can be mapped to discern and contrast the organising principles which underlie different perspectives of a field. In the latter, the degree of an individual’s familiarity with an item or genre can be included in theorisations of cultural preferences and their social dimensions. This is disrupted in a field such as Australian art music, however, as its emphasis on experimentation and innovation presents barriers to developing familiarity. Distance can be considered a defining characteristic of this field, and motivates its selection as a critical case study from which to investigate how audiences form attachments to distant musical sounds. The investigation of distance from multiple perspectives, using different scales of analysis and across a series of focal points in the lifecycle of artist practice, provides an analysis of Australian art music in terms of the tensions which emerge from these intersecting representations of the field. The singular spatial representation of ‘objective relations’ in a field, and a concern with power and domination – as found in the approach of Bourdieu – is replaced by a multiplicity of sets of relations and a concern with their organising principles and juxtapositions. The thesis argues that the actor constellations which distances produce are intimately linked to our capacity to engage with fields as discrete and knowable domains of cultural practice. Beyond our capacity to know a cultural field, it also argues for the importance of reconsidering how we form attachments to distant musical tastes. As an avant-garde genre which embraces foreign and confounding sounds, audiences require the capacity to draw on a range of consumption strategies and techniques to successfully engage with and value the unfamiliar

Predicting and Composing a Top Ten Billboard Hot 100 Single with Descriptive Analytics and Classification

In late 20th and early 21st century Western popular music, there are cyclical structures, sounds, and themes that come and go with historical trends. Not only do the production techniques utilized reflect technological advancements (the Yamaha DX7, the Roland 808, etc.), the art form reflects contemporary cultural attitudes through lyrics and stylistic choice. Through this lens, pop songs can serve as historical artifacts for their unique ability to captivate listeners based on their generally acceptable and familiar elements, both upon release and with future audiences. It raises the questions: “Can a chronological analysis of artistic choices reveal trends in songwriting and popular music composition?”; “Based on collected analysis, could forecast data suggest criteria that a future hit song may fit?”; and “How could the next ‘hit song’ sound, based on the calculated criteria from trend analysis and forecasting techniques?” By manually listening to and analyzing Billboard songs for each of the last 50 years and employing an assortment of feature selection and classification techniques, a random forest model predicts some of the significant characteristics of a potential future hit song. This prediction provided the framework for an original composition

Care for a Sample? De Minimis, Fair Use, Blockchain, and an Approach to an Affordable Music Sampling System for Independent Artists

Thanks, in part, to social media and the digital streaming age of music, independent artists have seen a rise in popularity and many musicians have achieved mainstream success without the affiliation of a major record label. Alongside the growth of independent music has come the widespread use of music sampling. Sampling, which was once depicted as a crime perpetrated by hip-hop artists, is now prevalent across charttopping hits from all genres. Artists have used sampling as a tool to integrate cultures, eras, and styles of music while experimenting with the bounds of musical creativity. Artists whose works are sampled have profited from royalties and the exposure of their original work in modern art. However, the laws that shaped the sample licensing system helped solidify financial and political obstacles that prevent independent artists from sampling. Therefore, while major label-affiliated artists can use their status and financial capital to bypass the obstacles, it is practically impossible for independent artists to afford sampling and participate in modern music’s sonic creativity