Significance and popularity in music production

Abstract

Creative industries constantly strive for fame and popularity. Though highly desirable, popularity is not the only achievement artistic creations might ever acquire. Leaving a longstanding mark in the global production and influencing future works is an even more important achievement, usually acknowledged by experts and scholars. ‘Significant’ or ‘influential’ works are not always well known to the public or have sometimes been long forgotten by the vast majority. In this paper, we focus on the duality between what is successful and what is significant in the musical context. To this end, we consider a user-generated set of tags collected through an online music platform, whose evolving co-occurrence network mirrors the growing conceptual space underlying music production. We define a set of general metrics aiming at characterizing music albums throughout history, and their relationships with the overall musical production. We show how these metrics allow to classify albums according to their current popularity or their belonging to expert-made lists of important albums. In this way, we provide the scientific community and the public at large with quantitative tools to tell apart popular albums from culturally or aesthetically relevant artworks. The generality of the methodology presented here lends itself to be used in all those fields where innovation and creativity are in play.

Five decades of US, UK, German and Dutch music charts show that cultural processes are accelerating

“…For the UK charts, a correlation analysis between musical trends, acoustic features and chart success has been performed [8]. On a general level, the interplay between significance and popularity has been investigated for the case of online music platforms [9].…”

Cultural evolution and music

“…In the last couple of years researchers have traced the cultural transmission of music samples through networks of hip-hop and electronic producers (Youngblood, 2019a), explored how mentorship and collaboration with elites in uences the success of up-and-coming DJs (Janosov et al, 2020), and used a dynamic collaboration network to reconstruct a cultural phylogeny of electronic music (Youngblood et al, 2021). Other notable uses of network methods in research on contemporary music include mapping cover songs to determine the in uence of di erent genres on one another (Ortega, 2021), and using the position of albums in an evolving co-occurrence network of user-generated tags to understand how heterogeneity and novelty in uence popularity and cultural signi cance (Monechi et al, 2017).…”

Instagram volksonomie as komplekse netwerke

“…Gebruikergegenereerde sosiale media-inhoud het oor die afgelope jare byvoorbeeld 'n belangrike faktor geword wat verbruikersgedrag beïnvloed (Jaakonmäki, Müller en Vom Brocke 2017), en boonop het sosiale media die geleentheid geskep vir mense om self inligting te klassifiseer deur middel van hutsmerke ("hashtags"), wat die onderwerp van die huidige studie is. Shen en Wu (2005), Noruzi (2006), Cattuto et al (2007), Xamena, Brignole en Maguitman (2017) en Monechi et al (2017) verwys na die verskynsel waar mense self kategorieë aan inhoud op sosiale media toeken as volksonomie. Die term is geskep deur Van der Wal (sien Van der Wal, 2007), wat die konsep soos volg omskryf:…”

“…Soos in die inleiding gestel, ondersoekShen en Wu (2005),Cattuto et al (2007),Monechi et al (2017) en Xamena, Brignole en Maguitman (2017) volksonomienetwerke, maar nie een van hierdie studies het ondersoek ingestel na hutsmerke op Instagram nie en hulle maak gebruik van die skatting van die gemiddelde pad vir lukrake netwerke en die skatting van kleinwêreldsheid.Shen en Wu (2005) enPan et al (2016) ondersoek die netwerk van etikette op Del. icio.us ('n sosiale boekmerkplatform wat nie meer in gebruik is nie),Cattuto et al (2007) ondersoek Del.icio.us en BibSonomy ('n akademiese boekmerkplatform waar gebruikers artikels kan deel), Xamena, Brignole en Maguitman (2017) ondersoek DMOZ ('n boekmerkplatform wat nie meer in gebruik is nie),Monechi et al (2017) ondersoek Last.fm ('n musiek platform) enLi en Zhang (2020) ondersoek volksonomienetwerke op Steam ('n aanlyn platform waar mense speletjies kan deel).Die huidige studie ontleed 20 netwerke wat vanaf Instagram saamgestel is, gebruik die presiese berekening van die gemiddelde pad in lukrake netwerke, soos voorgestel deur netwerk aandui en ákñ die gemiddelde getal skakels in die netwerk (sien ook byvoorbeeldShen en Wu, 2005 en Humphries en Gurney, 2008.…”