Studying Ad Targeting with Digital Methods: The Case of Spotify

Mähler, Roger; Vonderau, Patrick

doi:10.3384/cu.2000.1525.1792212

Cited by 5 publications

(3 citation statements)

References 4 publications

(2 reference statements)

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“…To the best of our knowledge, a small number of papers are devoted to the mathematical aspects of the rankings produced by Spotify. Among these papers, we have [35,36]. A paper that studies the relationship between personality and type of music is [37].…”

Section: Resultsmentioning

confidence: 99%

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Corrected Evolutive Kendall’s τ Coefficients for Incomplete Rankings with Ties: Application to Case of Spotify Lists

Pedroche

Conejero

2020

Mathematics

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Mathematical analysis of rankings is essential for a wide range of scientific, public, and industrial applications (e.g., group decision-making, organizational methods, R&D sponsorship, recommender systems, voter systems, sports competitions, grant proposals rankings, web searchers, Internet streaming-on-demand media providers, etc.). Recently, some methods for incomplete aggregate rankings (rankings in which not all the elements are ranked) with ties, based on the classic Kendall’s tau coefficient, have been presented. We are interested in ordinal rankings (that is, we can order the elements to be the first, the second, etc.) allowing ties between the elements (e.g., two elements may be in the first position). We extend a previous coefficient for comparing a series of complete rankings with ties to two new coefficients for comparing a series of incomplete rankings with ties. We make use of the newest definitions of Kendall’s tau extensions. We also offer a theoretical result to interpret these coefficients in terms of the type of interactions that the elements of two consecutive rankings may show (e.g., they preserve their positions, cross their positions, and they are tied in one ranking but untied in the other ranking, etc.). We give some small examples to illustrate all the newly presented parameters and coefficients. We also apply our coefficients to compare some series of Spotify charts, both Top 200 and Viral 50, showing the applicability and utility of the proposed measures.

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Section: Resultsmentioning

confidence: 99%

“…n is the number of common elements, given by (9). The coefficient τ • ev is given by (35), and the coefficient τ • ev is given by (36). In analogy with (4) we can define the corresponding normalized mean strengths given by…”

Section: New Coefficients For Series Of Incomplete Rankings With Tiesmentioning

confidence: 99%

Corrected Evolutive Kendall’s τ Coefficients for Incomplete Rankings with Ties: Application to Case of Spotify Lists

Pedroche

Conejero

2020

Mathematics

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“…Its ability to analyze vast user data, like listening habits and geographic locations, has enabled the creation of targeted advertising and personalized content for users worldwide. This innovative approach not only highlights Spotify's extensive global reach but also showcases its commitment to delivering a unique and engaging listening experience across the globe [17]. Big data, search engine optimisation, influencer branding and social media marketing that Spotify currently uses enhance their brand online as well.…”

Section: Global Reachmentioning

confidence: 92%

Insights into Strengths, Weaknesses, Opportunities, and Threats of Music Streaming GiantSpotify

2024

LNEP

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Spotify, born in Sweden in 2006, has reshaped the way people consume music in the digital age. As it has grown to become a major player in the music streaming industry, understanding its position and business model becomes crucial. This paper demonstrates the broader Music application market and overview. Employing the SWOT analytical framework, this paper undertakes a comprehensive assessment of Spotify's strengths, weaknesses, opportunities, and threats. Grounded in this analysis, this paper underscores the potential of diversifying into emergent domains such as education and wellness to augment user engagement and streamline operational expenses. Under the fierce market competition, the paper emphasizes the necessity for Spotify to strengthen its differentiation strategy within the music application sphere.

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Wie technische Systeme aus uns schlau werden. Von maschineller Auslegung und Festlegung

Gransche

2021

Zusammenwirken Von Natürlicher Und Künstlicher Intelligenz

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ZusammenfassungDas Zusammenwirken von natürlicher und künstlicher Intelligenz kann aus philosophischer Perspektive als ein Fall von allgemeineren Mensch-Technik-Relationen gefasst werden. Dieser Beitrag nimmt einerseits eine solche allgemeinere Perspektive ein, betrachtet andererseits die Assistenzrelation zwischen lernenden Assistenzsystemen und Menschen als wiederum einen Fall solchen Zusammenwirkens.Dazu werden zunächst einige Begriffe abgeschritten, die die philosophische Perspektive etwa im Gegensatz zur informatischen oder psychologischen benötigt. Nach einigen handlungstheoretischen Grundlagen rückt die Perspektive auf aktuelle und im Entstehen befindliche Mensch-Technik-Relationen in den Mittelpunkt. Als ein Unterfall von Mensch-Technik-Welt-Verhältnissen hat Don Ihde die sogenannte hermeneutische Relation herausgestellt. Diese besagt: Menschen interpretieren die Welt vermittelt durch Technik. Kern des hier vorliegenden Beitrags ist die These von der Inversion dieser hermeneutischen Relation durch lernende Technik bzw. künstliche Intelligenz. Diese Inversion besagt: Technik ‚interpretiert‘ Menschen vermittelt durch Daten und arrangiert entsprechend die Welt. In beiden Relation geht es um deuten und gedeutet werden und damit immer auch um den Kampf um Deutungshoheiten.

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Studying Ad Targeting with Digital Methods: The Case of Spotify

Abstract: not available.

Cited by 5 publications

References 4 publications

Corrected Evolutive Kendall’s τ Coefficients for Incomplete Rankings with Ties: Application to Case of Spotify Lists

Corrected Evolutive Kendall’s τ Coefficients for Incomplete Rankings with Ties: Application to Case of Spotify Lists

Insights into Strengths, Weaknesses, Opportunities, and Threats of Music Streaming GiantSpotify

Wie technische Systeme aus uns schlau werden. Von maschineller Auslegung und Festlegung

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