Matching Items (4)
Filtering by
- All Subjects: Copyright
- All Subjects: Spotify
- Creators: Koretz, Lora
- Creators: DiMuro, Louis
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
Music streaming services have affected the music industry from both a financial and legal standpoint. Their current business model affects stakeholders such as artists, users, and investors. These services have been scrutinized recently for their imperfect royalty distribution model. Covid-19 has made these discussions even more relevant as touring income has come to a halt for musicians and the live entertainment industry. <br/>Under the current per-stream model, it is becoming exceedingly hard for artists to make a living off of streams. This forces artists to tour heavily as well as cut corners to create what is essentially “disposable art”. Rapidly releasing multiple projects a year has become the norm for many modern artists. This paper will examine the licensing framework, royalty payout issues, and propose a solution.
ContributorsKoudssi, Zakaria Corley (Author) / Sadusky, Brian (Thesis director) / Koretz, Lora (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
The Internet has slowly over the past couple of decades has evolved greatly while also growing into its own community. Websites such as Facebook, Twitter, and even YouTube have developed their own trends, cultures, and communities. Certain people have chosen to earn their livelihood over the Internet through websites and deals with companies. In these dealings, legal matters start to take a major role as people try to review and utilize other peoples’ work to supplement their own. As a Business Law major, I aimed to delve into the legal troubles and dealings of those who wish to form a career on the website YouTube. While the intent of the work is to be informational, I will conclude with what I believe to be improvements possible for the system based on information found. With all the evidence considered, I will advocate for changes to the manual claim system by increasing human moderation as well as necessitating manual review prior to deletion of channels.
ContributorsHinchman, Troy Lemar (Author) / Koretz, Lora (Thesis director) / Forst, Bradley (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Although Spotify’s extensive library of songs are often seen broken up by “Top 100” and main lyrical genres, these categories are primarily based on popularity, artist and general mood alone. If a user wanted to create a playlist based on specific or situationally specific qualifiers from their own downloaded library, he/she would have to hand pick songs that fit the mold and create a new playlist. This is a time consuming process that may not produce the most efficient result due to human error. The objective of this project, therefore, was to develop an application to streamline this process, optimize efficiency, and fill this user need.
Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.
Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.
ContributorsDiMuro, Louis (Author) / Balasooriya, Janaka (Thesis director) / Chen, Yinong (Committee member) / Arts, Media and Engineering Sch T (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Technological advancements have provided ease and accessibility for musicians to produce, publish, and share music worldwide. However, contradictory court rulings in determining what is protected under copyright law have developed an environment where top-of-the-chart and up-and-coming artists fear their records will be liable for copyright infringement. Throughout the twelve circuit courts in the United States, various legal tests are applied to copyright infringement cases. Most courts use two specific legal tests; the Second and Ninth Circuit court tests. This thesis analyzes how copyright law is applied to music, focusing on the ambiguous legal tests of the Second and Ninth Circuit Courts. This analysis aims to outline the flaws in the current legal tests and establish a new legal test dedicated to providing structure and uniformity to copyright law and music.
ContributorsSidi, Joshua (Author) / Koretz, Lora (Thesis director) / Moore, James (Committee member) / Barrett, The Honors College (Contributor) / Dean, W.P. Carey School of Business (Contributor)
Created2022-05