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Full-Text Articles in Business
Spotify: You Have A Hit!, Christopher E. Dawson Jr., Steve Mann, Edward Roske, Gauthier Vasseur
Spotify: You Have A Hit!, Christopher E. Dawson Jr., Steve Mann, Edward Roske, Gauthier Vasseur
SMU Data Science Review
Abstract. Over 87% of the streaming music is owned by four major record labels (Jones, 2018). Yet, the songs owned by those labels account for <1% of the total amount of music created each year. These labels are historically better at identifying talent (though this talent identification is becoming more difficult). Even though Spotify has 36% of the streaming marketing share (T4, 2021), Spotify has not been profitable because of the large licensing costs paid to the large music labels. If Spotify could identify hit songs & artists before the large labels, they would sign those artists and dramatically reduce their licensing costs. Using the Spotify API, this paper will use Spotify data on over 400K songs over the last three years for exploratory data analysis, provide descriptive statistics, perform feature selection, and develop models using LASSO and XGBOOST Classification. The research determined multiple key features and predicted with over 60% accuracy songs which were going to be a hit (defined as >90% popularity).
Automated Analysis Of Rfps Using Natural Language Processing (Nlp) For The Technology Domain, Sterling Beason, William Hinton, Yousri A. Salamah, Jordan Salsman
Automated Analysis Of Rfps Using Natural Language Processing (Nlp) For The Technology Domain, Sterling Beason, William Hinton, Yousri A. Salamah, Jordan Salsman
SMU Data Science Review
Much progress has been made in text analysis, specifically within the statistical domain of Term Frequency (TF) and Inverse Document Frequency (IDF). However, there is much room for improvement especially within the area of discovering Emerging Trends. Emerging Trend Detection Systems (ETDS) depend on ingesting a collection of textual data and TF/IDF to identify new or up-trending topics within the Corpus. However, the tremendous rate of change and the amount of digital information presents a challenge that makes it almost impossible for a human expert to spot emerging trends without relying on an automated ETD system. Since the U.S. Government …