{"title":"用机器学习预测热门歌曲:是否有一个先验的秘密公式?","authors":"Agha Haider Raza, Krishnadas Nanath","doi":"10.1109/DATABIA50434.2020.9190613","DOIUrl":null,"url":null,"abstract":"Thought to be an ever-changing art form, music has been a form of recreational entertainment for ages. The music industry is constantly making efforts for songs to be a hit and earn considerable revenues. It could be an interesting exercise to predict a song making it to top charts from a mathematical perspective. While several studies have looked into factors after a song is released, this research looks at apriori parameters of a song to predict the success of a song. Data sources available from multiple platforms are combined to create a dataset that has technical parameters of a song and sentimental analysis of the lyrics. Four machine learning algorithms (Logistic Regression, Decision Trees, Naïve Bayes and Random Forests) to answer the question-Is there a magical formula for the prediction of hit songs? It was found that there are elements beyond technical data points that could predict a song being hit or not. This paper takes a stand that music prediction is yet not a data science activity.","PeriodicalId":165106,"journal":{"name":"2020 International Conference on Data Science, Artificial Intelligence, and Business Analytics (DATABIA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Predicting a Hit Song with Machine Learning: Is there an apriori secret formula?\",\"authors\":\"Agha Haider Raza, Krishnadas Nanath\",\"doi\":\"10.1109/DATABIA50434.2020.9190613\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Thought to be an ever-changing art form, music has been a form of recreational entertainment for ages. The music industry is constantly making efforts for songs to be a hit and earn considerable revenues. It could be an interesting exercise to predict a song making it to top charts from a mathematical perspective. While several studies have looked into factors after a song is released, this research looks at apriori parameters of a song to predict the success of a song. Data sources available from multiple platforms are combined to create a dataset that has technical parameters of a song and sentimental analysis of the lyrics. Four machine learning algorithms (Logistic Regression, Decision Trees, Naïve Bayes and Random Forests) to answer the question-Is there a magical formula for the prediction of hit songs? It was found that there are elements beyond technical data points that could predict a song being hit or not. This paper takes a stand that music prediction is yet not a data science activity.\",\"PeriodicalId\":165106,\"journal\":{\"name\":\"2020 International Conference on Data Science, Artificial Intelligence, and Business Analytics (DATABIA)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Data Science, Artificial Intelligence, and Business Analytics (DATABIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DATABIA50434.2020.9190613\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Data Science, Artificial Intelligence, and Business Analytics (DATABIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DATABIA50434.2020.9190613","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predicting a Hit Song with Machine Learning: Is there an apriori secret formula?
Thought to be an ever-changing art form, music has been a form of recreational entertainment for ages. The music industry is constantly making efforts for songs to be a hit and earn considerable revenues. It could be an interesting exercise to predict a song making it to top charts from a mathematical perspective. While several studies have looked into factors after a song is released, this research looks at apriori parameters of a song to predict the success of a song. Data sources available from multiple platforms are combined to create a dataset that has technical parameters of a song and sentimental analysis of the lyrics. Four machine learning algorithms (Logistic Regression, Decision Trees, Naïve Bayes and Random Forests) to answer the question-Is there a magical formula for the prediction of hit songs? It was found that there are elements beyond technical data points that could predict a song being hit or not. This paper takes a stand that music prediction is yet not a data science activity.