用机器学习预测热门歌曲:是否有一个先验的秘密公式?

Agha Haider Raza, Krishnadas Nanath
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引用次数: 11

摘要

音乐被认为是一种不断变化的艺术形式,多年来一直是休闲娱乐的一种形式。音乐产业一直在努力使歌曲成为热门歌曲,并获得可观的收入。从数学的角度来预测一首歌曲能否登上排行榜榜首,可能是一个有趣的练习。虽然有几项研究着眼于歌曲发布后的因素,但这项研究着眼于歌曲的先验参数,以预测歌曲的成功。来自多个平台的可用数据源被结合起来创建一个数据集,该数据集包含歌曲的技术参数和歌词的情感分析。四种机器学习算法(逻辑回归,决策树,Naïve贝叶斯和随机森林)来回答这个问题——是否有一个神奇的公式来预测热门歌曲?研究发现,除了技术数据之外,还有一些因素可以预测一首歌曲是否会受到欢迎。本文认为音乐预测还不是一项数据科学活动。
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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.
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