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論文名稱 Title |
熱門音樂預測、特徵變數趨勢及巨星現象之分析 Prediction of Potential Hit Song and The Superstar Effect Analysis using Machine Learning and Feature Variables |
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系所名稱 Department |
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畢業學年期 Year, semester |
語文別 Language |
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學位類別 Degree |
頁數 Number of pages |
64 |
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研究生 Author |
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指導教授 Advisor |
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召集委員 Convenor |
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口試委員 Advisory Committee |
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口試日期 Date of Exam |
2019-06-25 |
繳交日期 Date of Submission |
2019-07-09 |
關鍵字 Keywords |
預測模型、集群分析、巨星現象、趨勢分析、熱門歌曲科學 trend analysis, cluster analysis, prediction model, superstar phenomenon, hit song science |
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統計 Statistics |
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中文摘要 |
「Hit Song Science」的出現使得熱門歌曲預測的相關研究在近年不斷出現。伴隨著音樂產業的數位化,許多音樂產品提供者如串流平台業者除了可以透過消費者使用行為之資訊來進行相關歌曲推薦,亦可利用歌曲本身特徵變數進行數據分析,輔助制定其行銷相關策略。 音樂產業價值鏈中議價能力最高者為主流音樂廠牌,以環球音樂( Universal Music)、索尼音樂(Sony Music Entertainment)以及華納音樂(Warner Music)此三大音樂廠牌及掌握了全球八成音樂版權,簽約歌手及創作者的創作過程亦受制於唱片公司之行銷策略而使得作品經常必須取決於創作及商業兩者之間,而更因為唱片公司擁有極大資源使得簽約歌手及創作者之議價能力相對較小;與此同時,獨立音樂創作者在音樂產業鏈上之議價能力更顯微薄。 本研究以趨勢分析、集群分析及預測模型分析近代熱門音樂特徵趨勢並建立預測模型。透過集群分析以輔助熱門歌曲之定義;而透過預測模型準確率之提升發現美國音樂產業具有巨星現象。因此,本研究以量化研究之結果提供音樂產業產品提供者建議以輔助其制定決策,改善不同價值鏈上個角色之議價能力,以創造音樂產業進步之原動力。 |
Abstract |
The emergence of "Hit Song Science" has led to the emergence of research on hit song predictions in recent years. Along with the digitalization of the music industry, many music product relevant providers, such as streaming platform operators, can use the information of consumer behavior to make song recommendations, and can also use the song's own characteristic variables for data analysis to boost the development of marketing related strategy. The highest power of bargaining in the music industry value chain is the mainstream music label, with the three major music labels of Universal Music, Sony Music Entertainment and Warner Music, owning the 80% of the world's music copyrights. The process of creating a song is also subject to the marketing strategy of record companies so that the works have to be limited between creation and business. Because the music label have great resources, the bargaining power of the contracted singers and creators is relatively low. At the same time, independent music creators are more meager in bargaining power in the music industry chain. This study analyzes trend of popular music features and builds prediction models. Through cluster analysis to assist the definition of hit songs, and through the improvement of the accuracy of prediction models, the US music industry has found a superstar phenomenon. Therefore, this study provides recommendations from the music industry product providers to assist them in making decisions and improving the bargaining power of different roles in different value chain’s roles to create the momentum behind the music industry's progress. |
目次 Table of Contents |
第一章 緒論 1 第二章 文獻探討 4 第一節 熱門歌曲科學 4 第二節 巨星現象 5 第三節 美國音樂產業概況 7 第三章 研究方法 12 第一節 資料來源概述 12 第二節 特徵欄位來源及定義 12 第三節 研究架構圖 16 第四節 集群分析理論 20 第五節 預測模型 21 第四章 研究結果 26 第一節 趨勢分析 26 第二節 PCC分群結果(Period, Count and Continuation, PCC) 27 第三節 模型預測結果 28 第四節 巨星現象 36 第五章 結論與建議 47 第一節 結論 47 第二節 建議 47 第六章 參考文獻 50 |
參考文獻 References |
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