歌詞與評論情感和歌曲喜愛程度之關係

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廖久緣(CHIU-YUAN LIAO) 查詢紙本館藏

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企業管理學系

論文名稱

歌詞與評論情感和歌曲喜愛程度之關係
(The relationships between sentiments of lyric and comments and the popularity of songs.)

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摘要(中)

音樂是生活中不可或缺的元素之一，不管是在開車、等公車，或者是在寫作業，我們都會忍不住想要打開行動裝置或電腦，讓自己沈浸在音樂之中。也正是對音樂的需求，才會有像Spotify、Apple Music、Kkbox和Youtube…等這些音樂平台的出現。根據2018年IFPI發表的音樂消費者洞察報告顯示，全球平均一週聽音樂的時間是17.8小時，有52%的音樂點播是以影片的形式播放，且全球有47%的音樂收聽是在YouTube上，也因此我們能看出YouTube是一個熱門且重要的音樂串流平台。
目前對於YouTube這個平台的研究，大部分是用問卷調查的方式，針對平台的使用原因以及影響使用行為的因素來進行研究，也有一些文獻是研究YouTube影片的受歡迎程度和推薦系統。據目前能力所知，沒有人研究YouTube使用者在平台上聆聽音樂後所表達的情感與平台使用行為之間的關係，因此本研究基於以下三點：首先評論可以表達情感或意見，再來按讚是一種表達情感的方式，最後按讚表示有同感，為一種虛擬移情的表現。進而探討閱聽者在聽音樂的時候，按讚行為是否會因為音樂的情感與閱聽者的情感均愈正向或均愈負向而愈多。
本研究利用情感分析來判斷歌詞與評論的情感正負向，將判斷結果依照歌詞與評論的情感正負分為四個類別，並對四個類別分別進行迴歸分析，以得到研究結果。研究結果顯示，類別一與類別四之迴歸分析結果為顯著，類別二與類別三之結果為不顯著，也就是歌詞與評論的情感均愈正向或均愈負向，按讚數愈多。

摘要(英)

Music is everywhere in our life. No matter what you do, you might pick up your mobile device or computer and turn on the music to enjoy in it. Because of the demand for music, there are many kinds of music streaming service appeared, like Spotify, Apple Music, Kkbox and YouTube. According to the 2018 Music Consumer Insight Report published by IFPI, on average consumers spend 17.8hrs listening to music each week globally, 52% of music streaming is on video streaming, and 47% of time spend on listening to on-demand music is on YouTube. Thus, we can conclude that YouTube is a popular and important music streaming platform.
Many researches about YouTube is to realize the user behavior on YouTube and why people participate on the platform. Some researches about the popularity of the videos on YouTube. Some researches are about the recommendation system. As far as I know within my ability range, there is no research about the relationship between the sentiment on comments expressed by listeners and the listener behavior on YouTube. Thus, the research we do is to know that whether the amounts of like will be more when the sentiment of the music and the sentiment of comments are all more positive or are all more negative based on the following three demonstrations : Comments can be a way to express our sentiments or opinions, Like is a kind of way to express our sentiments and is also call as virtual empathy that we have same feeling to others.
We use sentiment analysis to get the sentiments of lyrics and comments, and according to the sentiments of them to divide all data in four kinds of categories. Then, we respectively use regression analysis on four kinds of categories. In the end, the result of this research is that if the sentiments of lyrics and comments are all more positive or they are all more negative, the amounts of like will be more.

關鍵字(中)

★ 情感
★ 評論

關鍵字(英)

★ sentiment
★ comment

論文目次

摘要 I
ABSTRACT II
第一章、緒論 1
1.1 研究背景與動機 1
1.2 研究問題與目的 2
1.3 研究架構 4
第二章、文獻探討 5
2.1 YOUTUBE與音樂 5
2.2 按讚與點擊機制 7
2.3 情感分析之相關研究 9
2.3.1 情感分析字典建構 10
2.3.2 情感辨識的方法 11
2.4 線上評論情感之應用 13
2.5 中文斷詞 15
2.6 語意分析 16
第三章、研究方法 19
3.1 斷詞方法 20
3.2 情感分數計算 21
3.3 資料分類 24
3.4 資料收集 25
第四章、實驗結果 27
4.1 類別一之迴歸分析 28
4.2 類別二之迴歸分析 29
4.3 類別三之迴歸分析 30
4.4 類別四之迴歸分析 31
第五章、結論與建議 32
參考文獻 33
附錄 41

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指導教授

許秉瑜(Ping Yu Hsu)

審核日期

2019-6-21

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