使用者偏好屬性對音樂發掘工具效能的影響－－以Spotify音樂串流服務為例

Evaluating Music Discovery Tools on Spotify: The Role of User Preference Characteristics

本研究以 Spotify 為研究平台，探討音樂社交軟體的使用者使用不同音樂發掘工具進行音樂欣賞時的主觀評價和客觀推薦成效，以及與使用者偏好結構之間的關係。本研究以實驗法為主，一共有26位參與者，採用拉丁方格的組內設計，每位參與者都使用了4種音 樂發掘工具（地區排行導覽工具、情境風格導覽工具、曲目電臺推薦工具、音樂追蹤導覽工具）在限定時間內探索並存取喜好的歌曲，所有參與者和系統互動的過程都以螢幕錄製 的方式記錄下來。為了能從多維度、更準確地評估音樂發掘工具之效用，我們使用了主觀 評價和客觀推薦成效兩個測量項目：（1）通過實證型的小型實驗來測量受試者之主觀評價， 自變項為 Spotify所提供的四種音樂發掘工具；中介變項為受試者的偏好結構（偏好洞見、 偏好多樣性、偏好開放性）；依變項為實驗後問卷中收集的受試者主觀評價；（2）客觀推薦 成效則由受試者在實驗中產生的曲目集合數量之比例決定，即以受測者所感興趣的曲目相較於工具所推薦的歌曲數目的比例。質化研究的部份，採用訪談法，通過實驗後對受試者進行針對性的訪談，為量化研究的結果提供檢定、補充和解釋。研究結果發現：一、不同音樂發掘工具的推薦效用的確有所差異。二、使用者面對不同音樂發掘工具時的主觀評價與客觀 推薦成效並不一致。三、使用者的個人偏好結構的確會影響音樂發掘工具的推薦效用。

An experimental study was conducted to assess the effectiveness of the four music discovery tools available on Spotify, a popular music streaming service, namely: radio recommendation, regional charts, genres and moods, as well as following Facebook friends. Both subjective judgment of user experience and objective measures of search effectiveness were used as the performance criteria. Other than comparison of these four tools, we also compared how consistent are these performance measures. The results show that user experience criteria were not necessarily corresponded to search effectiveness. Furthermore, three user preference characteristics: preference diversity, preference insight, and openness to novelty were introduced as mediating variables, with an aim to investigating how these attributes might interact with these four music discovery tools on performance. The results suggest that users' preference characteristics did have an impact on the performance of these music discovery tools.