運用社群媒體貼文預測使用者之購物傾向

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鄭筠叡(Yun-Rui Zheng) 查詢紙本館藏

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資訊管理學系

論文名稱

運用社群媒體貼文預測使用者之購物傾向
(Use of Social Media Posts to Predict User Shopping Orientation)

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摘要(中)

網路社群媒體的普及提供了消費者一個抒發消費體驗、交換對產品與服務意見的便利平台，也提供企業了解消費者心態的極佳管道。本研究運用機器學習方法分析社群媒體Instagram使用者之貼文資料，建構一套預測使用者購物傾向的模型; 使用者貼文資料包括貼文圖片、貼文內容和貼文特徵等三種類型，購物傾向類型包括市場行家、享樂購物、比較購物、物質主義、衝動購物等五種。本研究首先以問卷調查方式分析147位Instagram使用者之購物傾向，接著以隨機森林 (Random Forest)、決策樹 (Decision Trees)、支援向量機 (Support Vector Machine) 等六種機器學習演算法分析受測者的Instagram貼文資料，最後由模型來判斷受測者之購物傾向。研究結果顯示，預測模型的分類準確率介於72.3%-89.5%，具有良好之判斷能力。本研究成果有有助於企業規劃社群行銷與個人化之產品推薦。

摘要(英)

The popularity of online social media has provided consumers with convenient platforms on which they can share their consumption experiences and exchange opinions on products and services and also provided businesses with excellent channels through which they can understand the mentality of consumers. This study employed machine learning to analyze user posts on the social media, Instagram, to construct a user shopping orientation prediction model. The user post data included post image, post content, and post characteristics. The shopping orientation categories included market maven, hedonic shopping, comparison shopping, materialism, and impulse buying. We first investigated the shopping orientations of 147 Instagram users using a questionnaire and then employed five machine learning algorithms including random forest, decision trees, and support vector machine to analyze the Instagram post data of the participants. Finally, the models were utilized to determine the shopping orientations of the participants. The resulting accuracy rates of category prediction in the models ranged from 72.3% to 89.5%, which was fairly good. The results of this study can help businesses plan social media marketing and personalized product recommendations.

關鍵字(中)

★ 使用者輪廓
★ 購物傾向
★ Instagram
★ 使用者屬性建模

關鍵字(英)

★ User Profiling
★ Shopping Orientation
★ Instagram
★ User Attribute Modeling

論文目次

中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
圖目錄 vii
表目錄 viii
一、緒論 1
1-1　　研究背景 1
1-2　　研究動機 3
1-3　　研究目的 4
二、文獻探討 6
2-1　　使用者輪廓 (User Profiling) 6
2-1-1　性別 8
2-1-2　人格特質 10
2-2　　購物傾向 12
2-2-1　市場行家 (Market Maven) 12
2-2-2　享樂購物 (Hedonic Shopping) 13
2-2-3　比較購物 (Comparison Shopping) 14
2-2-4　物質主義 (Materialism) 16
2-2-5　衝動購物 (Impulse Buying) 17

三、研究方法 20
3-1　　研究設計與研究流程 20
3-1-1　資料蒐集 (Data Collection) 20
3-1-2　資料前處理 (Data Preprocessing) 21
3-1-3　資料標籤 (Data Labeling) 21
3-1-4　不平衡資料集處理 (Data Balancing) 22
3-1-5　模型訓練 (Modeling) 22
3-1-6　評估指標 (Evaluation) 22
3-2　　屬性資料篩選與處理 24
3-2-1　貼文圖片 24
3-2-2　貼文特徵 29
四、實驗結果 33
4-1　　資料描述 33
4-1-1　基本資料 33
4-1-2　信度與效度 35
4-1-3　資料平衡 37
4-1-4　屬性特徵分析 38
4-2　　分類結果評估 39
4-2-1　貼文分類結果 40
4-2-2　使用者分類結果 42
五、結論與建議 45
5-1　　研究發現 45
5-2　　研究限制與未來展望 47
參考文獻 49
附錄一購物傾向量表 56

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王培倫，「星座對於消費者在購物傾向上之影響-以大台北地區大學生為例」，國立政治大學，碩士論文，民國92年。

指導教授

許文錦(Wen-Chin Hsu)

審核日期

2021-7-5

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