臺灣博碩士論文加值系統

網際網路時代下，企業日益仰賴社群網站進行招募，此外企業的網路口碑決定了雇主品牌的優劣，進而影響其招募與留任人才。近年來，職場評論網Glassdoor的出現，成為企業在招募上的新選擇，員工可在Glassdoor上對企業評論與評分，以影響企業的雇主品牌與網路口碑。

本研究以Glassdoor為研究樣本，蒐集37,000多則線上評論，並使用大數據分析軟體Python為研究分析工具，進行網路爬蟲與文字探勘。使用詞頻分析，TF-IDF關鍵字分析與隱含狄利克雷分布 (Latent Dirichlet Allocation) ，對最佳與最差企業的優缺點四個文本作主題模型與關聯性分群，研究結果得出七大類員工工作在意要素的主題模型，包含（1）工作生活平衡、（2）組織文化認同、（3）職涯發展機會、（4）薪酬福利、（5）上層管理、（6）社會心理價值、（7）顧客關係。透過本研究，期望能幫助企業做人力資源政策上的調整，以提升雇主品牌來加強未來留任與招募人才的效能。

In the era of the Internet, enterprises are increasingly relying on different types of social networking sites for recruitment. In addition, the online word-of-mouth of the enterprise determines the pros and cons of the employer brand, which becomes the key factors to affect the enterprise to recruit or retain the talent. In recent years, the emergence of Glassdoor has become a new online employment website for enterprises and employees. Through Glassdoor, employees can leave online reviews and score for their enterprises, which in turn affects the employer brand and online word-of-mouth of the enterprise.

This study used the big data analysis tool Python as the research analysis tool to extract more than 37,000 employee’s online reviews for textual analysis from Glassdoor. Using words frequency analysis, TF-IDF keywords analysis, and Latent Dirichlet Allocation to conclude topic models and relevance grouping from four texts of the best and the worst enterprises’ pros and cons reviews. The result revealed 7 key employee work-concerned factors topic: (1) work-life balance, (2) organizational culture identity, (3) career development opportunity, (4) compensation and benefits, (5) upper management, (6) social and psychological value, (7) customer relationship. Through this study, it can help enterprises to adjust their human resource strategy, which in turn can improve their employer brand in order to enhance enterprises’ future performance on talent recruitment retention.

摘要 I
Abstract II
謝誌 III
目錄 IV
圖目錄 V
表目錄 V
壹、 緒論 1
貳、 文獻回顧 2
一、 雇主品牌吸引力 2
二、 員工工作在意要素 3
三、 網路口碑對雇主品牌與員工工作在意要素之影響 5
參、 研究方法 6
一、 研究對象 6
二、 研究程序 7
三、 研究分析 7
肆、 研究結果 11
一、 高詞頻與文字雲分析結果 11
二、 TF-IDF關鍵字分析結果 14
三、 LDA 主題模型分析結果 16
伍、 結論與建議 17
一、 結論 17
二、 貢獻 17
三、 研究限制與建議 18
參考文獻 18
一、 中文文獻 18
二、 英文文獻 19
附錄一 Glassdoor 爬蟲之程式碼 22
附錄二 最佳與最差企業評論文字處理與詞頻分析 25
附錄三 百大詞頻文字雲 26
附錄四 最佳與最差企業優缺點評論之TF-IDF分析 27
附錄五 LDA主題模型 31
附錄六 最佳與最差企業名單與評論數 34
附錄七 最佳企業優點主題分群 35
附錄八 最佳企業缺點主題分群 35
附錄九 最差企業優點主題分群 36
附錄十 最差企業缺點主題分群 36

圖目錄
圖 1 Glassdoor職場評論網評論截圖說明 6
圖 2 研究流程圖 7
圖 3 LDA主題分群與文本包含字詞之不同顏色區分之範例 10
圖 4 LDA主題模型結構圖 11
圖 5 最佳企業優點前百大高詞頻 12
圖 6 最佳企業缺點前百大高詞頻 12
圖 7 最差企業優點前百大高詞頻 12
圖 8 最差企業缺點前百大高詞頻 12
圖 9 最佳與最差企業共同優缺點差異分析圖 13

表目錄
表 1 員工工作在意要素之相關文獻整理 4
表 2 員工工作在意要素六大主題分類與操作性定義 4
表 3 最佳與最差企業優缺點之前十大高詞頻 13
表 4 最佳與最差企業前十大詞頻優缺點之共同點 14
表 5 最佳與最差企業優點與缺點十大關鍵字 15
表 6 前十大高詞頻與TFIDF關鍵字之七大主題分布 16

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