主題模型應用：透過新聞資料分析電動車產業

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彭彥勛(Yen-Hsun Peng) 查詢紙本館藏

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工業管理研究所

論文名稱

主題模型應用：透過新聞資料分析電動車產業

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摘要(中)

現今文字探勘的技術成熟，作為新穎的管理學工具，文字探勘為定性研究帶來了更多的見解。不同於過往定性研究倚賴研究者的背景知識及主觀判斷，文字探勘有大量的資料作為研究對象，可作為質化研究與量化研究的橋樑為管理學提供了不同面向的見解及成果。
本文採用主題模型對網路上關於電動車的新聞資料進行分析，我們對新聞網站進行爬蟲擷取近十年有關電動車的資料，並搜集了電動車的銷售數量。我們透過隱含迪利克雷分佈(LDA)對爬取的新聞資料進行建模並取得文件的主題分佈, 並比較兩個地區的隨時間推移的主題分佈，我們同時也對主題的分佈及電動車新車比例進行斯皮爾曼等級相關係數的分析，找出潛在的主題中與電動車銷量之間的關係。
實驗結果顯示政策、充電與自動駕駛相關議題的主題分佈與電動車新車比例呈現顯著的負相關，同時我們也在實驗中捕捉到疫情與電動車的發展並無顯著的關係、半導體與電動車新車比例呈現高度的正相關，顯示台灣半導體在電動車產業中將扮演不可忽視的角色。

摘要(英)

The text mining technique is mature and widely applied on management nowadays. As an advanced tool of management, text mining brings us more insight. Different from the previous qualitative research that relies on the background knowledge and subjective judgment of researchers, text mining has a large amount of data as the research object, which can be used as a bridge between qualitative research and quantitative research to provide management with different perspectives and results.
We use topic modeling to analysis the news about electric vehicle on the website. We crawl the news about EVs in recent ten years. We model the texture data and obtain the topic distribution of the document through the Latent Dirichlet Distribution (LDA), and compare the topic distribution over time in Taiwan and USA. We also analyze the topic distribution and the number of EV sales. Spearman’s rank correlation coefficient analysis was performed to find the relationship between potential themes and EV sales.
The results show that the correlation between three topic frames and the proportion of electric vehicle is negative significantly, they are policy, autonomous and charging issue. Meanwhile we find other topic related to the industry of EV; the impact of Covid -19 doesn’t affect the EV sales and the topics of semiconductor are highly positive correlated to proportion of EV sales.

關鍵字(中)

★ 電動車
★ 主題模型
★ 隱含狄利克雷分佈
★ 非監督式學習
★ 斯皮爾曼等級相關係數

關鍵字(英)

★ Electric vehicle
★ Topic modeling
★ Latent Dirichlet Allocation
★ Unsupervised machine learning
★ Spearman’s rank correlation coefficient

論文目次

中文摘要 ....................................................................................................................I ABSTRACT ..................................................................................................................II 目錄 ..........................................................................................................................III 第一章緒論 .............................................................................................................1
1-1 研究背景與動機.............................................................................................1 1-2 研究目的.........................................................................................................2 1-3 研究架構.........................................................................................................2
第二章文獻探討......................................................................................................3
2-1 電動車發展與現況 .........................................................................................3 2-2 自然語言處理與資料預處理..........................................................................3 2-3 主題模型.........................................................................................................5 2-4 隱含狄利克雷分佈 .........................................................................................5
2-4-1 狄利克雷分佈 ........................................................................................ 6
2-4-2 隱含狄利克雷分佈前身模型.................................................................8
2-4-3 隱含狄利克雷分佈原理.......................................................................10
2-4-4 參數選擇 .............................................................................................. 12
2-5 主題模型應用...............................................................................................13
第三章研究方法....................................................................................................14
3-1 實驗流程.......................................................................................................14 3-2 資料來源.......................................................................................................15 3-3 資料預處理...................................................................................................15
3-3-1 英文預處理 .......................................................................................... 15
iii
3-3-2 中文預處理 .......................................................................................... 16 3-4 LDA 模型 ........................................................................................................ 16
3-4-1 建模參數、主題數量確定 ................................................................... 17
3-4-2 生成主題分佈 ...................................................................................... 17
3-4-3 主題框架 .............................................................................................. 18
3-5 斯皮爾曼等級相關係數................................................................................20
第四章實驗成果....................................................................................................21
4-1 主題數量.......................................................................................................21 4-2 主題框架.......................................................................................................22 4-3 兩地區主題比較...........................................................................................24 4-4 主題與電動車新車掛牌數量之關係 ............................................................28
4-4-1 電動車主題框架 ..................................................................................28
4-4-2 其他主題 .............................................................................................. 29
4-5 小結 ..............................................................................................................29
第五章總結 ...........................................................................................................31 5-1 結論 ..............................................................................................................31
5-2 限制與未來展望...........................................................................................31
第六章參考文獻....................................................................................................32
外文部分 ............................................................................................................. 32 中文部分 ............................................................................................................. 33
附錄一 .................................................................................................................34 附錄二 ..................................................................................................................... 39

參考文獻

外文部分
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中文部分
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嚴建國(2022)。翻轉世界，電動車廠商經營發展策略分析—以特斯拉公司(Tesla Inc.)
為例。國立臺灣大學資訊管理組碩士論文，台北市。取自

指導教授

葉英傑(Ying-Chieh Yeh)

審核日期

2023-3-16

推文