應用PTT論壇文字探勘探討消費者對於網購平台的偏好之研究

隨著經濟發展與網路科技時代的來臨，實體門市逐漸轉至虛擬網路，消費者的線上購物體驗也日漸蓬勃。自2020年新冠肺炎疫情爆發後，民眾為了避免群聚感染風險，主動減少外出次數，進而帶動了消費者到網路平台上購物的意願上升。本研究以蝦皮、PChome以及MOMO此三大網路購物平台作為研究對象，透過PTT論壇在2020～2021於e-shopping與lifeismoney看板文章，運用網路爬文分析、R語言的文字探勘及正／負向詞彙分析，再以視覺化文字雲圖表呈現網路購物議題之熱門關鍵字，探究消費者對網購平台的偏好性。本研究結果顯示，「賣家」、「問題」、「優惠」為每季討論度最高的熱門詞彙，顯現出民眾對於消費體驗的感受與用最划算的方式來購買商品的想法，都有一定的在意程度。其次常出現的關鍵字還有「外套」、「洋裝」、「蝦皮」、「折扣」、「便宜」、「淘寶」、「台灣」，會依照消費者在不同季別需求出現。情感分析也顯示論壇中的正負評文章的比值，PChome（2.33）與MOMO（2.34）皆優於蝦皮（1.11）。本研究藉由詞頻分析，了解網路購物熱門關鍵字所帶給消費者以及網購經營業者的趨勢及建議。例如，可提供即將經營網路購物的潛在業者，了解網路購物的意義與優勢，增加新的行銷通路與顧客產生新的連結，以維持品牌延續及發展性。同時，近兩年疫情的發生，打亂了民眾購物的需求與管道，可以讓網路購物經營業者透過本研究分析，參考顧客對於在平台消費的關鍵決定性以及可能因素，也能避免供過於求而增加進貨成本。

關鍵字

大數據分析；文字探勘；網路購物；網路平台

並列摘要

With the advent of economic development and Internet technology, offline retail stores have gradually shifted to virtual shopping networks, and consumers' online shopping has become increasingly prosperous. Moreover, since the COVID-19 pandemic, the public has taken the initiative to reduce the number of outdoor activities, which has increased consumers' willingness to shop online. This research takes Shopee, PChome, and MOMO online platforms as the research subjects. We obtained data from 2020 to 2021 on PTT e-shopping and lifeismoney boards. In addition, we used web text crawling analysis, R data text mining and positive/negative sentiment analysis, and word cloud to determine popular keywords related to online shopping issues, and consumers' preferences for online shopping platforms are studied. The results show that "seller", "problem", and "offer" are the most discussed keywords indicating that people care about the consumer experience to a certain extent. The next most frequent keywords are "coat", "dress", "shopee", "discount", "cheap", "Taobao", and "Taiwan", which will appear according to the needs of consumers in different seasons. Based on the sentiment analysis, the consumers posted more positive articles than negatives in PChome (2.33) and MOMO (2.34) compared to Shopee (1.11). Through term frequency analysis, we can understand the trends and suggestions brought by popular keywords of online shopping to consumers and online store sellers, and also allow online store sellers to analyze the key decision concerns and the possibility of customers' behavior.

並列關鍵字

Big data analysis ； Online Shopping ； Internet platform ； Text mining

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