厚資料(thick data)這個名詞大約在 2013 到 2014 年間被創造出來。先在網路上流傳，後來出現在管理學的評論及期刊之中。一開始，這個詞的意思是強調「質化」方法的知識建構，多是從人類學的視角出發。但這並不新。其實，「厚」的核心內涵很早就在人類學中被運用，原稱叫作厚實描述(thick description)，因此，現在使用「厚資料」一詞者，不少是從「厚描述」或「厚敘事」(thick descriptions)的人類學民族誌研究方法(ethnographic methodology)傳統來使用這個詞。可惜的是，若只是這樣從「研究方法」的角度來看這個詞，那麼「大」數據與「厚」資料，可能只是幾個世代下來「量化」與「質化」之爭的舊酒新瓶。
As a reflection and supplement to data-driven research, thick data was firstly proposed as a complementary method of using data to engage in meaning mining in 2013. Through the case of Chinese political economy, this article demonstrates how the use of thick data enables researchers to overcome the problem of data distortion. It argues that meaningful use of data sources is based on the identification of actors. In order to do so, researchers are required to answer the following two questions: Who are the actors contributing to the tendency shown by the data? What are the interests and incentives of those actors? The second question necessitates an extensive analysis, which makes sense of human behavior in relation to the data we collect.
中國大陸(Mainland China)做為社會科學學術研究對象，隨學科變遷以及兩岸情勢發展，在各時期有不同主題。承此，本文使用主題分析工具 (CATAR)，對「中國大陸研究」期刊於 1998~2015 年刊載之論文，透過論文的篇名與摘要文字，從事主題群聚(clustering)分析，藉以辨識顯著的研究主題，及其關鍵字，並以此觀察各主題發展趨勢。結果呈現出「中國大陸研究」之 473 篇文章，可歸類為七大主題，每一主題各有關鍵字。從每個主題的發表量(包括「發表..
With the rapid development of cross-strait situation, “Mainland China” as a subject of social science studies reflects different topics in different eras. This study applies an automatic content analysis tool(CATAR)to analyze the journal “Mainland China Studies”(1998-2015)to observe research trends based on clustering of the texts from the title and abstract of each journal article. The results show that the 473 articles published by the journal are clustered into seven salient topics. By publication n..
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