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Relatedness and Compatibility: Semantic Dimensions of the Concept of Privacy in Chinese and English Corpora.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Relatedness and Compatibility: Semantic Dimensions of the Concept of Privacy in Chinese and English Corpora./
作者:	Ma, Yuanye.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
面頁冊數:	253 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-11, Section: A.
Contained By:	Dissertations Abstracts International83-11A.
標題:	Information science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29063993
ISBN:	9798802717349

Relatedness and Compatibility: Semantic Dimensions of the Concept of Privacy in Chinese and English Corpora.
Ma, Yuanye.

Relatedness and Compatibility: Semantic Dimensions of the Concept of Privacy in Chinese and English Corpora. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 253 p.

Source: Dissertations Abstracts International, Volume: 83-11, Section: A.

Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2022.

This item must not be sold to any third party vendors.

This dissertation is a study of how privacy as an ethical concept exists in two languages: Mandarin Chinese and American English. The assumption for this dissertation is that different languages will have their own distinctive expressions and understandings when it comes to privacy. Specifically, I have proposed a cross-genre and cross-language study to include two genres of language corpora for each of the languages: social media posts and news articles. In addition, the language corpora span from 2010 to 2019, which supported an observation of how privacy-related languages may have changed and evolved over the years. I took a mixed-methods approach, by using two computational methods: semantic network analysis (SNA) and structural topic modeling (STM) for processing the natural language corpora. When it comes to labeling and interpreting the results of topic modeling, I relied on external coders for labeling and my own in-depth reading of the topic words as well as original documents to make sense of the meaning of these topics. Last but not least, based on the interpretations of topics, I proposed four semantic dimensions and used these four dimensions to come back to code all the topics to have an overall depiction of the topics across these two languages and two genres. The four semantic dimensions, though were found present in both languages, have revealed unequal presence in the two languages. Specifically, the institution dimension has much more presence in the English language; and in the Chinese language, it is the individual dimension that is frequently seen across topics in both genres. Apart from topics, this different emphasis on these two semantic dimensions (institution and individual) is also reflected through the semantic network analysis of nodes where the nodes with leading centrality scores over the years in these two languages differ. After considering the limitation of the data in this study, I conclude by arguing that overall, it is more cautious and appropriate to understand the incompatibilities by saying the two languages differ by their emphasis on different dimensions. This study is one of the first empirically-grounded intercultural explorations of the concept of privacy. It not only provides an examination of the concept as it is understood at the current time of writing but also reveals that natural language is promising to operationalize intercultural privacy research and comparative privacy research.

ISBN: 9798802717349Subjects--Topical Terms:

554358
Information science.
Subjects--Index Terms:

Privacy as ethical concept

Relatedness and Compatibility: Semantic Dimensions of the Concept of Privacy in Chinese and English Corpora.
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520 $a This dissertation is a study of how privacy as an ethical concept exists in two languages: Mandarin Chinese and American English. The assumption for this dissertation is that different languages will have their own distinctive expressions and understandings when it comes to privacy. Specifically, I have proposed a cross-genre and cross-language study to include two genres of language corpora for each of the languages: social media posts and news articles. In addition, the language corpora span from 2010 to 2019, which supported an observation of how privacy-related languages may have changed and evolved over the years. I took a mixed-methods approach, by using two computational methods: semantic network analysis (SNA) and structural topic modeling (STM) for processing the natural language corpora. When it comes to labeling and interpreting the results of topic modeling, I relied on external coders for labeling and my own in-depth reading of the topic words as well as original documents to make sense of the meaning of these topics. Last but not least, based on the interpretations of topics, I proposed four semantic dimensions and used these four dimensions to come back to code all the topics to have an overall depiction of the topics across these two languages and two genres. The four semantic dimensions, though were found present in both languages, have revealed unequal presence in the two languages. Specifically, the institution dimension has much more presence in the English language; and in the Chinese language, it is the individual dimension that is frequently seen across topics in both genres. Apart from topics, this different emphasis on these two semantic dimensions (institution and individual) is also reflected through the semantic network analysis of nodes where the nodes with leading centrality scores over the years in these two languages differ. After considering the limitation of the data in this study, I conclude by arguing that overall, it is more cautious and appropriate to understand the incompatibilities by saying the two languages differ by their emphasis on different dimensions. This study is one of the first empirically-grounded intercultural explorations of the concept of privacy. It not only provides an examination of the concept as it is understood at the current time of writing but also reveals that natural language is promising to operationalize intercultural privacy research and comparative privacy research.
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