| 書(shū)目名稱(chēng) | Word Association Thematic Analysis | | 副標(biāo)題 | A Social Media Text | | 編輯 | Michael Thelwall | | 視頻video | http://file.papertrans.cn/1031/1030706/1030706.mp4 | | 叢書(shū)名稱(chēng) | Synthesis Lectures on Information Concepts, Retrieval, and Services | | 圖書(shū)封面 |  | | 描述 | .Many research projects involve analyzing sets of texts from the social web or elsewhere to get insights into issues, opinions, interests, news discussions, or communication styles. For example, many studies have investigated reactions to Covid-19 social distancing restrictions, conspiracy theories, and anti-vaccine sentiment on social media. This book describes word association thematic analysis, a mixed methods strategy to identify themes within a collection of social web or other texts. It identifies these themes in the differences between subsets of the texts, including female vs. male vs. nonbinary, older vs. newer, country A vs. country B, positive vs. negative sentiment, high scoring vs. low scoring, or subtopic A vs. subtopic B. It can also be used to identify the differences between a topic-focused collection of texts and a reference collection. The method starts by automatically finding words that are statistically significantly more common in one subset than another, thenidentifies the context of these words and groups them into themes. It is supported by the free Windows-based software Mozdeh for data collection or importing and for the quantitative analysis stages. Thi | | 出版日期 | Book 2021 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-02324-8 | | isbn_softcover | 978-3-031-01196-2 | | isbn_ebook | 978-3-031-02324-8Series ISSN 1947-945X Series E-ISSN 1947-9468 | | issn_series | 1947-945X | | copyright | Springer Nature Switzerland AG 2021 |
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