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008			230412s2021 sz | s |||| 0|eng d
020			_a9783031023248
024	7		_a10.1007/978-3-031-02324-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.76.T49 _b2021 EB
100	1		_aThelwall, Mike _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687915
245	1	0	_aWord Association Thematic Analysis : _bA Social Media Text Exploration Strategy _cby Michael Thelwall
250			_a1st edition 2021
264		1	_aCham _bSpringer International Publishing _c2021
300			_a1 recurso en línea (XVII, 111 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Information Concepts Retrieval and Services _x1947-9468
505	0		_aAcknowledgments -- Introduction -- Data Collection with Mozdeh -- Word Association Detection: Term Identification -- Word Association Contextualization: Term Meaning and Context -- Word Association Thematic Analysis: Theme Detection -- Word Association Thematic Analysis Examples -- Comparison Between WATA and Other Methods -- Ethics -- Project Planning -- Summary -- References -- Author Biography.
520			_aMany 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, then identifies 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. This book explains the word association thematic analysis method, with examples, and gives practical advice for using it. It is primarily intended for social media researchers and students, although the method is applicable to any collection of short texts.
988			_aSynthesis Collection of Technology_2021
650		7	_2embne _9164483 _aEditores de texto (Programas de ordenador)
650		7	_2embne _9405024 _aMedios de comunicación social
776	0	8	_iPrinted edition: _z9783031002311
776	0	8	_iPrinted edition: _z9783031011962
776	0	8	_iPrinted edition: _z9783031034527
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02324-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b04/2023 _dz _eIG _zSI