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oapen-20.500.12657-904212024-05-24T02:23:07Z Making Sense of Large Social Media Corpora Moreno-Ortiz, Antonio social media keyword extraction corpus linguistics natural language processing sentiment analysis thema EDItEUR::C Language and Linguistics::CF Linguistics thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBC Cultural and media studies::JBCT Media studies::JBCT1 Media studies: internet, digital media and society thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBC Cultural and media studies::JBCT Media studies thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GT Interdisciplinary studies::GTC Communication studies This open access book offers a comprehensive overview of available techniques and approaches to explore large social media corpora, using as an illustrative case study the Coronavirus Twitter corpus. First, the author describes in detail a number of methods, strategies, and tools that can be used to access, manage, and explore large Twitter/X corpora, including both user-friendly applications and more advanced methods that involve the use of data management skills and custom programming scripts. He goes on to show how these tools and methods are applied to explore one of the largest Twitter datasets on the COVID-19 pandemic publicly released, covering the two years when the pandemic had the strongest impact on society. Specifically, keyword extraction, topic modelling, sentiment analysis, and hashtag analysis methods are described, contrasted, and applied to extract information from the Coronavirus Twitter Corpus. The book will be of interest to students and researchers in fields that make use of big data to address societal and linguistic concerns, including corpus linguistics, sociology, psychology, and economics. 2024-05-23T07:47:04Z 2024-05-23T07:47:04Z 2024 book ONIX_20240523_9783031527197_15 9783031527197 9783031527180 https://library.oapen.org/handle/20.500.12657/90421 eng application/pdf n/a 978-3-031-52719-7.pdf https://link.springer.com/978-3-031-52719-7 Springer Nature Palgrave Macmillan 10.1007/978-3-031-52719-7 10.1007/978-3-031-52719-7 6c6992af-b843-4f46-859c-f6e9998e40d5 c3be253a-bbf5-4a71-9c9c-464c17e795c1 9783031527197 9783031527180 Palgrave Macmillan 192 Cham [...] open access
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This open access book offers a comprehensive overview of available techniques and approaches to explore large social media corpora, using as an illustrative case study the Coronavirus Twitter corpus. First, the author describes in detail a number of methods, strategies, and tools that can be used to access, manage, and explore large Twitter/X corpora, including both user-friendly applications and more advanced methods that involve the use of data management skills and custom programming scripts. He goes on to show how these tools and methods are applied to explore one of the largest Twitter datasets on the COVID-19 pandemic publicly released, covering the two years when the pandemic had the strongest impact on society. Specifically, keyword extraction, topic modelling, sentiment analysis, and hashtag analysis methods are described, contrasted, and applied to extract information from the Coronavirus Twitter Corpus. The book will be of interest to students and researchers in fields that make use of big data to address societal and linguistic concerns, including corpus linguistics, sociology, psychology, and economics.
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