Making Sense of Large Social Media Corpora
Moreno-Ortiz, Antonio
Produktnummer:
18e4bdc894d9064f97bc1779d1e3e7745f
Autor: | Moreno-Ortiz, Antonio |
---|---|
Themengebiete: | Open Access corpus linguistics keyword extraction natural language processing sentiment analysis social media |
Veröffentlichungsdatum: | 30.04.2024 |
EAN: | 9783031527180 |
Sprache: | Englisch |
Seitenzahl: | 192 |
Produktart: | Gebunden |
Verlag: | Springer International Publishing |
Untertitel: | Keywords, Topics, Sentiment, and Hashtags in the Coronavirus Twitter Corpus |
Produktinformationen "Making Sense of Large Social Media Corpora"
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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