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Making Sense of Large Social Media Corpora
Moreno-Ortiz, Antonio

Making Sense of Large Social Media Corpora

Author / Organization:
Humanities & Social Sciences Published 2024 Verification Pending

Overview & Synopsis

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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Indexed from repository: OAPEN Library (www.oapen.org)

Document Information

Document Title Making Sense of Large Social Media Corpora
Author / Organization Moreno-Ortiz, Antonio
Subject & Discipline social media
Categories Humanities & Social Sciences
Publication Year 2024
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website OAPEN Library (www.oapen.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-64499
Original Source Link Visit Source Page on www.oapen.org »