Fr. 43.90

Making Sense of Large Social Media Corpora - Keywords, Topics, Sentiment, and Hashtags in the Coronavirus Twitter Corpus

Anglais · Livre Relié

Expédition généralement dans un délai de 6 à 7 semaines

Description

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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.

Table des matières

Chapter 1 - Introduction.- Chapter 2 Managing large Twitter datasets.- Chapter 3. Keywords.- Chapter 4. Topics.- Chapter 5. Sentiment.- Chapter 6. Entities.- Chapter 7. Other social media semantic items: hashtags and emojis.- Chapter 8. Lessons learned.

A propos de l'auteur

Antonio Moreno-Ortiz is a lecturer at the Faculty of Arts of the University of Malaga, Spain.

Résumé

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.

Détails du produit

Auteurs Antonio Moreno-Ortiz
Edition Springer, Berlin
 
Langues Anglais
Format d'édition Livre Relié
Sortie 30.04.2024
 
EAN 9783031527180
ISBN 978-3-0-3152718-0
Pages 192
Dimensions 148 mm x 14 mm x 210 mm
Poids 360 g
Illustrations XII, 192 p. 105 illus., 102 illus. in color.
Catégories Sciences humaines, art, musique > Linguistique et littérature > Linguistique générale et comparée

Kommunikationswissenschaft, Social Media, Sentiment Analysis, Medienwissenschaften, Open Access, Applied Linguistics, Natural Language Processing, Research Methods in Language and Linguistics, Corpus Linguistics, Health Communication, keyword extraction

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