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.

Brings together in combination a wide range of methods and techniques not normally found in a single resource Written in an accessible style, not assuming prior knowledge in the various specialized fields touched upon Includes accompanying resources (corpora and software) users can customize and use on their own data This book is open access, which means that you have free and unlimited access

Autorentext

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

Inhalt

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.