RT Book, Whole
T1 Making Sense of Large Social Media Corpora: Keywords, Topics, Sentiment, and Hashtags in the Coronavirus Twitter Corpus.
A1 Moreno-Ortiz, Antonio Jesús
K1 Pandemia de la COVID-19, 2020-2023
K1 Medios de comunicación social
K1 Redes sociales en internet
K1 Análisis del discurso
K1 Lingüística computacional
AB 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.
PB Palgrave Macmillan
YR 2024
FD 2024-05
LK https://hdl.handle.net/10630/38803
UL https://hdl.handle.net/10630/38803
LA eng
NO Moreno-Ortiz, A. (2024). Making Sense of Large Social Media Corpora: Keywords, topics, entities, and sentiment in the Coronavirus Twitter Corpus. Palgrave Macmillan. https://doi.org/10.1007/978-3-031-52719-7
NO Ministerio de Ciencia e Innovacion
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026