Cargando…

Emotions and Topics Expressed on Twitter During the COVID-19 Pandemic in the United Kingdom: Comparative Geolocation and Text Mining Analysis

BACKGROUND: In recent years, the COVID-19 pandemic has brought great changes to public health, society, and the economy. Social media provide a platform for people to discuss health concerns, living conditions, and policies during the epidemic, allowing policymakers to use this content to analyze th...

Descripción completa

Detalles Bibliográficos
Autores principales:	Alhuzali, Hassan, Zhang, Tianlin, Ananiadou, Sophia
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	JMIR Publications 2022
Materias:	Original Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9536769/ https://www.ncbi.nlm.nih.gov/pubmed/36150046 http://dx.doi.org/10.2196/40323

Ejemplares similares

Twitter trends in #Parasitology determined by text mining and topic modelling
por: Ellis, John T., et al.
Publicado: (2023)

Text mining meets workflow: linking U-Compare with Taverna
por: Kano, Yoshinobu, et al.
Publicado: (2010)

U-Compare: share and compare text mining tools with UIMA
por: Kano, Yoshinobu, et al.
Publicado: (2009)

Text-mining-assisted biocuration workflows in Argo
por: Rak, Rafal, et al.
Publicado: (2014)

PathText: a text mining integrator for biological pathway visualizations
por: Kemper, Brian, et al.
Publicado: (2010)

The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets
por: Xu, Paiheng, et al.
Publicado: (2020)

Text Mining the History of Medicine
por: Thompson, Paul, et al.
Publicado: (2016)

A text mining analysis of human flourishing on Twitter
por: Cebral-Loureda, Manuel, et al.
Publicado: (2023)

Argo: an integrative, interactive, text mining-based workbench supporting curation
por: Rak, Rafal, et al.
Publicado: (2012)

Event-based text mining for biology and functional genomics
por: Ananiadou, Sophia, et al.
Publicado: (2015)

Text mining resources for the life sciences
por: Przybyła, Piotr, et al.
Publicado: (2016)

BioVAE: a pre-trained latent variable language model for biomedical text mining
por: Trieu, Hai-Long, et al.
Publicado: (2021)

ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials
por: Korkontzelos, Ioannis, et al.
Publicado: (2012)

Supporting the annotation of chronic obstructive pulmonary disease (COPD) phenotypes with text mining workflows
por: Fu, Xiao, et al.
Publicado: (2015)

Using text mining techniques to extract phenotypic information from the PhenoCHF corpus
por: Alnazzawi, Noha, et al.
Publicado: (2015)

Geolocated Twitter-based population mobility in Victoria, Australia, during the staged COVID-19 restrictions
por: Nguyen, Thin, et al.
Publicado: (2023)

Supporting the education evidence portal via text mining
por: Ananiadou, Sophia, et al.
Publicado: (2010)

Detecting Emotional Evolution on Twitter during the COVID-19 Pandemic Using Text Analysis
por: Cabezas, Javier, et al.
Publicado: (2021)

#Lorrydeaths: Structural Topic Modeling of Twitter Users' Attitudes About the Deaths of 39 Vietnamese Migrants to the United Kingdom
por: Than, Nga, et al.
Publicado: (2022)

Pooches on a platform: Text mining twitter for sector perceptions of dogs during a global pandemic
por: McMillan, Kirsten M., et al.
Publicado: (2023)

Investigating the Role of Nutrition in Enhancing Immunity During the COVID-19 Pandemic: Twitter Text-Mining Analysis
por: Shankar, Kavitha, et al.
Publicado: (2023)

Twitter sentiment analysis: An Arabic text mining approach based on COVID-19
por: Albahli, Saleh
Publicado: (2022)

Using text mining for study identification in systematic reviews: a systematic review of current approaches
por: O’Mara-Eves, Alison, et al.
Publicado: (2015)

A method for integrating and ranking the evidence for biochemical pathways by mining reactions from text
por: Miwa, Makoto, et al.
Publicado: (2013)

A text mining approach for CSR communication: an explorative analysis of energy firms on Twitter in the post-pandemic era
por: Mazza, Rocco, et al.
Publicado: (2022)

Applying machine learning and geolocation techniques to social media data (Twitter) to develop a resource for urban planning
por: Milusheva, Sveta, et al.
Publicado: (2021)

Geolocation in iOS
por: Allan, Alasdair
Publicado: (2012)

HTML5 Geolocation
por: Holdener, Anthony
Publicado: (2011)

Text Analysis of Evolving Emotions and Sentiments in COVID-19 Twitter Communication
por: Storey, Veda C., et al.
Publicado: (2022)

An effective short-text topic modelling with neighbourhood assistance-driven NMF in Twitter
por: Athukorala, Shalani, et al.
Publicado: (2022)

Erratum to: Using text mining for study identification in systematic reviews: a systematic review of current approaches
por: O’Mara-Eves, Alison, et al.
Publicado: (2015)

A text-mining based analysis of 100,000 tumours affecting dogs and cats in the United Kingdom
por: Rodríguez, José, et al.
Publicado: (2021)

Impact of COVID 19 on Indian Migrant Workers: Decoding Twitter Data by Text Mining
por: Misra, Pooja, et al.
Publicado: (2021)

DeepEventMine: end-to-end neural nested event extraction from biomedical texts
por: Trieu, Hai-Long, et al.
Publicado: (2020)

A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience
por: Shardlow, Matthew, et al.
Publicado: (2018)

Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data
por: Weisser, Christoph, et al.
Publicado: (2022)

Geolocation Techniques: Principles and Applications
por: Gentile, Camillo, et al.
Publicado: (2013)

Geolocation, ethics, and HIV research
por: Garett, Renee, et al.
Publicado: (2021)

How loneliness is talked about in social media during COVID-19 pandemic: Text mining of 4,492 Twitter feeds
por: Koh, Jing Xuan, et al.
Publicado: (2022)

Text Mining and Determinants of Sentiments towards the COVID-19 Vaccine Booster of Twitter Users in Malaysia
por: Ong, Song-Quan, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_ugp6730homnhmn6g7ej86clvaa