CovidStream: Interactive Visualization of Emotions Evolution Associated with Covid-19
| Autor: | Manuel J. Ibarra, Melvin Edward Huillcen Baca, Herwin Alayn Huillcen Baca, Flor de Luz Palomino Valdivia, Yalmar Ponce Atencio, Mario Aquino Cruz |
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| Rok vydání: | 2021 |
| Předmět: |
Visual analytics
business.industry media_common.quotation_subject Emotion classification Deep learning Sentiment analysis 02 engineering and technology Visualization Sadness 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Evolution of emotion Psychology business Interactive visualization media_common Cognitive psychology |
| Zdroj: | Information Management and Big Data ISBN: 9783030762278 SIMBig |
| DOI: | 10.1007/978-3-030-76228-5_39 |
| Popis: | Since the beginning of the pandemic caused by Covid-19, the emotions of humanity have evolved abruptly, mainly for policies adopted by the governments of countries. These policies, since they have a high impact on people’s health, need feedback on people’s emotional perception and their connections with entities directly related to emotions, to have relevant information for decision making. Given the global social isolation, emotions have been expressed with higher magnitude in comments on social networks, generating a large amount of data that is a source for various investigations. The objective of this work is to design and adapt an interactive visualization tool called CovidStream, for monitoring the evolution of emotions associated with Covid-19 in Peru, for which Visual Analytics, Deep learning, and Sentiment Analysis techniques are combined. This visualization tool allows showing the evolution of the emotions associated with the Covid-19 and its relationships with three entities: persons, places, and organizations, which have an impact on emotions, all in a temporal space dimension. For the visualization of entities and emotions, Peruvian tweets extracted between January and July 2020 were used, all of them with the hashtag #Covid-19. For the classification of emotions, a recurrent neural network model with LSTM architecture was implemented, taking as training and test data the one proposed by SemEval-2018 Task1, corresponding to Spanish tweets labeled with emotions: anger, fear, joy, and sadness. |
| Databáze: | OpenAIRE |
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