CovidEmoVis - An Interactive Visual Analytic Tool for Exploring Emotions from Twitter Data of Covid-19

Leticia Marisol Laura Ochoa; Franco Tejada-Toledo

doi:10.1007/978-3-030-66919-5_10

CovidEmoVis - An Interactive Visual Analytic Tool for Exploring Emotions from Twitter Data of Covid-19

Leticia Marisol Laura Ochoa, Franco Tejada-Toledo

Departamento Académico de Ingeniería de Sistemas e Informática

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Due to the Covid-19 pandemic, nowadays people comment a lot in Twitter expressing emotions around this. It can be very difficult to analyze and obtain information from big amounts of unstructured data, the objective of this work is the processing of high volumes of these tweets and to get a temporal visual exploration analysis of emotions through an interactive visual analytic tool from Twitter Data of Covid-19. This useful tool could help to the specialists in Psychology to know more about the emotional profile of users and the tweets posted daywise. Further it helps to see the important words of the tweets through word cloud and a two-dimensional plane graph to see the word of each tweet with its VAD (valence, arousal and dominance) scores and emotions. First we preprocessed the data to delete the stopwords, then we used a RNN (Recurrent Neural Network) to get an emotion related to the tweet, then we calculate VAD scores and fill missing emotions, this data can be visualized across this tool on a timeline interactively.

Original language	English
Title of host publication	Human-Computer Interaction - 6th Iberomarican Workshop, HCI-Collab 2020, Proceedings
Editors	Vanessa Agredo-Delgado, Pablo H. Ruiz, Vanessa Agredo-Delgado, Pablo H. Ruiz, Klinge Orlando Villalba-Condori
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	94-106
Number of pages	13
ISBN (Print)	9783030669188
DOIs	https://doi.org/10.1007/978-3-030-66919-5_10
State	Published - 2020
Event	6th Ibero-American Conference on Human-Computer Interaction, HCI-Collab 2020 - Arequipa, Peru Duration: 16 Sep 2020 → 18 Sep 2020

Publication series

Name	Communications in Computer and Information Science
Volume	1334
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	6th Ibero-American Conference on Human-Computer Interaction, HCI-Collab 2020
Country/Territory	Peru
City	Arequipa
Period	16/09/20 → 18/09/20

Bibliographical note

Funding Information:
We want to thank to the Universidad Nacional de San Agust?n de Arequipa with contract IBA 0021-2017-UNSA for supporting the research project ?Smart city: Dise?o de un Modelo conceptual para integraci?n de sistemas sectoriales en ?mbitos inteligentes: Medio Ambiente, Seguridad, Sanidad, Salud, Movilidad, Educaci?n, Econom?a y Gobierno?.

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

COVID-19
Emotion analysis
Social media text
Visual analytics

Access to Document

10.1007/978-3-030-66919-5_10

Cite this

Laura Ochoa, L. M., & Tejada-Toledo, F. (2020). CovidEmoVis - An Interactive Visual Analytic Tool for Exploring Emotions from Twitter Data of Covid-19. In V. Agredo-Delgado, P. H. Ruiz, V. Agredo-Delgado, P. H. Ruiz, & K. O. Villalba-Condori (Eds.), Human-Computer Interaction - 6th Iberomarican Workshop, HCI-Collab 2020, Proceedings (pp. 94-106). (Communications in Computer and Information Science; Vol. 1334). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-66919-5_10

Laura Ochoa, Leticia Marisol ; Tejada-Toledo, Franco. / CovidEmoVis - An Interactive Visual Analytic Tool for Exploring Emotions from Twitter Data of Covid-19. Human-Computer Interaction - 6th Iberomarican Workshop, HCI-Collab 2020, Proceedings. editor / Vanessa Agredo-Delgado ; Pablo H. Ruiz ; Vanessa Agredo-Delgado ; Pablo H. Ruiz ; Klinge Orlando Villalba-Condori. Springer Science and Business Media Deutschland GmbH, 2020. pp. 94-106 (Communications in Computer and Information Science).

@inproceedings{c866df97c9114df2b4d04e70c4b745bb,

title = "CovidEmoVis - An Interactive Visual Analytic Tool for Exploring Emotions from Twitter Data of Covid-19",

abstract = "Due to the Covid-19 pandemic, nowadays people comment a lot in Twitter expressing emotions around this. It can be very difficult to analyze and obtain information from big amounts of unstructured data, the objective of this work is the processing of high volumes of these tweets and to get a temporal visual exploration analysis of emotions through an interactive visual analytic tool from Twitter Data of Covid-19. This useful tool could help to the specialists in Psychology to know more about the emotional profile of users and the tweets posted daywise. Further it helps to see the important words of the tweets through word cloud and a two-dimensional plane graph to see the word of each tweet with its VAD (valence, arousal and dominance) scores and emotions. First we preprocessed the data to delete the stopwords, then we used a RNN (Recurrent Neural Network) to get an emotion related to the tweet, then we calculate VAD scores and fill missing emotions, this data can be visualized across this tool on a timeline interactively.",

keywords = "COVID-19, Emotion analysis, Social media text, Visual analytics",

author = "{Laura Ochoa}, {Leticia Marisol} and Franco Tejada-Toledo",

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year = "2020",

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Laura Ochoa, LM & Tejada-Toledo, F 2020, CovidEmoVis - An Interactive Visual Analytic Tool for Exploring Emotions from Twitter Data of Covid-19. in V Agredo-Delgado, PH Ruiz, V Agredo-Delgado, PH Ruiz & KO Villalba-Condori (eds), Human-Computer Interaction - 6th Iberomarican Workshop, HCI-Collab 2020, Proceedings. Communications in Computer and Information Science, vol. 1334, Springer Science and Business Media Deutschland GmbH, pp. 94-106, 6th Ibero-American Conference on Human-Computer Interaction, HCI-Collab 2020, Arequipa, Peru, 16/09/20. https://doi.org/10.1007/978-3-030-66919-5_10

CovidEmoVis - An Interactive Visual Analytic Tool for Exploring Emotions from Twitter Data of Covid-19. / Laura Ochoa, Leticia Marisol; Tejada-Toledo, Franco.
Human-Computer Interaction - 6th Iberomarican Workshop, HCI-Collab 2020, Proceedings. ed. / Vanessa Agredo-Delgado; Pablo H. Ruiz; Vanessa Agredo-Delgado; Pablo H. Ruiz; Klinge Orlando Villalba-Condori. Springer Science and Business Media Deutschland GmbH, 2020. p. 94-106 (Communications in Computer and Information Science; Vol. 1334).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - CovidEmoVis - An Interactive Visual Analytic Tool for Exploring Emotions from Twitter Data of Covid-19

AU - Laura Ochoa, Leticia Marisol

AU - Tejada-Toledo, Franco

PY - 2020

Y1 - 2020

N2 - Due to the Covid-19 pandemic, nowadays people comment a lot in Twitter expressing emotions around this. It can be very difficult to analyze and obtain information from big amounts of unstructured data, the objective of this work is the processing of high volumes of these tweets and to get a temporal visual exploration analysis of emotions through an interactive visual analytic tool from Twitter Data of Covid-19. This useful tool could help to the specialists in Psychology to know more about the emotional profile of users and the tweets posted daywise. Further it helps to see the important words of the tweets through word cloud and a two-dimensional plane graph to see the word of each tweet with its VAD (valence, arousal and dominance) scores and emotions. First we preprocessed the data to delete the stopwords, then we used a RNN (Recurrent Neural Network) to get an emotion related to the tweet, then we calculate VAD scores and fill missing emotions, this data can be visualized across this tool on a timeline interactively.

AB - Due to the Covid-19 pandemic, nowadays people comment a lot in Twitter expressing emotions around this. It can be very difficult to analyze and obtain information from big amounts of unstructured data, the objective of this work is the processing of high volumes of these tweets and to get a temporal visual exploration analysis of emotions through an interactive visual analytic tool from Twitter Data of Covid-19. This useful tool could help to the specialists in Psychology to know more about the emotional profile of users and the tweets posted daywise. Further it helps to see the important words of the tweets through word cloud and a two-dimensional plane graph to see the word of each tweet with its VAD (valence, arousal and dominance) scores and emotions. First we preprocessed the data to delete the stopwords, then we used a RNN (Recurrent Neural Network) to get an emotion related to the tweet, then we calculate VAD scores and fill missing emotions, this data can be visualized across this tool on a timeline interactively.

KW - COVID-19

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KW - Social media text

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A2 - Ruiz, Pablo H.

A2 - Villalba-Condori, Klinge Orlando

PB - Springer Science and Business Media Deutschland GmbH

T2 - 6th Ibero-American Conference on Human-Computer Interaction, HCI-Collab 2020

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Laura Ochoa LM, Tejada-Toledo F. CovidEmoVis - An Interactive Visual Analytic Tool for Exploring Emotions from Twitter Data of Covid-19. In Agredo-Delgado V, Ruiz PH, Agredo-Delgado V, Ruiz PH, Villalba-Condori KO, editors, Human-Computer Interaction - 6th Iberomarican Workshop, HCI-Collab 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 94-106. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-66919-5_10

CovidEmoVis - An Interactive Visual Analytic Tool for Exploring Emotions from Twitter Data of Covid-19

Abstract

Publication series

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Bibliographical note

Keywords

Access to Document

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