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.
|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|
|Number of pages||13|
|State||Published - 2020|
|Event||6th Ibero-American Conference on Human-Computer Interaction, HCI-Collab 2020 - Arequipa, Peru|
Duration: 16 Sep 2020 → 18 Sep 2020
|Name||Communications in Computer and Information Science|
|Conference||6th Ibero-American Conference on Human-Computer Interaction, HCI-Collab 2020|
|Period||16/09/20 → 18/09/20|
Bibliographical noteFunding 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?.
© 2020, Springer Nature Switzerland AG.
- Emotion analysis
- Social media text
- Visual analytics