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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Aparício, J. T., Sequeira, J. S. de. & Costa, C. J. (2021). Emotion analysis of Portuguese political parties communication over the Covid-19 pandemic. In Rocha, A., Goncalves, R., Penalvo, F. G., & Martins, J. (Ed.), 2021 16th Iberian Conference on Information Systems and Technologies (CISTI). Chaves: IEEE.
Exportar Referência (IEEE) 
J. T. Aparicio et al.,  "Emotion analysis of Portuguese political parties communication over the Covid-19 pandemic", in 2021 16th Iberian Conf. on Information Systems and Technologies (CISTI), Rocha, A., Goncalves, R., Penalvo, F. G., & Martins, J., Ed., Chaves, IEEE, 2021
Exportar BibTeX 
@inproceedings{aparicio2021_1715023749755,
	author = "Aparício, J. T. and Sequeira, J. S. de. and Costa, C. J.",
	title = "Emotion analysis of Portuguese political parties communication over the Covid-19 pandemic",
	booktitle = "2021 16th Iberian Conference on Information Systems and Technologies (CISTI)",
	year = "2021",
	editor = "Rocha, A., Goncalves, R., Penalvo, F. G., & Martins, J.",
	volume = "",
	number = "",
	series = "",
	doi = "10.23919/CISTI52073.2021.9476557",
	publisher = "IEEE",
	address = "Chaves",
	organization = "",
	url = "https://ieeexplore.ieee.org/xpl/conhome/9476245/proceeding"
}
Exportar RIS 
TY  - CPAPER
TI  - Emotion analysis of Portuguese political parties communication over the Covid-19 pandemic
T2  - 2021 16th Iberian Conference on Information Systems and Technologies (CISTI)
AU  - Aparício, J. T.
AU  - Sequeira, J. S. de.
AU  - Costa, C. J.
PY  - 2021
SN  - 2166-0727
DO  - 10.23919/CISTI52073.2021.9476557
CY  - Chaves
UR  - https://ieeexplore.ieee.org/xpl/conhome/9476245/proceeding
AB  - In this paper, we explore the use of emotions in the Portuguese political parties' (with a seat in the Portuguese Parliament) communication as expressed by their official Twitter accounts, as of March 2020. The chosen period of our investigation is particularly interesting because political parties had a chance to communicate their views during a pandemic situation and over a period of one year. These views include possible solutions to face the crisis and their comments on the development of the whole situation. Using a standard lexicon we classified the amount of particular emotions in different tweets. Using this method we plotted the average positivity and negativity along time per party. We also analyzed the impact of each emotion to classify positivity using the present corpus. Finally, we considered some important words regarding the pandemic and their average positivity score. The analysis allows us to identify different approaches to participation in social media according to different strategies, more than political ideology.
ER  -