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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) 
De Souza, G., Lopes, M., Fernandes, A., Leithardt, V. & Crocker, P. (2023). Comparison between sentiment analysis approaches applied to digital games. In 2023 18th Iberian Conference on Information Systems and Technologies (CISTI). Aveiro: IEEE.
Exportar Referência (IEEE) 
D. S. Adão et al.,  "Comparison between sentiment analysis approaches applied to digital games", in 2023 18th Iberian Conf. on Information Systems and Technologies (CISTI), Aveiro, IEEE, 2023
Exportar BibTeX 
@inproceedings{adão2023_1768313712364,
	author = "De Souza, G. and Lopes, M. and Fernandes, A. and Leithardt, V. and Crocker, P.",
	title = "Comparison between sentiment analysis approaches applied to digital games",
	booktitle = "2023 18th Iberian Conference on Information Systems and Technologies (CISTI)",
	year = "2023",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.23919/cisti58278.2023.10211536",
	publisher = "IEEE",
	address = "Aveiro",
	organization = "",
	url = "https://ieeexplore.ieee.org/document/10211536/authors#authors"
}
Exportar RIS 
TY  - CPAPER
TI  - Comparison between sentiment analysis approaches applied to digital games
T2  - 2023 18th Iberian Conference on Information Systems and Technologies (CISTI)
AU  - De Souza, G.
AU  - Lopes, M.
AU  - Fernandes, A.
AU  - Leithardt, V.
AU  - Crocker, P.
PY  - 2023
DO  - 10.23919/cisti58278.2023.10211536
CY  - Aveiro
UR  - https://ieeexplore.ieee.org/document/10211536/authors#authors
AB  - his article presents an analysis of sentiment classification algorithms, based on texts in Portuguese (Pt-Br) extracted from Twitter and Steam platforms, to determine which are the best Analysis Sentiment algorithms to classify user feedback in digital game contexts. On the Twitter platform, the best algorithm was Stacking with Support Vector Machine meta- classifier reaching 81.5% Accuracy. On the Steam platform, the best algorithm was Stacking with Random Forest meta-classifier reaching 82.8% Accuracy. The results show that the performance of each algorithm tends to improve when using Steam data.
ER  -