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Export Reference (APA) 
Gouveia, C., Di Fátima, Branco, Miranda, S., David, A. & Antunes, A. C. (2021). The many faces of racism on football: An analysis of the Facebook pages of Portuguese football clubs. ESA Research Network 28 Society and Sport MIDTERM CONFERENCE.
Export Reference (IEEE) 
C. M. Gouveia et al.,  "The many faces of racism on football: An analysis of the Facebook pages of Portuguese football clubs", in ESA Research Network 28 Society and Sport MIDTERM CONFERENCE,  Teramo , 2021
Export BibTeX 
@misc{gouveia2021_1716129075185,
	author = "Gouveia, C. and Di Fátima, Branco and Miranda, S. and David, A. and Antunes, A. C.",
	title = "The many faces of racism on football: An analysis of the Facebook pages of Portuguese football clubs",
	year = "2021",
	url = "http://www.esasocietyandsports-midtermconference.com"
}
Export RIS 
TY  - CPAPER
TI  - The many faces of racism on football: An analysis of the Facebook pages of Portuguese football clubs
T2  - ESA Research Network 28 Society and Sport MIDTERM CONFERENCE
AU  - Gouveia, C.
AU  - Di Fátima, Branco
AU  - Miranda, S.
AU  - David, A.
AU  - Antunes, A. C.
PY  - 2021
CY  -  Teramo 
UR  - http://www.esasocietyandsports-midtermconference.com
AB  - Racism has emerged in the 1970s as a major problem for the world of sports and remained until today. In the football realm, the racist behavior of fans directed towards players and/or fans of the opposing team constitutes the most common manifestations of racism usually held in the stadium. However, in the last years, racism has gone beyond these physical temples of football and has found a fertile ground on the internet. With social media, racism has gained a new nature and length, which has brought more visibility on these matters. 
The purpose of this article is to examine how Facebook is shaping the nature of racism, by specifically addressing and examining the racist features and manifestations present in the official Facebook pages of the Portuguese football clubs of the premier league.
Through the methodological approach of Network Social Analysis, this paper extracted public data via Facebook Graph API from the official fan pages of all 18 teams. The dataset has 5,064 posts by teams and more than 275,000 comments by fans, in the first three months of the competition in 2020. The analysis uses a set of Macros commands, programmed in Visual Basic code, which identifies semantic terms (words, expressions, phrases, emojis) associated with racism in the comment's dataset. The categories analysis combines quantitative (frequency) and qualitative (semantic sense) approaches. The results highlight a hate speech which is associated with specific events of the competition (e.g., team performance, match refereeing, player behaviours).
ER  -