Sports fans tend to associate themselves with a successful team (BIRGing), while disassociating themselves with unsuccessful teams (CORFing). This premise was applied to social media commentary within England’s matches against Croatia and Colombia during the 2018 Fédération Internationale de Football Association World Cup, uncovering that English fans tended to perform Basking in Reflected Glory (BIRG) when England was leading or victorious and tended to engage in Cutting Off Reflected Failure (CORF) when England was trailing or defeated. In Method 1, team identification, national identification with England, and sentiment were significantly higher when England was leading or victorious than when they were trailing or defeated. In Method 2, machine learning generated trending graphs to detect that English fans BIRGed when they scored against Colombia; they also BIRGed more frequently during the match with Croatia, peaking several times when they scored a goal, saved a goal, or took a free kick. However, even though CORFing (i.e., lower team identification, lower national identification, and lower sentiment) occurred when the opposing team scored, English fans still BIRGed when they were finally defeated by Croatia, likely a function of the stage the game took place (World Cup semifinal), indicating that England had nonetheless succeeded in the World Cup as a whole.
Atwell SeateA.MaR.IlesI.McCloskeyT.Parry-GilesS. (2017). ‘This is who we are!’: National identity construction and the 2014 FIFA World Cup. Communication & Sport, 5, 428–447.
2.
BeeC.MadrigalR. (2012). Outcomes are in the eye of the beholder. Journal of Media Psychology, 24, 143–153.
3.
BergerC. R. (1987). Communicating under uncertainty. In RoloffM. E.MillerG. R. (Eds.), Interpersonal processes: New directions in communication research (pp. 39–62). Beverly Hills, CA: Sage.
4.
BillingsA. C.BrownK. A.BrownN. A. (2013). 5,535 hours of impact: Effects of Olympic media on nationalism attitudes. Journal of Broadcasting & Electronic Media, 57, 579–595.
5.
BillingsA. C.BrownN. A.BrownK. A.Guoqing, LeemanM. A.LičenS.…RoweD. (2013). From pride to smugness and the nationalism between: Olympic media consumption effects on nationalism across the globe. Mass Communication and Society, 16, 910–932.
6.
BillingsA. C.BurchL. M.ZimmermanM. H. (2015). Fragments of us, fragments of them: Social media, nationality and US perceptions of the 2014 FIFA World Cup. Soccer & Society, 16, 726–744.
7.
BillingsA. C.DevlinM. B.BrownK. A. (2016). BIRGing with the best; CORFing for the country: Fan identification and nationalism during the 2014 FIFA World Cup. Journal of Global Sport Management, 1, 49–65.
8.
BillingsA. C.BrownK.Brown-DevlinN. (2015). Sports draped in the American flag: Impact of the 2014 Winter Olympic telecast on nationalized attitudes. Mass Communication and Society, 18, 377–398.
9.
BishopH.JaworskiA. (2003). ‘We beat’em’: Nationalism and the hegemony of homogeneity in the British press reportage of Germany versus England during Euro 2000. Discourse & Society, 14, 243–271.
10.
BoenF.VanbeselaereN.FeysJ. (2002). Behavioral consequences of fluctuating group success: An internet study of soccer-team fans. The Journal of social psychology, 142, 769–781.
11.
BollenJ.MaoH.ZengX. (2011). Twitter mood predicts the stock market. Journal of computational science, 2, 1–8.
12.
BranscombeN. R.WannD. L. (1994). Collective self‐esteem consequences of outgroup derogation when a valued social identity is on trial. European Journal of Social Psychology, 24, 641–657.
13.
CampbellR. M.JrAikenD.KentA. (2004). Beyond BIRGing and CORFing: Continuing the exploration of fan behavior. Sport Marketing Quarterly, 13.
14.
CialdiniR. B.BordenR. J.ThorneA.WalkerM. R.FreemanS.SloanL. R. (1976). Basking in reflected glory: Three (football) field studies. Journal of Personality and Social Psychology, 34, 366.
CrabbeT. (2008). Fishing for community: England fans at the 2006 FIFA World Cup. Soccer & Society, 9, 428–438.
17.
CuiG.WongM. L.LuiH. K. (2006). Machine learning for direct marketing response models: Bayesian networks with evolutionary programming. Management Science, 52, 597–612.
18.
CunninghamN. R.EastinM. S. (2017). Second screen and sports: A structural investigation into team identification and efficacy. Communication & Sport, 5, 288–310.
19.
DalakasV.MadrigalR.AndersonK. L. (2004). We are number one! The phenomenon of basking in reflected glory and its implications for sports marketing. Sports marketing and the psychology of marketing communication, 67–79.
20.
DevlinM. B.BillingsA. C. (2016). Examining the world’s game in the United States: Impact of nationalized qualities on fan identification and consumption of the 2014 FIFA World Cup. Journal of Broadcasting & Electronic Media, 60, 40–60.
21.
DhurupM. (2012). A dimensional analysis of the benefits derived from physical activity participation among university students and variation in terms of gender: Health. African Journal for Physical Health Education, Recreation and Dance, 18, 614–627.
EllingA.Van HilvoordeI.Van Den DoolR. (2014). Creating or awakening national pride through sporting success: A longitudinal study on macro effects in the Netherlands. International Review for the Sociology of Sport, 49, 129–151.
24.
FayyadU.Piatetsky-ShapiroG.SmythP. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17, 37.
25.
FunkD. C.JamesJ. (2001). The psychological continuum model: A conceptual framework for understanding an individual’s psychological connection to sport. Sport Management Review, 4, 119–150.
26.
GantzW.WennerL. A. (1995). Fanship and the television sports viewing experience. Sociology of Sport Journal, 12, 56–74.
27.
GibsonH.WillmingC.HoldnakA. (2002). “We’re Gators…not just Gator fans”: Serious leisure and University of Florida football. Journal of Leisure Research, 34, 397–425.
28.
HallmannK.BreuerC.KühnreichB. (2013). Happiness, pride and elite sporting success: What population segments gain most from national athletic achievements?Sport Management Review, 16, 226–235.
29.
HavardC. T.GrayD. P.GouldJ.SharpL. A.SchafferJ. J. (2013). Development and validation of the sport rivalry fan perception scale (SRFPS). Journal of Sport Behavior, 36.
30.
HeereB.JamesJ. D. (2007). Sports teams and their communities: Examining the influence of external group identities on team identity. Journal of Sport Management, 21, 319–337.
31.
HelderF. (1958). The psychology of interpersonal relations. New York, NY: Psychology Press.
32.
HolmesD.AlpersG. W.IsmailjiT.ClassenC.WalesT.CheastyV.…KoopmanC. (2007). Cognitive and emotional processing in narratives of women abused by intimate partners. Violence Against Women, 13, 1192–1205.
33.
HornseyM. J. (2008). Social identity theory and self‐categorization theory: A historical review. Social and Personality Psychology Compass, 2, 204–222.
34.
JensenJ. A.TurnerB. A.JamesJ.McEvoyC.SeifriedC.DeliaE.…WalshP. (2016). Forty years of BIRGing: New perspectives on Cialdini’s seminal studies. Journal of Sport Management, 30, 149–161.
35.
JoinsonA. N. (2000). Information seeking on the internet: A study of soccer fans on the WWW. Cyberpsychology and Behavior, 3, 185–190.
36.
JonesM. V.CoffeeP.SheffieldD.YangüezM.BarkerJ. B. (2012). Just a game? Changes in English and Spanish soccer fans’ emotions in the 2010 World Cup. Psychology of Sport and Exercise, 13, 162–169.
37.
KimN. S.ChalipL. (2004). Why travel to the FIFA World Cup? Effects of motives, background, interest, and constraints. Tourism Management, 25, 695–707.
KunovichR. M. (2009). The sources and consequences of national identification. American Sociological Review, 74, 573–593.
40.
LarkinB. A.FinkJ. S. (2016). Fantasy sport, FoMO, and traditional fandom: How second-screen use of social media allows fans to accommodate multiple identities. Journal of Sport Management, 30, 643–655.
41.
LevineM.ProsserA.EvansD.ReicherS. (2005). Identity and emergency intervention: How social group membership and inclusiveness of group boundaries shape helping behavior. Personality and Social Psychology Bulletin, 31, 443–453.
42.
LucasG. M.GratchJ.MalandrakisN.SzablowskiE.FesslerE.NicholsJ. (2017). GOAALLL!: Using sentiment in the world cup to explore theories of emotion. Image and Vision Computing, 65, 58–65.
43.
LutanR. (2005). Indonesia and the Asian Games: Sport, nationalism and the ‘new order’. Sport in Society, 8, 414–424.
44.
MaelF. A.AshforthB. E. (2001). Identification in work, war, sports, and religion: Contrasting the benefits and risks. Journal for the Theory of Social Behaviour, 31, 197–222.
45.
MarkmanK. D.HirtE. R. (2002). Social prediction and the “allegiance bias.”Social Cognition, 20, 58–86.
46.
MeierH. E.MutzM. (2016). Sport-related national pride in East and West Germany, 1992–2008: Persistent differences or trends toward convergence?Sage Open, 6. doi:10.1177/2158244016665893
47.
MudrickM.MillerM.AtkinD. (2016). The influence of social media on fan reactionary behaviors. Telematics and Informatics, 33, 896–903.
48.
NganH. M.PrendergastG. P.TsangA. S. (2011). Linking sports sponsorship with purchase intentions: team performance, stars, and the moderating role of team identification. European Journal of Marketing, 45, 551–566.
49.
O’ConnorB.BalasubramanyanR.RoutledgeB. R.SmithN. A. (2010). From tweets to polls: Linking text sentiment to public opinion time series. ICWSM, 11, 1–2.
50.
ObermeyerZ.EmanuelE. J. (2016). Predicting the future—Big data, machine learning, and clinical medicine. The New England journal of medicine, 375, 1216.
51.
OshimiD.HaradaM.FukuharaT. (2014). Spectators’ emotions during live sporting events: Analysis of spectators after the loss of the supported team at the 2013 FIFA Confederations Cup. Football Science, 11, 48–58.
52.
PodolerG. (2008). Nation, state and football: The Korean case. The International Journal of the History of Sport, 25, 1–17.
53.
RamosJ. (2003, December). Using TF-IDF to determine word relevance in document queries. In Proceedings of the first instructional conference on machine learning (Vol. 242, pp. 133–142). Piscataway, NJ.
54.
SebastianiF. (2002). Machine learning in automated text categorization. ACM Computing Surveys (CSUR), 34, 1–47.
SheltonJ. N.SellersR. M. (2000). Situational stability and variability in African American racial identity. Journal of Black Psychology, 26, 27–50.
57.
ShulmanS. (2004). The contours of civic and ethnic national identification in Ukraine. Europe-Asia Studies, 56, 35–56.
58.
SnyderC. R.LassegardM.FordC. E. (1986). Distancing after group success and failure: Basking in reflected glory and cutting off reflected failure. Journal of Personality and Social Psychology, 51, 382–388.
59.
SpindaJ. S. (2011). The development of basking in reflected glory (BIRGing) and cutting off reflected failure (CORFing) measures. Journal of Sport Behavior, 34, 392–420.
60.
StetsJ. E.BurkeP. J. (2000). Identity theory and social identity theory. Social Psychology Quarterly, 63, 224–237.
61.
StevensonT. B.AlaugA. K. (2008). Sports diplomacy and emergent nationalism: Football links between the two Yemens, 1970-1990. Anthropology of the Middle East, 3, 1–19.
62.
StojanovskiD.StrezoskiG.MadjarovG.DimitrovskiI. (2015, November). Emotion identification in FIFA world cup tweets using convolutional neural network. In Innovations in Information Technology (IIT), 2015 11th International Conference on IEEE, Dubai, UAE, 1-3 November 2015, pp. 52–57.
63.
SuttonW. A.McDonaldM. A.MilneG. R.CimpermanJ. (1997). Creating and fostering fan identification in professional sports. Sport Marketing Quarterly, 6, 15–22.
64.
TajfelH.TurnerJ. C. (1979). An integrative theory of intergroup conflict. In AustinW. G.WorchelS. (Eds.), The social psychology of intergroup relations (pp. 33–47). Monterey, CA: Brooks/Cole.
65.
TervoM. (2001). Nationalism, sports and gender in Finnish sports journalism in the early twentieth century. Gender, Place and Culture: A Journal of Feminist Geography, 8, 357–373.
66.
ThessenA. (2016). Adoption of machine learning techniques in ecology and earth science. One Ecosystem, 1, e8621.
67.
TrailG. T.AndersonD. F.FinkJ. S. (2005). Consumer satisfaction and identity theory: A model of sport spectator conative loyalty. Sport Marketing Quarterly, 14, 98–111.
68.
TrailG. T.FinkJ. S.AndersonD. F. (2003). Sport spectator consumption behavior. Sport Marketing Quarterly, 12, 1–117.
69.
WannD. L.GrieveF. G. (2005). Biased evaluations of in-group and out-group spectator behavior at sporting events: The importance of team identification and threats to social identity. The Journal of Social Psychology, 145, 531–546.
70.
WannD. L. (2006). Understanding the positive social psychological benefits of sport team identification: The team identification-social psychological health model. Group Dynamics: Theory, Research, and Practice, 10, 272.
71.
WannD. L.BranscombeN. R. (1990). Die-hard and fair-weather fans: Effects of identification on BIRGing and CORFing tendencies. Journal of Sport and Social Issues, 14, 103–117.
72.
WinterS.KrämerN. C.BenninghoffB.GallusC. (2018). Shared entertainment, shared opinions: The influence of Social TV comments on the evaluation of talent shows. Journal of Broadcasting & Electronic Media, 62, 21–37.
73.
YeeO. S.SagadevanS.MalimN. H. A. H. (2018). Credit card fraud detection using machine learning as data mining technique. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10, 23–27.
74.
YuY.WangX. (2015). World Cup 2014 in the Twitter World: A big data analysis of sentiments in US sports fans’ tweets. Computers in Human Behavior, 48, 392–400.
75.
ZafaraniR.AbbasiM. A.LiuH. (2014). Social media mining: An introduction. Cambridge, England: Cambridge University Press.
76.
ZamithR.LewisS. C. (2015). Content analysis and the algorithmic coder: What computational social science means for traditional modes of media analysis. The Annals of the American Academy of Political and Social Science, 659, 307–318.
77.
ZitnikM.NguyenF.WangB.LeskovecJ.GoldenbergA.HoffmanM. M. (2019). Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities. Information Fusion, 50, 71–91.
