Perceptual Biases and Behavioral Effects Among NFL Fans: An Investigation of First-Person, Second-Person, and Third-Person Effects

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www.IJSC-Journal.comORIGINAL RESEARCH

International Journal of Sport Communication, 2012, 5, 327-347 © 2012 Human Kinetics, Inc.

The author is with the Dept. of Organizational Communication, Murray State University, Murray, KY.

Perceptual Biases and Behavioral Effects Among NFL Fans: An Investigation

of First-Person, Second-Person, and Third-Person Effects

John S.W. SpindaMurray State University, USA

This study explored first-, second-, and third-person effects related to the outcome of televised National Football League (NFL) games among an online sample of NFL fans (N = 646). Overall findings indicated that first-person and second-person perceptual biases were projected toward comparison groups that were labeled as fans of other NFL teams or as the average person. In addition, support was found for both first and second-person behavioral effects in the form of postgame Bask-ing In Reflected Glory (BIRGing) and Cutting Off Reflected Failure (CORFing) behaviors. However, the strength of NFL fans’ team identification was a more robust predictor of these effects than NFL fans self-reported BIRGing/CORFing behaviors. These findings support the hypothesis that self-enhancement processes (i.e., BIRGing/CORFing) are usurped by self-categorization processes when a social identity is made salient (i.e., NFL team identification). Areas of future research and limitations are also addressed.

Keywords: National Football League, BIRGing, CORFing

Third-person effects (3PE) research, and more recently, first-person (1PE) and second-person effects (2PE) research, have received considerable scholarly attention over the last three decades across numerous genres of mediated messages. Originally conceptualized by Davison (1983), third-person effects are centered on the hypothesis that a media message’s “greatest impact will not be on ‘me’ or ‘you,’ but on ‘them’—the third persons” (p. 3). In general, negatively perceived media messages result in individuals projecting greater media effects on to groups of comparison others (i.e., 3PE), while positively perceived media messages result individuals projecting greater media effects on to themselves (i.e., 1PE; see And-sager & White, 2007 for review). Scholars have also illustrated 2PE, which occurs when individuals recognize media influences on themselves (1PE) together with media influences on others that are perceived to share their beliefs (Meirick, 2005, Neuwirth & Frederick, 2002). Together, the 1PE, 2PE, and 3PE research hypotheses can be broadly conceptualized as person effects research.

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In discussing the veracity of person effects research as a theoretical framework (more specifically 3PE research), Perloff (2002) noted that “although the third-person effect is more hypothesis than full-blown theory, it has roots fully planted in venerable communication concepts and respected research traditions” (p. 491). Bryant and Miron (2004) reported that person effects research is the fifth-most popular theoretical framework in 21st Century mass communication research. In recent years, scholars have continued to test a number of social/psychological processes and concomitant variables within the person effects framework; adding further depth and understanding to both the perceptual and behavioral processes involved in person effects research.

Despite the variety of mediated messages that have been examined in person effects research, scholars have yet to explore mediated sports fandom. This is surprising considering the mass appeal and ubiquitous nature of televised sports in the United States; particularly as it relates to National Football League (NFL) games. The outcome of NFL football games provide an interesting case study for person effects research because of the comparable body of sports fandom literature that suggests sports fans exhibit self-serving biases to maintain their self-esteem (e.g., Wann, Melnick, Russell, & Pease, 2001; Wann & Dolan, 1994). Wann et al. (2001) stated that “one of the most common tactics used by fans to maintain their psychological health is to strategically adjust their associations with their team” (p. 169). Therefore, it is tenable to suggest that sports fans also will demonstrate perceptual biases within the person effects framework.

Contemporary person effects research not only examines perceptions of media effects from the self to groups of comparison others (i.e., perceptual biases), but also attempts to determine how those perceptual biases may lead to behavioral outcomes (i.e., behavioral effects). Because of this, a major aim of the current study was to not only examine whether NFL fans exhibited perceptual biases regarding the outcome of televised NFL games involving their favorite team, but also to examine the link between perceptual biases and self-reported sports fandom behaviors. Of particular interest here is the area of first-person and second-person behavioral effects, which have only recently been explored by scholars (Andsager & White, 2007; Day, 2008; Frederick & Neuwirth, 2008). Second, this study explores the nature of person effects when a nondirectional message is presented (Oliver, Yang, Ramasubramanian, Kim, & Lee, 2008), as sporting events are perceived (and behaved upon) differently depending on winning or losing outcomes (Cialdini et al., 1976; Gantz & Wenner, 1995; Hirt, Zillman, Erickson, & Kennedy, 1992). Third, this study attempts to bridge the gap between the person effects framework and sports fandom by utilizing variables traditionally associated with both person effects research (e.g., social distance, message desirability, perceived exposure) and variables typically associated with sports fandom (e.g., team identification, BIRGing/CORFing).

Person Effects Research: An OverviewBased on meta-analyses of 3PE/1PE studies, nearly all person effects research has found some evidence of perceptual biases (Paul, Salwen, & Dupagne, 2000; Sun, Pan, & Shen, 2008). Recently, scholars have argued that person effects research can

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be framed within two major explanations of effects; the self-enhancement explana-tion and the self-categorization explanation (Reid, Byrne, Brundidge, Shoham, & Maslow, 2007; Zhang, 2010).

The Self-Enhancement Explanation

The self-enhancement explanation of person effects research revolves around social identity theory (SIT; Tajfel & Turner, 1979). More specifically, in SIT, individuals are motivated to maintain or bolster their self-image by making social comparisons that favor themselves (or the ingroup) over those in outgroups. Consequently, nega-tively valenced media messages, such as violent television programming (Innes & Zeitz, 1988) or pornography (Gunther, 1995) have resulted in 3PE, as individuals improve their self-image by disassociating with these stimuli. Conversely, proso-cial stimuli, such as messages that promote blood donation (Andsager & White, 2007), have resulted in 1PE. In addition to social identity theory, scholars have also argued that other self-enhancement mechanisms, such attribution theory (Eveland, Nathanson, Detenber, & McLeod, 1999; Gunther, 1991; McLeod, Detenber, & Eveland, 2001) or optimistic biases (Gunther & Mundy, 1993; Li, 2008) may also drive person effects.

While self-enhancement processes have been a viable explanation for person effects findings, recent studies have provided a great deal of evidence that the self-enhancement process is generally usurped by the self-categorization process when a social identity is made salient (Giles & Reid, 2005; Reid & Hogg, 2005; Reid et al., 2007; Zhang, 2010). In other words, both explanations operate in person effects research, but self-enhancement processes only operate when salient self-categorizations are weak or nonexistent (Zhang, 2010).

The Self-Categorization Explanation

The self-categorization explanation is grounded in self-categorization theory (SCT; Turner, Hogg, Oakes, Reicher, & Wetherell, 1987), which highlights the social cognitive processes that underpin the formation of salient social identities. According to SCT, social identities are formed by prototypes, which are “fuzzy sets of attributes that best define a category within a given context” (Reid et al., 2007, p. 146). In addition, SCT implies that an individual’s social identity changes as the relevant social context changes as a form of uncertainty reduction. SCT suggests that salient social identities are malleable and serve as a guide for both the self as well as for groups of others in a given social context. To illustrate, NFL football fans may choose to maintain an individual identity (e.g., “I am a football fan”) or may choose to self-categorize, where the group identity over-rides individual identity (e.g., “I am a Green Bay Packer fan”). Based on the self-categorization explanation of person effects, self-categorized group identities are used to guide perceptions and behaviors (e.g., Duck, Hogg, & Terry, 1995; Meirick, 2005; Price, Tewksbury, & Huang, 1998). The consensus of these person effects studies of salient social group identity, or “ego-involvement” (Perloff, 1999), is that “‘I’ becomes ‘we,’ and ‘me vs. you’ becomes ‘us vs. them’ (Duck, Hogg, & Terry, 1999, p. 1881).

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Perceptions of Social Distance and Perceived Effects

This study also engaged the question of whether perceptions of social distance or perceptions of media effects from the self to groups of comparison others were more influential in predicting perceptual biases related to the outcome of televised NFL football games. First, the social distance corollary implies that as perceived social distance increases from the self-to-groups of comparison others, perceptual biases and behavioral effects grow as well (Gunther, 1991; Meirick, 2004; Paek, Pan, Sun, Abisaid, & Houden, 2005; Perloff, 1993). Perloff (1993) suggested that social distance perceptions between the self and others may be a function of psychological distance (e.g., “just like me” to “not at all like me”) or group size and heterogeneity (e.g., “my closest group or community” to “my largest group or community”).

On the other hand, some person effects scholars have brought forth support that the perceived exposure of groups of comparison others to a media message is a more influential predictor of perceptual biases and behavioral effects than social distance, this is known as the target corollary (David, Morrison, Johnson, & Ross, 2002; Eveland et al., 1999; McLeod et al., 1997; Paek et al., 2005). The target corollary has been measured in person effects research using specifically defined, topic/message relevant groups of comparison others. Studies have reported that these defined target groups often are perceived to be more exposed to a particular media message, leading to enhanced third-person perceptual bias (David et al., 2002; Eveland et al., 1999; McLeod et al., 1997, 2001; Meirick, 2004; Tsfati & Cohen, 2004).

The distinctions between the social distance corollary and the target corol-lary imply different theoretical interpretations for person effects research. When increased social distance predicts perceived effects, scholars have argued that ingroup/outgroup biases may be responsible for increases in perceived effects between the self and more socially distant groups of comparison others (Meirick, 2005). Conversely, when perceived exposure positively predicts perceived effects, scholars have forwarded the “hypodermic needle” hypothesis of media influence that implies media audiences are not capable of resisting media influence (Eveland et al., 1999). Because of this lack of resistance, media influence simply grows with media exposure (Perloff, 2002).

Linking Person Effects and Sports Fandom Research

As outlined above, extant research supports the self-enhancement and self-categorization interpretations forwarded by person effects scholars. Similar to person effects research, a robust body of literature illustrates the use of self-enhancement and self-categorization biases by sports fans.

Self-Enhancement Processes Among Sports Fans

Hastorf and Cantril (1954) asked students to describe a football game between two universities. The winning team’s fans described the game as “rough but fair” while the losing team’s fans described the game as “rough and dirty,” with 55% implying

Person Effects on NFL Teams 331

that an injury to a star player on their team was intentionally caused. These types of self-enhancing internal and external attributions have also emerged in subse-quent studies of sports fans (Mann, 1974; Wann & Dolan, 1994). Sports fans have also demonstrated self-enhancing optimistic biases (Weinstein, 1980), similar to the ones outlined in person effects research (Gunther & Mundy, 1993; Li, 2008). These include predictions that collegiate athletes would be drafted into professional sports (Murrell & Dietz, 1992), overzealous evaluations and estimations of team performance for an upcoming season (Wann & Dolan, 1994).

The most developed line of research concerning sports fans’ self-enhancement biases is the Basking In Reflected Glory (BIRG; Cialdini et al., 1976) / Cutting Off Reflected Failure (CORF; Snyder, Lassegard, & Ford, 1986) hypotheses, otherwise known as BIRGing and CORFing. Cialdini et al. (1976) implied that BIRGing occurs when individuals strategically align themselves with a successful group (i.e., internal attributions made for victorious effort) and publicly display their association for others to see. Conversely, Snyder and colleagues (Snyder, Higgins, & Stucky, 1983; Snyder et al., 1986) expanded on the concept of BIRGing by exploring what occurs to group identification in the event of negative outcomes. They noted that CORFing is “the severing of associations with others who have failed, in the interest of avoiding a negative evaluation by others (and oneself)” (i.e., external attributions made for losing effort; Snyder et al., 1986, p. 383).

Evidence of BIRGing behavior has been observed via higher levels of institu-tion related apparel at universities with successful football teams (Cialdini et al., 1976), more sports team-related internet use (Boen, Vanbeselaere, & Feys, 2002; End, 2001), talking to other sports fans and seeking out sports highlights after a victory (Gantz & Wenner, 1995), and improved self-esteem (Hirt et al., 1992). Similarly, CORFing behavior has been exhibited by the refusal of a team poster immediately after a defeat (Bizman & Yinon, 2002) and by fans that avoided others following a defeat (Gantz & Wenner, 1995).

Self-Categorization Processes Among Sports Fans

As noted earlier, person effects scholars have concluded that self-enhancement processes (via social identity theory) only operate when salient self-categorizations (via self-categorization theory) are weak or nonexistent (Giles & Reid, 2005; Reid & Hogg, 2005; Reid et al., 2007; Zhang, 2010). One form of self-categorization that sports fans voluntarily undertake is to choose allegiance to a favorite team (or teams). The level to which sports fans identify, or self-categorize, with these selected teams has been extensively studied through team identification, or “the extent to which a fan feels psychologically connected to a team” (Wann et al., 2001, p. 3). Team identification has been found to be relatively stable and trait-like, with consistent levels of identification being reported from game-to-game and season-to-season (Wann, 1996). In addition, multiple studies have indicated that highly identified fans employ positive traits when describing other fans of their favorite team (i.e., ingroup), while using more derogatory terms in describing fans of rival teams (i.e., outgroup; Franco & Maass, 1996; Wann & Branscombe, 1993, 1995).

Beyond perceptual differences, Billings (2008) noted that Olympic television broadcasts foster “us versus them” dichotomies by using more subjective descrip-tions for home nation athletes (e.g., athletic courage, personality), while referring to

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objective terms to describe foreign athletes (e.g., strength, speed). Levine, Prosser, Evans, and Reicher (2005) provided experimental evidence of team identification leading to behavioral biases; as a confederate wearing an ingroup jersey received assistance more often than a confederate in a neutral outgroup jersey. In sum, past research in both person effects and in sports fandom suggest that self-enhancement and self-categorization processes lead to perceptual and behavioral effects.

Research Questions and HypothesesThe foremost research question in this study, as in all person effects research, is the nature of the perceptual bias regarding media messages. Thus, the following research question was asked:

RQ1: Will NFL fans exhibit first-person, second-person, and/or third-person perceptual biases regarding the outcome televised NFL football games involving their favorite team?

An important research variable that has been applied to person effects research has been message desirability, or how the perceived positive or negative valence of media content affects perceptual bias. Although some violent incidents during and after sporting events have anecdotally portrayed sports fans as aggressive or antisocial in nature (see Wann et al., 2001 for a review), research on sports fan motives suggests that fans watch sports to satisfy mostly prosocial needs (Gantz & Wenner, 1995; Trail & James, 2001; Wann, 1995). Moreover, the mass appeal of televised NFL football suggests that these media messages would be positively valenced in nature for both the self and for others ingroup members. Thus, it was predicted that

H1a: Message desirability will be positively related to first-person perceptual biases associated with televised NFL football games

H1b: Message desirability will be positively related to second-person perceptual biases associated with televised NFL football games.

As noted earlier, sports fans’ identification often results in biased attributions and ingroup biases. Thus, the ingroup favoritism associated with high levels of team identification should translate to positive perceptions of NFL football games for both the self and fellow ingroup members. Therefore, it was predicted that

H2a: NFL team identification will be positively related to first-person percep-tual biases associated with televised NFL football games

H2b: NFL team identification will be positively related to second-person per-ceptual biases associated with televised NFL football games.

In exploring the social distance corollary and the target corollary, scholars have provided evidence that has indicated perceptions of social distance are not as strong of a predictor of perceptual bias as perceived exposure (Eveland et al., 1999), and does not account for the relevant social knowledge of comparison others (Tsfati & Cohen, 2004). Because recent studies have generally provided evidence of the target corollary, it was predicted that

H3: Perceived exposure of televised NFL games will predict increases in per-ceived effects related to televised NFL games for outgroup fans.

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Person effects scholars have also continued to find support for the social dis-tance corollary (Leone & Bissell, 2005). Because support for the social distance corollary has been mixed in recent studies, the following was asked:

RQ2: Will perceived social distance predict perceived effects related to televised NFL games for ingroup and outgroup fans?

A few studies have indicated that perceived exposure does predict influence on the self (McLeod et al., 2001; Meirick, 2005). Because of this, Meirick (2005) suggested the target corollary does not account well for first-person perceptual bias, noting that when individuals perceive greater media influence on themselves, they also perceive groups of comparison others to be more exposed to media messages as well. Conversely, Tsfati and Cohen (2004) found that respondents exhibited first-person perceptual bias while also indicating greater perceived exposure for themselves. In lieu of these contradictory findings, we asked

RQ3: Will perceived exposure for oneself predict increases in perceived effects related to televised NFL football games for oneself?

Evidence of the behavioral component in 3PE research has come in the form of support for some type of message restriction or even support of outright censor-ship regarding antisocial messages (Paul et al., 2000; Perloff, 1999; Schmierbach, Boyle, & McLeod, 2008). Meanwhile, evidence of the behavioral component in 1PE research has only recently been explored in the form of volunteer efforts to assist war veterans (Andsager & White, 2007) or voting intentions (Day, 2008). In examining 2PE, Frederick and Neuwirth (2008) examined potential behaviors for expressing opinions regarding the legalization of prostitution. Consequently, this study aims to continue this trend of adding to the collection of behaviors explored in person effects research by exploring postgame fandom behaviors in the form of BIRGing and CORFing:

RQ4: Does a linear combination of audience dispositions (message desirability, NFL team identification) and perceptual biases (i.e., 1PE, 2PE, 3PE) pre-dict post-game behaviors among NFL fans (i.e., BIRGing and CORFing)?

Method

Sampling Procedure

To obtain participants, National Football League (NFL) fans (Mage

= 35.72, age range 18–83) were recruited online via NFL-related blogs and websites (N = 646). Blog administrators (i.e., bloggers) were contacted via e-mail and asked to post an Internet hyperlink on their respective blogs or websites that led respondents to the online questionnaire used in this study. Of the 929 online questionnaires begun by respondents, 646 were completed in full, for a completion rate of 69.5%. Overall, fans from 27 of the 32 NFL franchises were represented in the sample, with fans and/or bloggers representing 5 franchises failing to participate. There were many more men (N = 605) than women (N = 34) in the sample, with 7 respondents choosing not to identify their gender. With respect to education level, 1.2% of respondents indicated they did not finish high school, 7.0% had a high school diploma or equivalent, 10.2% had completed a two-year college degree or trade

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school, 20.9% had completed some college studies, 34.8% had completed a four-year college degree, 8.7% had completed some graduate studies, and 17.2% had completed a graduate degree.

Measures

Question order effects were accounted for by utilizing three different versions of an online questionnaire. Each version had a separate order and was systematically distributed to bloggers via hyperlink. In each version of the questionnaire, the first item prompted participants to choose the name of their favorite (or most familiar) NFL team from a drop-down box containing the names of all 32 NFL teams. This process of selecting of a favorite NFL team was used throughout the questionnaire by HTML text piping. For instance, if a person selected the Pittsburgh Steelers as a favorite NFL team, that team name will appear in future questions or scale items (e.g., “How important is it to you that the Pittsburgh Steelers win?”). This choice is represented throughout whenever “favorite NFL team” appears in parenthesis.

Perceived Effects. A measure of perceived effects, modeled from Lambe and McLeod (2005), was measured with five semantic differential items (1 = not affected and 7 = very affected) that prompted respondents to estimate “how much does the outcome of televised NFL games involving the (favorite NFL team) affect” a) you personally, b) other fans of the (favorite NFL team), c) fans whose favorite team is a rival of the (favorite NFL team, d) fans whose favorite team is another team around the league, and e) the average person. The various groups of comparison others were chosen based on the in-group/out-group perceptual bias found in studies involving partisan groups, such as political supporters (Duck et al., 1995; Meirick, 2004) or national/religious identities (Price et al., 1998; Perloff, 1989).

Perceptual Bias. Perceptual bias values were observed by three methods in this study. First, the subtracted difference between how much a person believes televised NFL games influences themselves relative to how much televised NFL games influence groups of comparison others was used. This technique, which has been labeled as a “subtractive term,” has been the most used measure to determine person effects. While it has been scrutinized by scholars, the subtractive term has also been noted to be theoretically appropriate for 1PE/3PE research (Schmierbach et al., 2008). Second, the addition of how much a person believes televised NFL games influence themselves with how much televised NFL games influence groups of comparison others was used. Conversely, this technique has been labeled as an “additive term.” The additive term is suitable for measuring 2PE, as it explores the joint media influence of the self and others (Frederick & Neuwirth, 2008; Neuwirth & Frederick, 2002; Schmierbach et al., 2008). Together, the subtractive term and additive term are employed in what is known as the Diamond Model (Whitt, 1983). This type of regression model has been effectively employed in previous person effects studies (see Schmierbach et al., 2008 for review). Third, a second-person perceptual bias value was computed by averaging the two items for perceived effects on the self and perceived effects on fellow fans of favorite team. This averaging afforded the opportunity to measure 2PE mean differences from a favorite team ingroup (i.e., self and other fans of favorite team combined) to outgroups (i.e., rival fans, fans around NFL, the average person).

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Perceived Social Distance and Exposure. Perceived social distance, modeled from Eveland et al. (1999), was measured using four semantic differential items (1 = not at all similar and 7 = very similar). These items were reverse coded so that higher social distance values indicated more social distance. Perceived exposure to televised professional sports consisted of semantic differential items (1 = never and 7 = very frequently) that examined perceptions of actual exposure to televised NFL football (Eveland et al., 1999; Lambe & McLeod, 2005; McLeod et al., 2001).

Message Desirability. Message desirability was gauged with a four-item seman-tic differential measure (Hitchon, Chang, & Harris, 1997). This measure prompts respondents to rate televised NFL football games involving one’s favorite NFL team on four continua ranging from a) socially desirable to not socially desirable, b) beneficial to not beneficial, c) socially responsible to not socially responsible, and d) favorable to society to not favorable to society. The four items were summed and averaged to create a message desirability score (M = 5.47, SD = 1.28, α = .89).

NFL Team Identification. NFL team identification was measured using the Sport Spectator Identification Scale (SSIS; Wann & Branscombe, 1993). This scale utilizes seven, eight-point semantic differential scales that determine the level of psychological connection one feels with their favorite team. The SSIS is a highly reliable measure of sport fan identification that has been applied in over 100 studies of sports fandom internationally (e.g., Wann et al., 2001). In this study, the seven items were summed and averaged to create the identification score (M = 6.62, SD = 1.13, α = .83).

BIRGing/CORFing Measures. Separate self-report measures for BIRGing and CORFing behaviors were generated to be reflective of the behaviors noted in extant BIRGing and CORFing research (Spinda, 2011). Each parallel-worded scale included 10 Likert-scale items (1 = strongly disagree and 5 = strongly agree). Each BIRGing item was an extension of the statement “after the (favorite NFL team) win . . .”, while each CORFing item was an extension of the statement “after the (favorite NFL team) lose . . .”. These ten items examined sports fans’ public display behaviors (i.e., logo or insignia display), interpersonal communication behaviors, online communication behaviors, and bragging/suppressing behaviors related to game outcomes. In this study, the BIRGing measure (M = 3.21, SD = 0.83, α = .83) and CORFing measure (M = 2.60, SD = 0.81, α = .81) were summed and averaged.

ResultsResearch question one was asked to determine which type of perceptual biases were exhibited among NFL football fans in this study. First, a series of four paired sample t tests were run to determine whether 1PE of 3PE were present (see Table 1). The results indicated that perceived effects of televised NFL football games were significantly lower for oneself than for other fans of the same favorite team, which would indicate a third-person perceptual bias at face value. However, in research where ingroup identities have been made salient, this significant, but small mean difference can most likely be attributed to intragroup evaluation effects. In other words, it is likely participants reported higher levels of perceived effects for favorite team ingroup members (i.e., fellow fans of favorite NFL team) due to perceived ingroup cohesion (Turner & Oakes, 1989; Voci, 2006). Other recent person effects

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studies have found a similar pattern of intragroup cohesion effects (Andsager & White, 2007; Meirick, 2004). Perceived effects on the self were not significantly different than perceived effects on fans of rival teams. However, perceived effects of televised NFL games were significantly higher when estimating effects onto groups of fans whose favorite team is another team around the NFL and to the average person comparison group, indicating a first-person perceptual bias.

However, to test the possibility that these mean differences may be due to the joint influence of the self and others in the favorite team ingroup (i.e., 2PE), the averaged second-person effects perceptual bias value was tested against the mean values for other comparison groups in second set of paired t tests (see Table 2). The results in this second set of tests indicated that perceived effects were not signifi-cantly higher for the averaged 2PE value than for fans of rival NFL teams, but were significantly higher when the averaged 2PE value was compared with perceived effects for fans around the NFL as well as the average person comparison group.

Hypothesis 1 implied that message desirability would be positively related to first and second-person perceptual bias values. This hypothesis was fully supported. Hierarchical regression analyses were employed using the aforementioned diamond

Table 1 Paired t Tests: Perceived Effects on the Self and Comparison Groups

Perceived effect on . . . M SD t(645) p

Self 4.85 1.63 — —

Other fans of favorite NFL team 5.03 1.28 –3.02 .003*

Fans of rival NFL team 4.86 1.27 –0.12 .905

Fans around the NFL 4.62 1.37 3.18 .002*

The average person 4.37 1.41 6.98 <.001*

Note. Bonferroni corrected significance level was α = .0063 for paired t tests (eight paired compari-sons/.05). N = 646.

* p < .0063.

Table 2 Paired t tests: Second-Person Perceptual Bias and Comparison Groups

Perceived effect on . . . M SD t(645) p

Second-person perceptual bias 4.94 1.25 — —

Fans of rival NFL team 4.86 1.27 1.66 .098

Fans around the NFL 4.62 1.37 5.61 < .001*

The average person 4.37 1.41 10.25 < .001*

Note. Second-person perceptual bias was computed as the perceived effect on the self + perceived effect on other fans of favorite NFL team / 2. N = 646. Bonferroni corrected significance level was α = .0083 for paired t tests (six paired comparisons/.05).

* p < .0083.

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model, which included both the subtractive term (self- comparison other to account for 1PE/3PE) and the additive term (self + comparison other to account for 2PE) on the second step of the equation, while control variables (e.g., age, gender, formal education) served as the first step in the equation. While both the subtractive term and the additive term were significant predictors of message desirability in all four regres-sion equations, the additive term was a more robust predictor of message desirability each time, suggesting that second-person perceptual biases were more influential in predicting perceptions of NFL football as a desirable media message (see Table 3).

Hypotheses 2 posited that NFL team identification would be positively related to first and second-person perceptual biases. This hypothesis was fully supported. Similar to the method used in H1, hierarchical regressions were computed using the diamond model on the second step of the regression equations to account for both the subtractive (1PE/3PE) and additive terms (2PE) simultaneously while control variables were employed on the first step of the regression equations. These results indicated that both first-person and second-person perceptual biases were robust predictors of NFL team identification overall (see Table 4). But it is important to note that the positive subtractive term (1PE) was more robust in the self-to-fellow fans comparison. This would imply that the aforementioned intragroup evaluation effect may have been evident regarding participants’ perceptions of NFL team identification in this study. In other words, assigning larger perceived effects onto fellow ingroup members than oneself regarding NFL team identification may serve as a show of ingroup solidarity.

Research questions 2 and 3, as well as hypothesis 3, dealt with whether social distance or perceived exposure is more influential predicting changes in perceived effects of televised NFL football from the self to comparison others. To determine this, multiple regression analyses were employed (see Eveland et al., 1999; Mei-rick, 2005). Table 5 provides the final beta values for all five of these regression

Table 3 Summary of Multiple Regression Analyses for First-Person Perceptual Bias and Second-Person Perceptual Biases Predicting Message Desirability

Comparison group

First-person perceptual bias

Second-person perceptual bias

Final β Final βOther fans of favorite NFL team .12** .21***

Fans of rival NFL team .13** .21***

Fans around the NFL .13** .22***

The average person .14*** .21***

Note. N = 646. The above table displays standardized betas, controlling for the effects of gender, age, and education. Standardized beta values reported for final block of equation. For Other Fans of Favorite NFL Team model: R = .29, R2 = .08, ΔR2 = .07***, F(5, 640) = 11.84, p < .001. For Fans of Rival NFL Team model: R = .29, R2 = .08, ΔR2 = .07***, F(5, 640) = 11.86, p < .001. For Fans Around the NFL model: R = .29, R2 = .08, ΔR2 = .07***, F(5, 640) = 11.97, p < .001. For The Average Person model: R = .29, R2 = .08, ΔR2 = .07***, F(5, 640) = 11.86, p < .001.

* p < .05, ** p < .01, *** p < .001.

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Table 4 Summary of Multiple Regression Analyses for First-Person Perceptual Bias and Second-Person Perceptual Biases Predicting NFL Team Identification

Comparison group

First-person perceptual bias

Second-person perceptual bias

Final β Final βOther fans of favorite NFL team .37*** .32***

Fans of rival NFL team .30*** .37***

Fans around the NFL .32*** .38***

The average person .29*** .41***

Note. N = 646. The above table displays standardized betas, controlling for the effects of gender, age, and education. Standardized beta values reported for final block of equation. For Other Fans of Favorite NFL Team model: R = .60, R2 = .35, ΔR2 = .30***, F(5, 640) = 70.14, p < .001. For Fans of Rival NFL Team model: R = .58, R2 = .33, ΔR2 = .28***, F(5, 640) = 65.43, p < .001. For Fans Around the NFL model: R = .58, R2 = .33, ΔR2 = .28***, F(5, 640) = 65.24, p < .001. For The Average Person model: R = .58, R2 = .33, ΔR2 = .28***, F(5, 640) = 65.12, p < .001.

* p < .05, ** p < .01, *** p < .001.

Table 5 Summary of Hierarchical Multiple Regression Analyses for Predicting Perceived Effects on Self and Comparison Others

Perceived effect on . . .

Perceived social distance Perceived exposure

Final β Final βSelf n/a .16***

Other fans of favorite NFL team –.12** .14***

Fans of rival NFL team –.13** .12**

Fans around the NFL –.16*** .12**

The average person –.05 .25***

Note. N = 646. The above table displays standardized betas, controlling for the effects of gender, age, education, and perceived effects on the self (the latter was not included in predicting perceived effects on self). Positive social distance values indicate higher social distance.. For Self model: R = .20, R2 = .04, F(4, 641) = 6.97, p < .001. For Other Fans of Favorite NFL Team model: R = .52, R2 = .26, F(6, 639) = 38.51, p < .001. For Fans of Rival NFL Team model: R = .58, R2 = .33, ΔR2 = .28***, F(5, 640) = 65.43, p < .001. For Fans Around the NFL model: R = .58, R2 = .33, ΔR2 = .28***, F(5, 640) = 65.24, p < .001. For The Average Person model: R = .58, R2 = .33, ΔR2 = .28***, F(5, 640) = 65.12, p < .001.

* p < .05, ** p < .01, *** p < .001.

equations. These tests suggest that both social distance and perceived exposure predicted perceived effects. Perceived social distance was a significant negative predictor of effects for three comparison groups (i.e., other fans of favorite NFL team, fans of rival NFL teams, fans around the NFL), but did not significantly pre-dict effects for the average person comparison group (RQ2). This negative social

Person Effects on NFL Teams 339

distance implies that respondents view other defined groups of NFL fans as very much like themselves, and that this similarity predicts perceived effects of televised NFL football games. Perceived exposure predicted effects on the self, as well as perceived effects across all other groups of comparison others (e.g., other fans of favorite NFL team, fans of rival NFL teams, fans around the NFL), confirming H3 in this study. Of note, however, is the large spike in the beta value for perceived exposure related to the vaguely defined “average person.”

Research question 5 asked whether audience dispositions (e.g., NFL fan identification, message desirability) and first, second, and third-person perceptual biases could successfully predict NFL fans’ self-reported BIRGing and CORFing behavior. Overall, four hierarchical multiple regression analyses were conducted to examine this question (see Tables 6 and 7). The first two analyses regressed BIRG-ing and CORFing behaviors on four blocks of variables to explore 1PE and 3PE. Block one contained demographic control variables (i.e., age, gender, education). Block two explored audience dispositions (i.e., NFL fan identification and mes-sage desirability). Third, perceived effects on the self were added to the regression

Table 6 Regression Analyses: Control Variables, Audience Dispositions, and Perceived Effects as Predictors of BIRGing and CORFing Behavior

Predictors BIRGing CORFing

Block 1: control variables

Age –.16*** .09*

Gender (female = high) .02 –.06

Education –.11*** .06

Block 2: audience dispositions

NFL team identification .37*** –.31***

Message desirability .11** –.02

Block 3: perceived effects on self

Effect on self .15*** .25***

Block 4: Perceived effects on others

Effect on other fans of favorite team .08 .02

Effect on fans of rival team –.04 .03

Effect on fans around the NFL .02 –.09*

Effect on the average person –.04 .03

Note. N = 646. Standardized beta values reported for final block of equation. For BIRGing equations: R = .30, R2 = .09, F(3, 642) = 21.07, p < .001 for Block 1. R = .57, R2 = .32, ΔR2 = .24, F(5,640) = 62.10, p < .001 for Block 2. R = .59, R2 = .34, ΔR2 = .02, F(6, 639) = 56.51, p < .001 for Block 3. R = .59, R2 = .34, ΔR2 = .01, F(10, 635) = 34.43, p < .001 for Block 4. For CORFing equations: R = .16, R2 = .03, F(3, 642) = 5.45, p = .001 for Block 1. R = .24, R2 = .03, ΔR2 = .03, F(5,640) = 7.54, p < .001 for Block 2. R = .31, R2 = .09, ΔR2 = .04, F(6, 639) = 11.54, p < .001 for Block 3. R = .32, R2 = .09, ΔR2 = .01, F(10, 635) = 7.34, p < .001 for Block 4.

* p < .05, ** p < .01, *** p < .001.

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equation to better account for the influence of perceived effects on comparison others (e.g., Schmierbach et al., 2008). The fourth and final block included all four self-to-comparison group difference scores, which provided some understanding as to which difference scores were the most salient in predicting self-reported BIRGing and CORFing. Table 6 provides an overview of model changes and final beta values. Next, two analyses regressed BIRGing and CORFing behaviors on four blocks of variables to determine if 2PE or 1PE/3PE were at work in this study via the diamond model. Blocks one and two of these regression equations again controlled for demographics and audience dispositions. However, block three in each test contained both the difference scores (1PE/3PE) and the additive scores (2PE). Table 7 provides an overview of model changes and final beta values for these equations.

The results of the first set of regressions indicated that younger, less edu-cated sports fans with high levels of NFL team identification, high perceptions of message desirability, and higher levels of perceived effects on the self were more likely to engage in BIRGing behaviors. Conversely, older sports fans with lower levels of NFL team identification, and higher levels of perceived effects

Table 7 Regression Analyses: First-, Second-, and Third-Person Perceptual Bias as Predictors of BIRGing and CORFing Behavior

Predictors BIRGing CORFing

Self to other fans of favorite NFL team

First-/third-person perception (self to other) .03 .12**

Second-person perception (self to other) .16*** .19***

Final R2 (ΔR2 for final block) .34 (.02***) .08 (.04***)

Self to fans of rival NFL teams

First-/third-person perception (self to other) .10** .14***

Second-person perception (self to other) .12** .18***

Final R2 (ΔR2 for final block) .34 (.02***) .09 (.04***)

Self to fans around the NFL

First-/third-person perception (self to other) .08* .20***

Second-person perception (self to other) .14*** .14**

Final R2 (ΔR2 for final block) .35 (.02***) .09 (.05***)

Self to the average person

First-/third-person perception (self to other) .12** .12**

Second-person perception (self to other) .11** .20***

Final R2 (ΔR2 for final block) .34 (.02***) .09 (.04***)

Note. N = 646. Standardized betas presented in this table are from final block of regression equation controlling for age, gender, education, NFL team identification, and message desirability. For First/Third Person Perception (self—other), a positive beta represents first-person perception and a nega-tive beta represents a third-person perception. All regression equations predicted BIRGing/CORFing

* p < .05, ** p < .01, *** p < .001.

Person Effects on NFL Teams 341

on the self were more likely to engage in CORFing behaviors. These findings suggest that 1PE is at work for both BIRGing and CORFing in this study (see Table 6). However, the second set of regressions indicated that both 1PE and 2PE significantly predicted BIRGing and CORFing for all self-to-comparison group evaluations, with the exception of self-to-other fans of favorite team, where only 2PE emerged (see Table 7).

DiscussionIn this study, both first and second-person perceptual biases were exhibited when comparing the self (1PE) or comparing the joint impact of the self and fellow fans of a favorite NFL team (2PE) toward comparison groups, such as NFL fans around the league and the average person. In addition, the robust findings regarding 2PE indicate support for the self-categorization explanation of person effects in this study. Self-categorization is further evidenced here because no person effects emerged when comparing perceived effects on the self (1PE) or the self and fellow fans of a favorite NFL team (2PE) against perceived effects on rival NFL fans. While this is not consistent with the “us” versus “them” biases found in past research with highly identified or partisan groups (Duck et al., 1995, 1999; Meirick, 2005; Perloff, 1989; Price et al., 1998), this finding may suggest that NFL fans’ team identification as a social identity serves as a context-specific guide to perceptions or behavior; or a prototype, as outlined in self-categorization theory.

In the case of NFL football, it is important to consider that many rivalries are regionally associated, with fan bases colocated in the same geographical region. Thus, it seems tenable that a sizable portion of fans have prototypes that allow them to temper outgroup biases during times when rival threats lay dormant, such as during the offseason or when a contest between two rivals is not eminent. In addition, there are instances when regional rivals may support a rival team if it is beneficial for their team, such as when a rival team may control a favorite team’s postseason fate within a division. Another finding from the current study that sup-ports the self-categorization explanation is the negative social distance values that emerged from the self-to-rival NFL fans comparison, suggesting that fans in this sample see rival fans as more “like” them than “unlike” them. Likewise, a nearly identical negative social distance value was noted in the self-to-fans of other NFL teams comparison, which would suggest that NFL fans may have the ability to express outgroup degradation toward rival fans when that prototype is enacted, per self-categorization theory, while still being able to perceive them as fellow NFL fans and geographical neighbors when that is the appropriate prototype.

Aside from determining the nature of person effects regarding NFL football games, another major objective of this study was to examine the link between per-ceptual biases and fans’ self-reported BIRGing/CORFing behavior. In this study, first and second-person perceptual biases predicted both BIRGing and CORFing behavior. This finding could be interpreted in a few ways. One explanation for this finding could be that some NFL fans may strategically choose to avoid making their fandom a salient social identity to have the autonomy to CORFing in a losing situa-tion. This argument is supported in this study because those that reported CORFing behavior also reported low team identification. A competing explanation could be that fans with first-person, and especially second-person perceptual biases, see their

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fandom as a salient social identity, but employ CORFing as a temporary emotional coping (or self-enhancement) mechanism to a loss, only to restore their allegiance to their favorite team shortly thereafter (Bizman & Yinon, 2002).

Findings in this study indicated that perceived social distance negatively pre-dicted perceived effects in three groups of comparison others that were defined as NFL fans (e.g., fellow fans of favorite NFL team, fans of rival NFL teams, fans of other NFL fans). However, the findings in this study indicated support for the target corollary as well. Perceived exposure to televised NFL games positively predicted perceived effects, especially for the average person comparison group. Perceptions of social distance and perceptions of exposure both predicted perceived effects of televised NFL games with near equal strength when evaluating specifically-defined groups of comparison others. Paek et al. (2005), suggested that “when individuals make judgments on message effects on each target, they compensate for their lack of information about the target by resorting to self and the relevant knowledge on self-other differences activated by the label of each target other” (p. 162). Although perceived social distance predicted perceived effects of televised NFL football, these predictions did not vary much between groups of comparison others and only occurred in cases where comparison others were well defined. Conversely, it appears that the influence of perceived exposure was most evident for the vaguely-defined average person. This finding is deserving of further attention in regards to the target corollary, which has generally found that well-defined comparison others with a perceived propensity to be exposed to a message will garner stronger perceived effects (McLeod et al., 1997).

Limitations and Conclusion

The first limitation of this study is that the sample is not indicative of all types of sports fans and was not randomly chosen. The decision to use NFL fans was based on its standing as the most popular spectator sport in the United States. This choice led to a convenience sample of fans that indicated high involvement with the sport overall. Future studies that sampled other sports, or sampled fans using methods that minimize sampling error, would certainly help clarify the findings that emerged here. Another limitation was gender imbalance. Many more males (94%) than females (5%) completed this online questionnaire. This disparity could be partially attributed to reported sex differences in sports fandom. While females are just as likely as males to consider themselves sports fans and to attend sporting events (Dietz-Uhler et al., 2000), males are “more likely than females to spend time discussing sports, show a greater interest in sports, and have more self-reported and actual knowledge of sports” (p. 227). This increased interest and potential for discussion may motivate a male NFL fan to frequent an NFL blog or website more so than a female fan.

Third, the nature of BIRGing and CORFing has been broadly defined by scholars. The self-report measure of these variables is still in need of further test-ing. While BIRGing and CORFing were found to be internally consistent as an overall measure in this analysis, other analyses have indicated these behaviors are more functional as separate subscales of postgame behaviors (Spinda, 2011). Based on these subscale means, postgame media consumption behaviors (i.e., reading newspaper or online articles, viewing highlights) were reported as the most salient BIRGing behavior among male NFL fans. Meanwhile, postgame

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media avoidance behaviors concerning these same media forms were reported as the least likely CORFing behavior. Since these findings are descriptive and tenu-ous in nature, further research is needed to fully elucidate the role that postgame media consumption plays in either enhancing fans’ postgame BIRGing experiences or helping fans’ analyze or cope with a defeat as a form of CORFing. In addition, research that measures BIRGing and CORFing behaviors in a longitudinal fashion may produce different results than studies that measure these behaviors at one interval, as this study did.

Future person effects research regarding sport fans would also benefit from exploring more specific media effects outcomes than were used in this study, which asked participants how much the “outcome” of a game influenced them and groups of comparison others. While this measure does provide baseline evidence that fans are affected by NFL game outcomes, more specific outcomes (e.g., overall season outcomes, playoff game outcomes, rival game outcomes, unexpected wins/losses) would provide more depth and clarity regarding these effects. Lastly, because of broad national and international access to televised NFL games, the impact of fans’ geographic location relative to their favorite NFL team (i.e., local fan or displaced fan) deserves attention in future research. This is especially important considering the evidence that has been presented regarding the significant effects that geographic location can produce among sport fans (see Wann, Polk, & Franz, 2011).

In conclusion, this study highlighted that game outcomes are a viable media messages deserving of future attention within the person effects framework. Overall, NFL fans in this study reported perceptual biases congruent with the self-categorization explanation of person effects research by assigning greater perceived effects onto themselves, and especially on to those that share their a common identity as fans of an NFL team. This is not to suggest that self-enhancement behaviors, such as BIRGing/CORFing in this study, are not viable behavioral responses to NFL game outcomes. Instead, it seems likely from both extant research and the findings presented here that these self-enhancement behaviors are secondary to self-categorization in the form of team identification. Just as other person effects research has indicated the importance of salient political identities (Meirick, 2004) or salient religious identities (Price et al., 1998) in predicting perceptual bias and self-reported behaviors, this study has highlighted the importance of NFL team identification for predicting perceptions and behaviors related to televised NFL games. Future research in person effects and sport should build toward exploring the perceptual biases and behavioral effects associated with more specific mediated messages in the sport domain; such as violence in sports (Wann et al., 2001) or even antisocial athlete behaviors (Earnheardt, 2010), both of which have garnered a great deal of attention in recent media coverage.

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