*..,.,. 1), 2), 3) 8:0, 7:1, 6:2, 5:3, 4:4, 3:5, 2:6, 1:7, 0:8 9. /, /, / 2 (two alternative forced choice task).,. (nonlinear data fitting), (point of subjective equality: PSE) (precision)., - 0.5,. - 0.5, - 0.5.,,.,. * 2016 ( ) [NRF-2013S1A3A2054886]. 1. :,, (46241) 63 2 ( ) Email : dhlee@pusan.ac.kr
.,. (facial expression),.. (Ekman, 1993; Ekman & Friesen, 1971; Izard, 1994) (Park & Kim, 2015).,. Uchida, Townsend, Markus Bergsieker(2009). Uchida (2009)?,,,. Uchida (2009). Uchida (2009) (Lee, Choi, & Cho, 2012; Masuda et al., 2008).,.,?? (crowd perception) (Haberman & Whitney, 2007, 2009; Yamanashi Leib et al., 2012; Yang, Yoon, Chong, & Oh, 2013). Haberman Whitney(2007, 2009),, (ensemble representation).,,,,
. (prosopagnosia) Yamanashi Leib (2012), (ensemble coding). Yang (2013). Yang (2013) Haberman Whitney(2007, 2009),. Yang (2013) Haberman Whitney(2007, 2009),,. (point of subjective equality: PSE) (precision). (social anxiety level),. Yang (2013),..,.. Barsäde Gibson(1998) (group emotion),.,,, (Parkinson et al., 2005). Barsäde Gibson (2012), (bottom-up), (emotional contagion).
, (Kelly, 2001; Magee & Tiedens, 2006).... (Niedenthal & Brauer, 2011), (Boiger & Mesquita, 2012).,.,., 45%, 55%,?? Haberman Whitney(2007, 2009). 45%?? Yang (2013) 0.54, 0.59.,,.?, (emotional valence),.,.,,.
,,. 8 1) -, 2) -, 3) - 8:0, 7:1, 6:2, 5:3, 4:4, 3:5, 2:6, 1:7, 0:8 9., /, /, /. Yang (2013) 0.1 (100ms),, 3. (ensemble representation),,.. (the Positive and Negative Affect Schedule; PANAS, Watson et al., 1988),,, (, ). 153, 51-2. - 51 ( :13, :38; :20.9 ), - 49 ( :11, :38; : 20.5 ), - 51 ( :12, :39; : 20.3 ) 151.. (the Positive and Negative Affect Schedule; PANAS). Watson, Clark Tellegen(1988) (the Positive and Negative Affect Schedule; PANAS) (Lee, Kim, & Lee, 2003). Watson (1988) 10 10, 0~4. Lee (2003)
(alert), 9 10. Lee (2003) (Cronbach's ɑ).84.87, (Cronbach's ɑ).81.83.,. 11. Cronbach's α.93.,, r=.498, p <.001,, r = -.339, p <.001. (The Revised Oxford Happiness Scale). Hills Argyle(2002) - (The Revised Oxford Happiness Scale). 29 6..,.,.. (Kim, Choi, & Cho, 2011) FACES (Ebner et al., 2010).,.
. 24, 96,, 288. 45x50mm. 8, 4:4. 1) -, 2) -, 3) -, 8:0, 7:1, 6:2, 5:3, 4:4, 3:5, 2:6, 1:7, 0:8 9 (Figure 1 ). 16 144(9x16). 6,. (PANAS),. 60cm, 8 2 (two alternative forced choice; 2AFC). E-prime 2 professional, 19 ( : 1290x1024). (+) 500ms 8 Figure 1 14. 3,,., /, /, /.. 144 ( ) 6, 30. 1.,, -, -, -
. X, Y, (Figure 2). 2 (cumulative distribution function: CDF), (data fitting). (parameters) (μ) (σ), 50% (point of subjective equality: PSE), (precision) ( ). GraphPad Prism 7.0(Motulsky, 1999), (least squares method)..,.,.,., (R 2 < 0.5),. - 2, - 2 4 ( 5% ). 3., PANAS (Table 1).,, ( : F(2, 150) = 1.77, p =.174; : F(2, 150) = 0.19, p =.981; Conditions Positive Affect PANAS Negative Affect Oxford Happiness Scale Neutral-Happy (n=51) 15.51(5.84) 11.27(6.62) 119.17(12.89) Neutral-Sad (n=49) 16.10(5.66) 11.02(6.46) 119.53(17.27) Happy-Sad (n=51) 17.66(6.40) 11.13(6.37) 123.74(16.73)
: F(2, 150) = 1.33, p =.269).,, F(1, 148) = 60.60, p <.001, (Lee, Kim, & Lee, 2003),, F(2, 148) =.987 p =.375. Figure 2,. Figure 2a b - -, Figure 2c-1 c-2 -.,
Figure 2c-1 c-2. Figure 2, ( 0.0 -> 0.5 <- 1.0 ), F(8, 1184) = 86.39, p <.001, -,, F(2, 148) = 2.98, p =.054. Figure 2,. Figure 3 Table 2., -, ( 50% ), (PSE) 0.475(SE ±.007, 95% CI [.460,.489]), 0.5, -.526(SE ±.007, 95% CI [.513,.540]) 0.5 (Figure 3 1a, 1b)., ( ) -.472(.14), -.534(.12), -.508(.07),, F(2, 142) = 3.779, p =.025. (Tukey, HSD), - - (d =.31 p =.019),. -.502(SE ±.005, 95% CI [.493,.512]).496(SE ±.005, 95% CI [.487,.506]) 0.5. (SD) -.248(SE ±.010, 95% CI [.228,.269]), -.254(SE ±.009, 95% CI [.236,.274]). -,.215(SE ±.007, 95% CI [.201,.228]),.215(SE ±.007, 95% CI [.202,.229]), -, -. -.208(.11), -.234(.10), -.199(.09), F(2, 142) = 1.686, p =.189. Figure 3.2 3.3 - - -
conditions x(ratio) y(response) Mean(PSE) SD(precision) R 2 Neutral-Happy (n=51) Happy faces Happy.475 [.46,.49].248 [.23,.27].84 Neutral-Sad (n=49) Sad faces Sad.526 [.51,.54].255 [.24,.27].86 Sad-Happy (n=51) Happy faces Happy.502 [.49,.51].215 [.20,.23].92 Sad-Happy (n=51) Sad faces Sad.496 [.49,.51].215 [.20,.23].92. Figure 3.2a, 50% (, 8 4 ), ( )., Figure 3.3a, 50% (, 8 4 ), ( ).,. Table 3,. - PANAS, r = -.303, p =.034,, r = -.314, p =.028.,. -, 0.1, r =.240, p = PSE PANAS PA score PANAS NA score Oxford Happiness scale PSE of Neutral-Happy condition -.303(.034) * -.067(.649) -.314(028) * PSE of Neutral-Sad condition.192(.186) -.096(.510).240(.097) PSE of Sad-Happy condition -.017(.907).006(.966) -397(.004) * p <.10, * p <.05
.097.. - ( ),,, r =.397, p =.004( )..,.., (, ),.,,, ( ). (4:4,, 0.5),.,.,. Yang (2013) /. -,,.,. - -,., - -,
.., (, Haberman & Whitney, 2007, 2009; Yamanashi Leib et al., 2012).,.,,.,.,,.,,.,. (anger superiority effect) (Bar-Haim et al., 2007; Hansen & Hansen, 1988; Yang, Kim, & Oh, 2006),.. (mood congruency effect) (Bouhuys, Bloem, & Groothuis, 1995; Bower, 1981; Niedenthal, Halberstadt, Margolin, & Innes-Ker, 2000)., Bouhuys, Bloem Groothuis(1995), ( vs ),,
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Analysis of Response Characteristics in the Judgment of Emotion for a Group of Emotional Faces Sewon Kim Hyun Jung Shin Bia Kim Donghoon Lee Department of Psychology, Pusan National University Facial emotion is an important social cue for inferring emotional states of other people. Psychological research using facial emotions has focused on the perception of individual emotional faces. However, in the ordinary life we may infer a group level emotion from multiple faces in a group, but little has been known about what kinds of factors influence this process. In the current study, we investigate the response characteristics of the group emotion judgment for a group of emotional faces which are composed of individual faces in different emotional categories with different ratios. The group facial emotion stimuli are composed of 1) neutral and happy faces, 2) neutral and sad faces, and 3) sad and happy faces in the 8:0, 7:1, 6:2, 5:3, 4:4, 3:5, 2:6, 1:7, 0:8 ratios. By this way, the level of emotional intensity of the group is manipulated into 9 steps. Participants in each condition performed a two alternative forced choice task by judging the overall emotion of a group facial stimulus into one of two response categories (e.g., Neutral-Happy). Analysis of response times for the judgment of the group emotion showed that the response time for judging the overall emotion was slow down as faces in the two different emotion categories mixed together with a similar ratio. The response ratio data were analyzed by a nonlinear data fitting procedure using a psychometric function, and the point of subjective equality (PSE) and the precision of each participant in each condition were estimated. In results, the mean PSE in the Sad-Happy condition was almost same as a hypothetical mean (0.5) and the precision was high. On the contrary, the mean PSE of the happy response in the Neutral-Happy condition was lower than 0.5 but the mean PSE of the sad response in the Neutral-Sad condition was higher than 0.5. Moreover, participants PSE of the happy response was negatively correlated with participants positive emotion levels as well as happiness scores, whereas participants PSEs of the sad response were positively correlated with participants happiness scores. These results imply that the judgment of emotion for a group of faces is influenced by bottom-up factors such as how the group is comprised of what kinds of emotional faces, and by top-down factors such as observers emotional states and traits. Key words : Group emotion, Facial expression, Crowd preception, Psychometric Function, Point of Subjective Equality (PSE)