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The Own-Race Bias Effect and the Effects of Happy Facial Expressions during Face Recognition

The Own-Race Bias Effect

The own-race bias effect debits that, when comparing the memory of human faces, own-race faces are better remembered as compared to faces from other races (Chiroro, & Valentine, 1995). For instance, if individuals are presented with ‘target faces’ which are meant to be remembered and later shown the ‘target faces together  with the ‘filler faces’ which were not in the original presentation, the ability to recognize the original ‘target faces is minimal (Reyes & Segal, 2018). Studies have shown that individuals response criterion and discrimination accuracy is normally aggregated by the own-race bias (McKone et al., 2012). The differentiation process and perceptual learning nommally are the major influence of the own-race bias effect (Chiroro, & Valentine, 1995). This is because people usually became ‘experts’ of their own-race faces thus recognizing other faces is based on memory ability. Happy facial expression recognition usually is faster and more accurately than any different expression. However, people believe that detection in visual search of happy faces is less rapid than in angry faces ("Human Face Processing: From Recognition to Emotion," 2013). According to the study by Nummenmaa in 2015, detection of unhappy faces was observed even where the stimulus emotionality was rearranged or distorted. The same study concluded that happy faces have a recognition advantage as compared to neutral or angry faces and the memory processing of happy faces is secure and faster.

Studies suggest that happy faces recognition advantage is facilitated by various factors. According to Numenmaa 2015, various faces stimuli determine how fast a face can be recognized. The facial expression memory of various emotions especially the happy face occurs faster when the mouth is closed other than when an individual is smiling or with exposed teeth ( Nummenmaa, & Calvo,2015). In addition, the happy face advantage is reliable across all cultures. In 2015, around 57 dataset consisting of 21 cultures were reviewed ( Nummenmaa, & Calvo,2015). The dataset showed that the recognition of happy faces across all 21 cultures was high as compared to any other facial expression. There are various suggestion has been put into account why recognition of happy faces has an advantage (Chen, 2014). First, the effective uniqueness hypothesis suggests that it is easy to recognize the happy faces as most individuals found them pleasant. In addition, recognition of another facial expression like anger is considered to interfere with personal values ("Human Face Processing: From Recognition to Emotion," 2013). Secondly, the diagnostic hypothesis debits that specific facial characteristic like conspicuous smiles is normally associated with happiness and a sense of recognition (Chen, 2014). Finally, the frequency of occurrence hypothesis postulate that the frequency of happy faces in a social setting is highly experienced than any other faces thus easily recognized. These three account proves no other facial expression can be easily be remembered than happy faces. However, the theory of contact hypothesis suggests that the own-race bias effect might due to limited contact between different individuals. For instance, if someone lives in a cross-racial neighborhood, the degree of recognition of own-race faces and other race faces will be equal. In addition, other than living in an intergraded neighborhood, the influence of media, place of employment, tourism and personal experience with other races may affect the way individuals are able to recognize faces from other races.

The Effects of Happy Facial Expressions on Face Recognition

In this study, the faces from two races are included in the study. A total of 142 pictures of various faces were obtained from three databases. Both East-Asian and Caucasian faces were studied in which each consisted of 72 images. A total no of 110 participants was included where only 68 participants were used due to various problems. The experiment was conducted to explore the effects of facial emotional expression on the own-race bias effect.

The Signal Detection Theory is used to analyze data from experiments which possess ambiguous stimuli that can be either be generated by a signal processor by chance (Abdi, 2013).  The goal of Signal Detection Theory is to estimate two parameters from a given experiment. The first parameter usually referred to as d ’usually shows the strength of the signal (Abdi, 2013). The second parameter is called C, and it shows the strategy of the response of the participants ("Signal Detection Theory," 2018). Generally, the signal detection theory assumes that participant’s responses are as a result of a hidden variable ("Signal Detection Theory," 2018). In this study, the Signal Detection Theory is used to measure memory recognition.

In this study, a total number of 110 participants was used. However, only data from 68 individuals were applied due to various reasons.  All individuals consisted of both females and males. There were 29% males and 71% females making the number of women to be higher.  87% of all participants were right-handed and the rest 13% left handed. The mean age was 21.87, and the standard deviation age was 4.61 meaning all participants were adults.

The study used an experimental model. The experiment employed two races which include the East-Asian and Caucasians. In addition, two face expressions were used which include happy and neutral faces. The experimental design applied sigmoid detection theory to calculate memory discrimination (d’) which was used as the DV.

A total number of 72 East-Asian faces images were obtained from both the CUHK Face Database and DFH Database. A total number of 36 pictures from this category were portraited neutral-emotion faces, and the other 36 images were happy emotion faces.  Half of the photographs showed female, and the other half showed males of both types. All photos were of high quality measuring 16” by 20” print and a resolution of 1600 by 1200 pixels. The second group consisted of 72 Caucasian faces images selected from Radboud Faces Database. Thirty-six of the images were portrayed-neutral emotion faces and the other half happy faces. Half of the pictures showed male and the other half females. The quality and size of the pictures was similar as of the East-Asian faces images.

The procedure was programmed with E-prime 2.0.  During the study, the images in both groups were divided into two major trial sessions conducted over five days. Each session took two days with three rounds of presentations. During the first day, a total number of 24 images was presented from both East-Asia faces and Caucasian faces. The participants were presented with both six happy, and six neutral East-Asian male and females face images in the first round. The participants were later presented with both six happy and six neutral Caucasian faces images in the second round. The participants were left to rest until the second day where all first and second round images were represented again together with the additional six happy and six neutral new East Asia female and male face images and six happy and six neutral new Caucasian male and female face images. The participants were asked to recognize the first 24 pictures where the data were reconded. The procedure was repeated during the second session on the third and fourth day, and the fifth day the results were compiled.

Theories and Hypotheses Explaining the Happy Face Recognition Advantage

Results

Figure.1.1 A  bar graph representing participants reaction to both happy and neutral East-Asia and Caucasian face images.

The own-race bias effect suggests that people tend to remember faces of own race than other races ( Meissner., & Brigham, 2001). Considering that most people in Singapore are more familiar with Asia's faces than Caucasians, they can recognize East-Asians face easily. However, the results showed differently. The Happy Asians faces were recognized worse than Happy Caucasians faces. The expectation was that the happy Asians faces will be identified more accurately than the Caucasian faces. Furthermore, from the theory, the happy faces were expected to be identified with ease than the neutral faces in both groups (Wright, Boyd, & Tredoux, 2001). However, the happy faces and neutral faces in Caucasians were recognized similarly. In addition, the results showed that the neutral faces of the Asians were remembered better than the happy faces. The results from the whole experiments contradict the theory which creates a gap for more research and investigation. However, the study does not illustrate well whether the all the participants were Asians, whether they live with Caucasians neighborhood or Asians. The study had assumed since the participants live in Singapore, they can only recognize Asians better than Caucasians. Taking into account the theory of contact hypothesis, most of the participants might have been living in a neighborhood integrated with Caucasians. This might be the reason why they were able to recognize Caucasians faces more than East Asia. Individuals who have personal experience with other races have an increased ability to recognize them easily. For instance, the University has international students from all over the world. This has made students be familiar with all other races through positive contact. Therefore, all the students will be able to recognize both Caucasians and East Asia faces with ease.

References

Abdi, H. (2013). Signal Detection Theory (SDT). Retrieved from https://www.utdallas.edu/~herve/Abdi-SDT2007-pretty.pdf

Chen, J. (2014). Face recognition as a predictor of social cognitive ability: Effects of emotion and race on face processing. Retrieved from https://onlinelibrary.wiley.com/doi/pdf/10.1111/ajsp.12041

Chiroro, P., & Valentine, T. (1995). An investigation of the contact hypothesis of the own- race bias in face recognition. The Quarterly Journal of Experimental Psychology, 48(4), 879-894.

Human Face Processing: From Recognition to Emotion. (2013). Psychophysiology, 50, S20-S21. doi: 10.1111/psyp.12117

Li, Y., & Tse, C. (2016). Interference among the Processing of Facial Emotion, Face Race and Face Gender. Frontiers In Psychology, 7. doi: 10.3389/fpsyg.2016.01700

McKone, E., Stokes, S., Liu, J., Cohan, S., Fiorentini, C., Pidcock, M., ... & Pelleg, M. (2012). A robust method of measuring other-race and other-ethnicity effects: The Cambridge Face Memory Test format. PLoS One, 7(10), e47956.

Meissner, C. A., & Brigham, J. C. (2001). Thirty years of investigating the own-race bias in memory for faces: A meta-analytic review. Psychology, Public Policy, and Law, 7(1), 3-35.

Nummenmaa, L., & Calvo, M. G. (2015). Dissociation between recognition and detection advantage for facial expressions: a meta-analysis. Emotion, 15(2), 243–256.

https://doi.org/10.1037/emo0000042 Reyes, N., & Segal, S. (2018). An investigation of the effect of race-based social categorization on adults’ recognition of emotion. Retrieved from https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0192418

Signal Detection Theory. (2018). Retrieved from https://www.cns.nyu.edu/~david/courses/perception/lecturenotes/sdt/sdt.html

Wright, D. B., Boyd, C. E., & Tredoux, C. G. (2001). A field study of own-race bias in South Africa and England. Psychology, Public Policy, and Law, 7(1), 119-133.

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