Studying Human Behavior in Online Games in Response To Color and Movement

Abstract

Human cognition was initially studied around 300 BC by Aristotle because of his interest in how the human mind works and how it affects our day-to-day experiences. In the 21st century, we have realized that the human mind is complex and unique for each individual, making the study of human cognition challenging. In this investigation, human cognition is studied in response to colors and movements on a display. A game of six levels was programmed using Java language in the GitHub software, and subjects were asked to choose five out of 20 bubbles presented to them at each level. The levels each involve a combination of red bubbles, black bubbles, red shaking bubbles, and black shaking bubbles. Subjects were asked to take a screenshot of the “results page”, which showed how many bubbles of each “type” (i.e. shaking, still, red, black) were chosen, and send the data to a specified email/phone number. A One-Way Analysis of Variance for 2 Correlated Samples was used to compare the data obtained from each level. Then, using ANOVA statistics, the values of the mean captured and the standard error of the data in each level were compared. This analysis showed a statistically significant difference between the selection of red and black bubbles (preference for red bubbles) - with a 91.5% mean capture of red bubbles amongst black bubbles and red bubbles (p-value < 0.0001) and a 95.5% mean capture of shaking red bubbles amongst shaking black bubbles and shaking red bubbles (p-value < 0.0001). This analysis also showed a statistically significant difference between still and shaky bubbles (preference for shaking bubbles) - with a 91.6% mean capture of shaking red bubbles amongst red bubbles and shaking red bubbles (p-value < 0.0001) and a 92.1% mean capture of shaking black bubbles amongst black bubbles and shaking black bubbles (p-value < 0.0001). This indicates that subjects are motivated by colors and movements when presented with a still black stimulus, a still red stimulus, a shaky black stimulus, and a shaky red stimulus and that red is preferred to black when testing color preferences and shaking is preferred to still when testing movement preferences, accepting the alternative hypothesis. Eventually, data gathered from this study will provide evidence that there is a wider utility for colors and movements of certain patterns in trading systems design, pilot heads-up displays, video games, and any place where dashboards/head-up displays are used - including television programs.

Background

Many studies have been conducted to show that certain colors are associated with certain moods/situations (Aslam, 2006; Lee et al., 2015; Murray and Deabler, 1957; Na and Suk, 2014; Schaie, 1961b, 1961a; Wexner, 1954). Red, for example, is frequently associated with mainly negative experiences and is seen as an aggressive color in relevance to blood and danger (Kuniecki et al., 2015). Furthermore, specific colors appeal to our eyes and hold our attention. Red, being one of these colors, captures the attentional guidance of the human eye more than the other colors do, and therefore, other colors look less “appealing” than red (Andersen, Maier, 2019).

Previous research demonstrates that gamification is a main motivational design that ensures players stay engaged (Hassan, Dias, Hamari, 2018), so to test that red is the most attractive color, an online game was developed to track user engagement when presented with an array of colored spheres. Gamification increases engagement in online games because it motivates players to re-engage with the game repeatedly to unlock premier content. Additionally, it motivates players with exclusive updates that could include content such as new levels or different gaming modes (Hamari, J., & Koivisto, J., 2015). Gamification not only leverages a player's external motivation (ie. coming from outside goals that help the player do better in the game) but also internal motivation. Internal motivation comes from the players themselves and their personal goals for the game, which often has a positive effect on the player’s actions (Hamari, J., & Koivisto, J., 2015). Gamification features, therefore, ensure an engaging experience that motivates the player to stay committed and continue playing (Hassan, Dias, Hamari, 2018).

One study by Kuniecki et al. provides evidence that the color red is an attractor and therefore can lead human beings to be distracted from other colors (Kuniecki et al., 2015). Participants were seated 70 centimeters away from a screen with a neutral gray background and were asked to look at the screen. Before participating in the study, they were informed that a pair of images would be flashed and were told to ignore these images. The pair of images, featuring snakes (a species that is typically associated with danger), consisted of either one red-colored image and one non-red-colored image, or two non-red-colored images. Then, an asterisk, representative of the target, appeared on the screen for 150 milliseconds on either the left or right side of the screen. The participants were asked to quickly respond to where the asterisk was flashed on the screen, by pressing the button corresponding to the location of the asterisk on the screen, with their left or right thumb, accordingly. Overall, most participants responded that the target was on the side where the red image flashed, showing a pattern that indicates red is an effective distractor. Additionally, this study demonstrates that an electronic method of data collection can be done to assess human behavior (Kuniecki et al., 2015).

Another study by Racey, C. et al. provides evidence that individuals have specific preferences for certain hues (2019). Participants were chosen voluntarily and were pre-screened for correct vision and color blindness. Twenty-four chromatic stimuli, presented in the form of colored boxes, were colored in the saturated, light, and dark versions of eight hues: red, orange, yellow, chartreuse, green, cyan, blue, and purple. Participants were shown all stimuli and asked to choose the color they liked the most and the color that they liked the least. Then, each hue was shown to the participants and they were asked to rate them on a scale of “not at all” and “very much.” From the data, researchers concluded that the most preferred colors were saturated blues and greens and that the least preferred colors were dark yellow and dark orange. This study supports that certain colors are perceived to be attractive and that certain hues can differentially engage human behavior and attention (Racey, C. et.al, 2019).

The data gathered from these games support the current evidence that luminance and contrasts within a single color do not matter and that red is the most attractive color (Fuller, S., & Carrasco, M., 2006). However, to establish whether or not red is the most attractive color, much more data will need to be gathered.

Based on these studies, I hypothesized that, in an online game, the players will be affected by the randomized movement of black bubbles and red bubbles of varied hues because people will be more attracted to the red bubbles than the black bubbles. I attempted to distract my subjects from the red bubbles by asking them to capture as many black bubbles as possible (with the incentive of extra points awarded for black bubbles captured). I quantified how distracted the subjects were from the task by quantifying how many red bubbles were captured. Additionally, I tested whether participants would preferentially choose one shade of the red bubbles over the other available shades. I designed the game in OpenProcessing, a flexible software sketchbook that uses Java language, and created radio buttons, each holding a different mode of the game so that I could put all three experimental arms into one program.

The positive control experiment in my study was created to replicate the study with the snakes and show that red is more engaging and, therefore, be chosen preferentially over other shades when the subjects are not motivated by a point system. In this experiment, red (red with a standard red hue) bubbles and tomato (red with an orange hue) bubbles were chosen because red was hypothesized to be more engaging and orange was found to guide the least attention (Racey, C. et al., 2019, Andersen, Emil & Maier, Anja., 2019). Therefore, in the positive control experiment, it was hypothesized that subjects would prefer the red bubbles over the tomato bubbles. The negative control experiment tested if subjects followed instructions and were motivated by a point system to choose the black bubbles over red. However, it was anticipated that the minor points awarded from the red bubbles were enough to motivate subjects to deviate from the central objective of getting as many points as possible. The experimental arm of this study was created to test whether the red bubbles would be preferred over maroon (red with a brown hue) bubbles and crimson (red with a purple hue) bubbles, with both hues having low attentional guidance (Racey, C. et al., 2019, Andersen, Emil & Maier, Anja., 2019).

Throughout all modes of this preliminary study’s game, the black bubbles were always chosen over the other shades of red-hued bubbles (17.67% of the total black bubbles chosen over 9.14% of the total red bubbles chosen in the negative control and 30.56% of the total black bubbles chosen over the 7.36% of the total red bubbles chosen, 6.80% of the total tomato bubbles chosen, 8.40% of the total maroon bubbles chosen, and 7.75% of the total crimson bubbles chosen in the experimental). This indicates that the subjects followed the rules. However, when they deviated from the core objective, the subjects’ preference for one hue of red over other hues completely disappeared (7.36% of the total red bubbles chosen, 6.80% of the total tomato bubbles chosen, 8.40% of the total maroon bubbles chosen, and 7.75% of the total crimson bubbles chosen in the experimental), suggesting that subjects are more attracted towards gaining a profit than a specific color.

It is unclear why varied hues of a single color do not differentially distract users from a task when previous publications indicate that there is a clear hue preference amongst colors (Racey, C. et al., 2019, Andersen, Emil & Maier, Anja., 2019). To investigate this preliminary result further, a new version of the positive control should be created to test the preference for all four hues of red, without any black bubbles present. Additionally, to test if the red bubbles are preferred over the black bubbles, a new version of the negative control should be created to test the preference for red without the profit difference.

Given the results of the preliminary study, more data needed to be gathered to establish whether or not red is the most attractive color. As I already conducted experiments with the colors red and black, I added in a new variable of movement to test whether or not this changed the subjects’ preferences to red and black. Humans are stimulated by objects in motion as they lead us to notice and perceive these objects as potential threats - making us pay closer attention to them, whereas a stationary object does not attract us in that way (Konrath, 2017). I hypothesized that red moving objects will attract more attention than black stationary objects because people are scientifically more attracted to red than black and the human brain has a bias towards motion.

(Kuniecki, Pilarczyk, Joanna, & Szymon, 2015)

(Racey, C., Franklin, A., & Bird, C. M., 2019)

Positive Control

Negative Control

Experimental

Methods

Throughout all levels of the game, the subjects’ preference for still and shaking bubbles (along with their preference for the red and black bubbles) is tested. The six levels of the game are broken down into distinct experiments. Two levels display the positive control, two levels display the negative control, and two levels display the experimental group.

In the positive control levels, still red and black bubbles are displayed in level 1, and shaking red and black bubbles are displayed in level 4. It is already known from previous research that the color red is more attractive than black, so the positive control levels confirm prior findings that subjects preferentially choose red over black (Andersen, Maier, 2019). Moving on, the negative control displays shaking red bubbles and still red bubbles in level 2 as well as shaking black bubbles and still black bubbles in level 6. In this control, the new variable of movement is introduced. The human brain’s bias towards motion should result in subjects choosing the shaking bubbles over the still in both levels (Konrath, 2017). Therefore, in the absence of color differences, the negative control experiment tests whether there is a preference towards moving objects. Finally, in the experimental arm, still red bubbles and shaking black bubbles in level 3 as well as shaking red bubbles and still black bubbles in level 5 are displayed. The hypothesized result for this experiment is that shaking red bubbles are the most attractive and preferentially chosen out of all available bubbles. The experimental arm of this study is created to test whether there is a synergistic preference for objects that are both red and moving. The results of these levels will distinguish how movement and color contribute to subject engagement in a video game.

CODE FOR GAME

Figure 1. A hyperlink to a full procedure describing how to code the game in GitHub (including instructions with how to set up a GitHub account)

Once the game was set up, all data collection was fully online. One of the many benefits of remote data collection is that subject recruitment is continuous and requires minimal communication between the subject and lead scientist. In addition, subjects can play the game on any smart device and immediately send over a screenshot of their results. The low time commitment, simplicity of participating, and ease of online engagement, allowed for quick subject recruitment. All three experimental arms, as well as the three experimental replicas for each arm, are embedded into one gameplay - simplifying the process for subjects. An IRB (Institutional Review Board) application was completed and approved by the Berkeley Carroll School IRB, to ensure the study would have no serious/harmful impact on the subjects nor violate subject privacy.

This study recruited participants ages 13 to 30 to target subjects that had experience with smart devices. 68 percent of adults own smartphones (Pew Research Center, 2015) and 67 percent of teenagers own smartphones (Common Sense Media, 2015), so the study honed in on this fixed age group to provide less bias in the data. All subjects were recruited through a social media announcement of the game’s release and they were screened for color blindness and for fitting in the appropriate age criteria.

To ensure that the subjects’ level of attention was high during the game, a text with the game level (i.e. “Playing Level (1, 2, 3, 4, 5, 6)”) and the instructions, “Choose any 5 items” provided the subjects with a specific task that kept them motivated throughout the study. Additionally, in between each level of the game, the screen paused and switched over to the next level, a transition that allowed the subjects to anticipate change. According to the Cognitive Load Theory, games that demand higher cognition of the player are essential to increase attention and dedication to the task of the game (Sweller, 1988, Sweller et al., 1988).

To collect the data, all subjects were asked to take a screenshot of the “results page” that was displayed at the end of the game. The “results” page showed how many bubbles of each “type” (i.e. shaking, still, red, black) were chosen from each level. Subjects were asked to send the data to the specified email/phone number. Finally, the data was organized into a Google Folder and then plugged into a Google Spreadsheet by counting the number of times each subject chose each type of bubble; the emails containing the data were deleted for the anonymity of the participating subjects. There were 15 total bubbles a subject could choose for each level. The first part of data analysis was to remove outliers. Since there were over 100 data points, any major outliers would statistically stand out in the data. To determine outliers, the interquartile range was calculated for each dataset. Once the five outliers in the study were identified, all the data generated from those specific individuals were removed from the study. To analyze the data, an independent sample t-test was done to determine if there is a significant difference between data sets. This type of t-test is used to determine if there is statistical evidence that the mean of one of the associated populations of the two populations present in each of the controls is statistically significant. ANOVA (Analysis of Variance) was previously used for analyzing preliminary studies, such as the previous study conducted on the preference of a specific hue of red amongst several red hues. However, since only two sets of data for each of the experimental arms are collected, an independent sample t-test is more appropriate.

Results

In each of the results obtained, the P-value is less than 0.0001. Essentially any P-value less than 0.05 means that there is a statistical significance between the datasets presented. Therefore, there is a statistically significant difference between the selection of red and black bubbles and a statistically significant difference between still and shaky bubbles - which indicates that subjects are adequately motivated by the colors and movements when presented with a still black stimulus, a still red stimulus, a shaky black stimulus, and a shaky red stimulus. Overall, all data supports our hypothesis that in this game testing color preference amongst red and black and movement preference amongst still bubbles and shaky bubbles, the color preference will be red over black, and the movement preference will be shaky bubbles versus still bubbles.

Figure 1 In the first round of the game, subjects were asked to select 15 bubbles from still black bubbles and still red bubbles. The bars shown above provide the mean number of still black bubbles chosen by all subjects (indicated by the black bar) and the mean number of still red bubbles chosen by all subjects (indicated by the red bar) as well as standard error bars. Tests to gather these values were computed by the One-Way Analysis of Variance for 2 Correlated Samples provided by vassarstats.net.

Table 1: Mean Capture and Standard Error of Still Black Bubbles and Still Red Bubbles

Figure 2 In the fourth round of the game, subjects were asked to select 15 bubbles from shaky black bubbles and shaky red bubbles. The bars shown above provide the mean number of shaky black bubbles chosen by all subjects (indicated by the dark gray bar) and the mean number of shaky red bubbles chosen by all subjects (indicated by the dark red bar) as well as standard error bars. Tests to gather these values were computed by the One-Way Analysis of Variance for 2 Correlated Samples provided by vassarstats.net.

Table 2: Mean Capture and Standard Error of Shaky Black Bubbles and Shaky Red Bubbles

Figure 3 In the second round of the game, subjects were asked to select 15 bubbles from still red bubbles and shaky red bubbles. The bars shown above provide the mean number of still red bubbles chosen by all subjects (indicated by the red bar) and the mean number of shaky red bubbles chosen by all subjects (indicated by the dark red bar) as well as standard error bars. Tests to gather these values were computed by the One-Way Analysis of Variance for 2 Correlated Samples provided by vassarstats.net.

Table 3: Mean Capture and Standard Error of Still Red Bubbles and Shaky Red Bubbles

Figure 4 In the sixth round of the game, subjects were asked to select 15 bubbles from still black bubbles and shaky black bubbles. The bars shown above provide the mean number of still black bubbles chosen by all subjects (indicated by the black bar) and the mean number of shaky black bubbles chosen by all subjects (indicated by the dark gray bar) as well as standard error bars. Tests to gather these values were computed by the One-Way Analysis of Variance for 2 Correlated Samples provided by vassarstats.net.

Table 4: Mean Capture and Standard Error of Still Black Bubbles and Shaky Black Bubbles

Figure 5 In the third round of the game, subjects were asked to select 15 bubbles from still red bubbles and shaky black bubbles. The bars shown above provide the mean number of still red bubbles chosen by all subjects (indicated by the red bar) and the mean number of shaky black bubbles chosen by all subjects (indicated by the dark gray bar) as well as standard error bars. Tests to gather these values were computed by the One-Way Analysis of Variance for 2 Correlated Samples provided by vassarstats.net.

Table 5: Mean Capture and Standard Error of Still Red Bubbles and Shaky Black Bubbles

Figure 6 In the fifth round of the game, subjects were asked to select 15 bubbles from still black bubbles and shaky red bubbles. The bars shown above provide the mean number of still black bubbles chosen by all subjects (indicated by the black bar) and the mean number of shaky red bubbles chosen by all subjects (indicated by the dark red bar) as well as standard error bars. Tests to gather these values were computed by the One-Way Analysis of Variance for 2 Correlated Samples provided by vassarstats.net.

Table 6: Mean Capture and Standard Error of Still Red Bubbles and Shaky Black Bubbles

Discussion

In both positive control experiments, subjects chose red bubbles over black bubbles - regardless of movement, which replicates prior findings that red is the most attractive color (Andersen, Maier, 2019). In the first positive control experiment (Table 1, Figure 1), out of a possible 15 bubbles, the mean capture of still black bubbles was 1.27 bubbles versus the mean capture of still red bubbles, which was 13.73 bubbles (P<0.0001, One-Way ANOVA Test for Independent Samples). In the second positive control experiment (Table 2, Figure 2), out of a possible 15 bubbles, the mean capture of shaky black bubbles was 0.67 bubbles versus the mean capture of shaky red bubbles, which was 14.33 bubbles (P<0.0001, One-Way ANOVA Test for Independent Samples). Therefore, in this mode testing a red stimulus versus a black stimulus, the results obtained support the conclusions made by Andersen and Maier.

Humans are stimulated by objects in motion as they lead us to notice and perceive these objects as potential threats - making us pay closer attention to them, whereas a stationary object does not attract us in that way (Konrath, 2017). In both negative control experiments, subjects chose shaky bubbles over still bubbles - regardless of color. In the first negative control experiment (Table 3, Figure 3), out of a possible 15 bubbles, the mean capture of still red bubbles was 1.26 bubbles versus the mean capture of shaky red bubbles, which was 13.74 (P<0.0001, One-Way ANOVA Test for Independent Samples). In the second negative control experiment (Table 4, Figure 4), out of a possible 15 bubbles, the mean capture of still black bubbles was 1.19 bubbles versus the mean capture of shaky black bubbles, which was 13.81 bubbles (P<0.0001, One-Way ANOVA Test for Independent Samples). Therefore, in this mode testing a shaky stimulus versus a still stimulus, the results obtained support the conclusions made by Konrath.

The experimental control experiments demonstrate that subjects are motivated by the color red and movement. Thus, one can surmise that subjects would have an even higher engagement for objects that are red and move. In the first experimental control experiment (Table 5, Figure 5), out of a possible 15 bubbles, the mean capture of still red bubbles was 11.57 bubbles versus the mean capture of the shaky black bubbles, which was 3.43 bubbles (P<0.0001), One-Way ANOVA Test for Independent Samples). In the second experimental control experiment (Table 6, Figure 6), out of a possible 15 bubbles, the mean capture of still black bubbles was 1.53 bubbles versus the mean capture of shaky red bubbles, which was 13.47 bubbles (P<0.0001, One-Way ANOVA Test for Independent Samples). Therefore, these results support that subjects prefer shaking bubbles over still bubbles. Previous studies have shown an increased activation across the human brain in response to the dynamic movement of non-rigid 3D materials (Schmid, A., Boyaci, H., & Doerschner, K, 2020). Thus, these results are in line with current findings on gaming engagement.

Although all three experimental arms support the initial hypothesis that subjects have a preference towards a red, moving stimulus over a black, still stimulus, further experimentation is needed to verify these results and determine if it applies to a wider array of colors and movements. This future study would require a larger group of subjects (eg. 1000 total subjects) that would first have to participate in this current study to verify that the results obtained stay the same. A larger group could be obtained using the same recruitment methods (via email) over a longer period. In this current study, I gathered data from people all over the world - primarily from people in the United States and India, between the ages of 13 and 30. Given that teenagers and millennials are more easily distracted, the results of this study may be dependent on the age of the participants. (University of Illinois at Urbana-Champaign, News Bureau, 2014). To assess this limitation, participants from a wider range of geographic locations and ages will need to be recruited. Furthermore, an experiment testing reaction time to different stimuli could be a useful future direction of this work (Maslovat, D., Klapp, S., Forgaard, C., Chua, R., & Franks, I, 2019). In this experiment, subjects will be provided three keyboard keys - left (L), middle (M), and right (R) - with three different stimuli and asked to press the key corresponding to the position of the stimuli they noticed first. This type of cognitive research has many real-world applications because knowing how digital displays engage quick user responses has immediate applications to the design of trading systems, pilot head-up displays, video games, dashboards, etc.

Conclusion

Overall, all data supports the hypothesis that subjects prefer red over black, shaky bubbles over still bubbles, and shaky red bubbles over all other color/movement combinations presented. Therefore, the data accepts our alternative hypothesis that red moving objects will attract more attention than black stationary objects because people are scientifically more attracted to red than black and the human brain has a bias towards motion.

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Shreya B '21

Shreya is presenting her research on human cognition in response to color and movement. Since ninth grade, she has been a student pilot - flying a Cessna 172 Skyhawk - and with over 100 hours of flying time, she is getting her private pilot license this summer. As a pilot who is partially colorblind, Shreya has always been fascinated by pilot head-up displays in how they use colorful blinking lights to communicate how high or low the aircraft is as the pilot descends onto the runway. Over the last two years, Shreya furthered her interest in cognition by developing two online games in Java language that showed subjects’ preference for a specific color/movement. She hopes to continue her research by developing new programs testing reaction times of seeing specific colors and movements to examine cognition further.

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