Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Nowadays, with the rapid development of the Internet, online communication has become increasingly popular and popular. However, due to the lack of nonverbal cues in face-to-face communication, it is difficult for people to detect the emotional state of each other, which hinders normal communication. Emoji, which compensate for nonverbal cues in online communication, have been introduced into cyberspace to compensate for the absence of gestures and facial attributes in online communication, and have been developing constantly. The development of Emojis has gone through Emoticon composed of ASCII characters, Emoji of pictographic icons and now emerging more vivid and interesting stickers. This paper will mainly comb, analyze and summarize the functions, influencing factors and interaction mechanisms of Emoji in network communication, as well as the current application of Emoji in different fields, and put forward the future research direction of Emoji based on the current research status of Emoji. At the beginning, Emoji is borrowed from Japanese animation symbols, and gradually developed into a widely used image symbol system. Since the creation of Emoji by Shigetaka Kurita in 1999, it has been enriched and developed continuously At present, Emoji has become a tool commonly used around the world to replace non-verbal cues such as body gestures and facial expressions in digital communication. In the process of continuous use in Internet communication, Emoji has been equipped with many functions, including expressing emotions, enhancing expression, changing tone, maintaining or enhancing interpersonal relationship, etc. At the same time, the use of Emoji is also affected by many factors, including age, gender, culture, context and platform. In addition, we also explore the interactive mechanism of Emoji in online communication from the perspective of symbol interaction theory, so as to clearly reveal the specific interaction process of people in online communication through Emoji. At present, with the continuous development and widespread use of Emoji, its application scope has been extended to many other fields besides Internet communication. In the field of sentiment analysis, Emoji has become an important object of sentiment analysis due to its rich emotions. In psychometrics, Emoji has been developed into a nonverbal tool for evaluating personality and depression which has the same reliability and validity as text items. In the field of commercial marketing, Emoji has begun to play a role in advertising marketing and attracting consumers, and can measure consumers' food-related emotions in the form of questionnaires. In the field of legal judgment, Emoji has gradually become a powerful evidence in judicial trials due to its widespread use. Through the above analysis and summary, we put forward the future research direction of Emoji from the following aspects: (1) explore the application and future development trend of Emoji in online communication; (2) study on the application of Emoji in other fields; (3) further explore the neurophysiological mechanism of Emoji; (4) discuss the positive effect of Emoji in online communication from the perspective of cognitive processing.
Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： In virtual reality (VR), rotating the head to select a moving target is common. A moving target involves two general directions, that is movement toward or away from a user; thus, knowing the characteristics difference between selecting the approaching target (interception movement) and receding target (pursuit movement) is important for designing an efficient user interface. In this study, 17 participants (7 males; mean age = 22.5 ± 2.5 years) were given an Oculus Rift helmet-mounted display to wear and instructed to complete a task in a VR environment. They were required to position a small opaque sphere (cursor) that appeared randomly on the left or right side of the visual field into a larger half-transparent moving sphere (target) on the other side of the visual field quickly and accurately by rotating their head. The target moved randomly toward or away from the cursor horizontally, which were both at the participants’ eye height, with a depth of 3 meters. The diameter of the cursor was fixed at 4°. The initial movement amplitude (A; distance between the center of the cursor and target; 20° and 40°), the target tolerance (TT; size difference between the target and cursor; 4°, 6°, and 8°), and the target’s moving velocity (V; 0.5 m/s, 1 m/s, 1.5 m/s, and 2 m/s) were varied. The cursor movement paths were divided into three phases for analysis: acceleration, deceleration, and correction. Results showed that the average total movement time (MT) of selecting receding targets was significantly larger than that of selecting approaching targets and the two movements performed differently under different factors. A and TT had a similar influence on the total MT for both movements, which increased as A increased and TT decreased. In contrast, V had an inverse effect on the total MT for the two movements. A large V leaded to a long total MT for the pursuit movement, whereas the total MT for the interception movement decreased as V increased. Moreover, the interception movement showed a light U-shaped relationship between the total MT and V, with the lowest point at 1.5 m/s when A was 20°. The two movements were further compared in the three phases. The outcome showed that the MT of pursuit movement was only longer in the acceleration phase and deceleration phase compared with the interception movement, while the MTs of two movements were very close in the correction phase. Moreover, the three factors had different impact on the two movements in three phases. In the acceleration phase, MT increased for the pursuit movement but decreased for the interception movement as A decreased and V increased. In the deceleration phase, although MT was positively related to A and negatively related to V for both movements, the MT of interception movement increased more quicky as A increased and decreased more quickly as V increased as compared to the pursuit movement. In the correction phase, the TT had a same impact on the MT for both movements, which decreased with an increase of TT. Moreover, the increasing V and A increased the MT for the pursuit movement, while the MT of the interception movement was not affected by both V and A. Based on the findings, a model was proposed to depict the relationship between the total MT and the three factors, which fit the participants’ performance well. This study showed that the pursuit and interception movements had different characteristics. Selecting a receding target was more difficult than selecting an approaching target via head rotation, and A and V, but not TT, had a different impact on human performance for the two movements. The empirical findings suggested the importance of considering both movements separately when designing a user interface. The model provides a valid method for quantitatively evaluating the characteristics of human performance in selecting moving targets.
Subjects: Psychology >> Industrial Psychology submitted time 2022-04-22
Abstract：
In virtual reality (VR), rotating the head to select a moving target is common. A moving target involves two general directions, that is movement toward (chasing) or away (interception) from a user; thus, knowing the characteristics of the two movements is important when designing an efficient user interface.
In this study, 17 participants (7 males; mean age = 22.5 ± 2.5 years) were given an Oculus Rift helmet-mounted display to wear and instructed to complete a task in a VR environment. They were required to position a small opaque sphere (cursor) that appeared randomly on the left or right side of the visual field into a larger half-transparent moving sphere (target) on the other side of the visual field quickly and accurately by rotating their head. The target moved randomly toward or away from the cursor horizontally, which were both at the participants’ eye height, with a depth of 3 meters. The diameter of the cursor was fixed at 4°. The initial movement amplitude (A; distance between the center of the cursor and target; 20° and 40°), target tolerance (TT; size difference between the target and cursor; 4°, 6°, and 8°), and target’s moving velocity (V; 0.5 m/s, 1 m/s, 1.5 m/s, and 2 m/s) were varied. The cursor movement paths were recorded and divided into three phases: acceleration, deceleration, and correction.
Results showed that A and TT had a similar influence on the total movement time (MT) for both movements, and the total MT increased as A increased and TT decreased. Moreover, V had an inverse effect on the total MT for the two movements. A large V led to a long total MT for the chasing movement, whereas the total MT for the interception movement decreased as V increased. In addition, the interception movement showed a light U-shaped relationship between the total MT and V, with the lowest point at 1.5 m/s when A was 20°. The two movements were further compared in the three phases, and the MT outcome showed that only TT had the same effect on both movements. Specifically, in the acceleration phase, MT increased for the chasing movement but decreased for the interception movement as A decreased and V increased. In the deceleration phase, MT was positively related to A but negatively related to V for both movements. In the correction phase, the increasing V and reduced TT increased MT for both movements, and only the MT for the chasing movement was positively proportional to A. The MT difference between the two movements was observed in the acceleration and deceleration phases, whereas the MT for the two movements was indistinguishable in the correction phase. Based on the findings, a model was proposed to depict the relationship between the total MT and three factors, which fit the participants’ performance well.
This study showed that the chasing and intercepting movements had different characteristics. Selecting a receding target was more difficult than selecting an approaching target via head rotation, and A and V, but not TT, had a different impact on human performance for the two movements. The empirical findings suggested the importance of considering both movements separately when designing a user interface. The model provides a valid method for quantitatively evaluating the characteristics of moving targets.
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