关键词: 微信交流, 人格判断, 非语言线索, 透镜模型分析, 自我—他人一致性

Abstract: Computer-mediated communication (CMC) refers to the cluster of interpersonal communication technologies that are based upon the transfer and storage of information among interconnected networks of computers. Common CMCs include email, instant messaging, social networking sites, etc. WeChat is one of the most common CMC forms in China. It is generally believed that CMC lacks abundant nonverbal cues, which makes it difficult to conduct effective emotional communication and to form accurate personality impression. However, numerous studies have found that there is no lack of non-verbal communication in CMC, and users have created many emotional cues to adapt to this new communication situation, such as “emoticons”, “word repetition” and so on.
Emoticons and other nonverbal cues can be used to enhance the perceived richness of CMC, and increase the accuracy of message interpretation. CMC nonverbal helps avoid the effects of ambiguity in online communication, by supporting interactors decipher intent from ambiguous messages. The purpose of this study is to explore the use of CMC nonverbal cues and whether they can affect the accuracy of personality judgment in WeChat communication situations by using the WeChat software platform.
Procedure: In the experiment, 146 participants were divided into three groups (50, 46, 50) and conducted pair-to-pair WeChat instant chat for 5min, 10min, and 20min respectively. All 146 participants evaluated each other's personality after the chat and were asked to submit screenshots of the chat transcripts via e-mail. Finally, we conducted classified statistics and lens model analysis on the non-verbal cues in chat materials, including “word count”, “message amount”, “emoticons”, “punctuation”, and “word repetition”.
The results showed that: (1) Except for neuroticism, the total self-other agreement (SOA) of the other four traits reached a significant level, and the average SOA increased with the length of interaction; (2) The frequency of non-verbal cues in WeChat communication was 55.8%; (3) In the 10min and 20min groups, “word count” and “message amount” were diagnostic cues of extroversion, while “emoticons” and “word repetition” were diagnostic cues of agreeableness and openness; (4) The sensitivity of observers to cues of agreeableness and extroversion in the 10min group and to cues of all traits in the 20min group were significant, and improved with the increase of interaction duration.
These results suggest that WeChat communication-based personality judgments have certain accuracy, and the non-verbal cues are closely related to the accuracy of personality judgments, especially extroversion, openness, and agreeableness. Non-verbal cues are common in WeChat communication. Individuals will use a lot of non-verbal information during WeChat interaction, and observers will infer the level of personality traits of the target based on this information. However, only by providing a long enough communication time(20min) can the target present effective nonverbal cues, which can be used by the observer to infer relevant traits and make accurate judgments.

Key words: WeChat communication, personality judgment, nonverbal cues, lens model analysis, self-other agreement