Short and silent gif motion-pictures, which people widely use today on mobile devices and instant messenger, play an essential role in the daily scenario of emotional communication via computer-mediated-communication, known as stickers or “Biao Qing Bao” in Chinese. Previous researches on relevant topics have proved there exists a misunderstanding of non-verbal symbols when people use it in digital communication. This research takes the cultural difference as the central aspect, tries to study the intercultural difference of peoples’ recognition of motion stickers, which users frequently used in mobile and desktop instant message applications.
The research collects emotional recognition result data from both Chinese and American participants via a web-based experiment. In the experiment, a participant firstly sees an emotion word that the program randomly selected from the word list consists of 17 words. He or she should choose one from the picture pair as the preferred image, which can express the given emotion words. After data collection, the researcher converts choices on motion stickers pairs from participants into scores of emotion strength via the TrueSkill algorithm developed by Microsoft. All further analyses based on converted ratings.
The research found that both data from Chinese and American participants show excellent consistency in each emotional word(rmin > 0.6). The study argues that facial expression of motion stickers can spread out recognizable emotions.
Further factor analysis indicates that there are several ‘basic’ emotional patterns in recognition of facial expressions of motion stickers on given emotion words, but the emotion pattern is not universal; it is partially interculturally consistent.
Firstly, in the result of the factor analysis of Chinese data, there exist several items that have negative loads on factors. It means that the corresponding component has a reversed effect on the given emotional structure. In detailed comparison, when classifying all emotion words into four factors, the data will result in the best solution, and Chinese and American share 3 of 4 factors in total, which provide evidence support that emotional recognition is interculturally consistent.
Secondly, in Chinese data, no corresponding ‘dislike’ factor exists in American data. In the meantime, there is a lack of relevant ‘humiliated’ factor in American data compared to Chinese data.
Lastly, emotional words that integrated as each unique factor dissolve into the other set of data. Specifically, for Chinese participants, happy absorbs ‘dislike’ and those two factors become an integrated concept, just like both sides of a coin. Correspondingly, the ‘ashamed’ factor from American participants disintegrates and reintegrates with other emotional words, resulting in a new ‘humiliated’ factor in Chinese participants. The researchers hold the opinion that liberal and individualistic cultures may have a possible impact on peoples’ emotional recognition.
In brief, the emotional recognition of motion stickers used in online communication derives from consensus created by media products. Its cross-cultural difference reflects the influence of a macro concept of social and culture, like social norms and language.