Insights from cross-cultural memes: An empirical study on instagram and Douban

被引:0
作者
Zhang, Leihan [1 ]
Cao, Herui [1 ]
Yan, Qiang [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Econ & Management, 10 Xitucheng Rd, Beijing 100876, Peoples R China
基金
中国国家自然科学基金;
关键词
Visual memes; Cross-cultural diffusion; Emotions; Topics; Multimodal discourse; WORLD;
D O I
10.1016/j.tele.2024.102186
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
As one of the most prevalent types of memes, visual memes often transcend individual cultures and languages and reach broad online communities of disparate actors. However, how the intrinsic factors of visual memes shape cross-cultural diffusion and whether visual memes can positively promote digital cultural globalization remains unclear. To answer these questions, we identified 1147 visual memes with 11,729 instances from four online communities on Instagram and Douban and manually annotated the memes in three dimensions, i.e., form, content, and emotion. Then, regression and structural causal models were designed to investigate the intrinsic factors affecting cross-cultural diffusion. Empirical results reveal that memes expressing focused and positive emotions, conveying universal topics, sourcing from films, using short captions, and featuring African or Caucasian roles are more likely to attain cross-cultural diffusion. In contrast, the memes featuring female or Asian roles are just the opposite. Moreover, the structural analysis of emotions, topics, and social identities suggests that although the dominance of Western culture and male groups persists in cross-cultural memes, visual memes have the potential to challenge the hegemonic power structures. From the prism of cross-cultural diffusion, the connotation of memes is enriched-expressive repertoires using multimodal discourses that can act as bridges between different cultures and languages. In summary, this research uncovered the effects of the intrinsic factors of visual memes on cross-cultural diffusion using regression and causal models for the first time and can help perform effective memetic engagement across different communities and cultures.
引用
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页数:24
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