social network analysis

Memetic Moments: The Speed of Twitter Memes

ABSTRACT

This paper examines how speed shapes internet culture. To do so, it analyses ‘memetic moments’ on Twitter, short-lived and rapidly circulated memes that quickly reach saturation. The paper examines two ‘memetic moments’ on Twitter in 2018 and 2019 to assess how they develop over time. Each case study comprises a week’s worth of relevant tweets that were analysed for temporal patterns. We analyse these ‘memetic moments’ through Lefebvre’s (2004) work on rhythmanalysis, arguing that the temporal patterns of memes on Twitter can be understood through his concepts of repetition, presence and dialogue. While seemingly trivial, memetic moments underscore the didactic relationship between social media and news media while also providing a way to approach complex social issues.

The Network Life of Non-biomedical Knowledge: Mapping Vietnamese Traditional Medicine Discourses on Facebook

ABSTRACT

Traditional medicine is hugely popular throughout Southeast Asia and other parts of the world. The development of the internet and online social networks in these contexts has enabled a significant proliferation of non-biomedical knowledge and practices via platforms such as Facebook. People use Facebook to advocate for non- biomedical alternatives to unaffordable biomedicine, share family medical recipes, discuss medicinal properties of indigenous plants, buy and sell these plants, and even crowdsource disease diagnoses. This paper examines the network characteristics of, and discourses present within, three popular Vietnamese non-biomedical knowledge Facebook sites over a period of five years. These large-scale datasets are studied using social network analysis and generative statistical models for topic analysis (Latent Dirichlet allocation). Forty-nine unique topics were quantitatively identified and qualitatively interpreted. Among these topics, themes of religion and philanthropy, critical discussions of traditional medicine, and negotiations involving overseas Vietnamese were particularly notable. Although non-biomedical networks on Facebook are growing both in terms of scale and popularity, sub-network comment activities within these networks exhibit ‘small world’ characteristics. This suggests that social media seem to be replicating existing social dynamics that historically enable the maintenance of traditional forms of medical knowledge, rather than transforming them here.