ACM Transactions on Intelligent Systems and Technology · 2019 · 630 citations · 28 references
Social SciencesGeographyHuman-computer InteractionSocial GeographySocial Media AnalyticsSocial ComputingSocial MediaUser Behavior AnalysisSocial Media Geographies
Social media growth has made microblogging platforms like Twitter central to Cyber‑Physical‑Social Systems, yet geographic and cultural diversity complicates modeling user behavior. This study aims to compare microblogging users across countries and develop a Country‑Level Micro‑Blog User (CLMB) model to support CPSS applications. The CLMB model analyzes content, emotion indices, and relationship networks, and was evaluated on data from 16 highly active countries. Results show that small, cohesive populations prioritize social features, large loose groups use microblogs mainly for news, and reciprocal‑network countries employ more happiness‑expressing language.
As the rapid growth of social media technologies continues, Cyber-Physical-Social System (CPSS) has been a hot topic in many industrial applications. The use of “microblogging” services, such as Twitter, has rapidly become an influential way to share information. While recent studies have revealed that understanding and modelling microblog user behaviour with massive users’ data in social media are keen to success of many practical applications in CPSS, a key challenge in literatures is that diversity of geography and cultures in social media technologies strongly affect user behaviour and activity. The motivation of this article is to understand differences and similarities between microblogging users from different countries using social media technologies, and to attempt to design a Country-Level Micro-Blog User (CLMB) behaviour and activity model for supporting CPSS applications. We proposed a CLMB model for analysing microblogging user behaviour and their activity across different countries in the CPSS applications. The model has considered three important characteristics of user behaviour in microblogging data, including content of microblogging messages, user emotion index, and user relationship network. We evaluated CLBM model under the collected microblog dataset from 16 countries with the largest number of representative and active users in the world. Experimental results show that (1) for some countries with small population and strong cohesiveness, users pay more attention to social functionalities of microblogging service; (2) for some countries containing mostly large loose social groups, users use microblogging services as a news dissemination platform; (3) users in countries whose social network structure exhibits reciprocity rather than hierarchy will use more linguistic elements to express happiness in microblogging services.
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