Mining Twitter for Cultural Patterns

Abstract

Adaptive applications rely on the knowledge of their users, their needs and differences. For instance, in the scope of the ImReal project, a training process is adapted to users’ origins using information on user cultural backgrounds. For inferring culture-specific information from available microblogging content, we monitor the usage of Twitter elements such as hashtags, web links and user mentions. We analyze how users from different cultural groups employ these elements when they tweet. This allows us to get insights on microblogging patterns for different cultural groups of Twitter users and an outlook into user preferences and traits towards sharing content with others, time preferences, and social networking attitudes. Potentially, such information can be used for adapting software applications in accord with user culture-specific behavioral traits.