Twitter is one of the top-growing online communities in the last years. In this poster, we study the language us- Age and diversity in Twitter local communities. We identify local communities in Twitter on a country-level. For each community, we examine: (1) the language diversity, (2) the language dominance and how it differs from local to global views, (3) demographic representativeness of tweets, and (4) the spatial distribution of different cultural groups within the community. We show fruitful insights about language usage on Twitter which can be exploited in language- based applications on top of tweets, e.g., lingual analysis and disaster management. In addition, we provide an interactive tool to explore the spatial distribution of cultural groups, which provides a low-effort and high-precision localization of different cultural groups.