Sports games and other media events can induce very strong feelings of co-presence that can change communication patterns within large communities. Live tweeting reactions to media events provide high-resolution data with time-stamps to understand these behavioral dynamics. We employ a computational focus group method to identify 790,744 international Twitter users, and we track their behavior before and during the 2014 FIFA World Cup. We pick a set of Twitter users who speci fied the teams that they are supporting, such that we can identify communities of fans of the teams, as well as the entire community of World Cup fans. The structure, dynamics, and content of communication of these communities are analyzed to compare behavior outside and during the event and to examine behavioral responses across languages. Specifically, the temporal patterns of the tweeting volume, topics, retweeting, and mentioning behaviors are analyzed. We find similarities in the responses to media events, characteristic changes in activity patterns, and substantial differences in linguistic features. Our findings have implications for designing more resilient socio-technical systems during crises and developing better models of complex social behavior.