  Internet and social media offer firms novel ways of managing their marketing
strategy and gain competitive advantage. The groups of users expressing
themselves on the Internet about a particular topic, product, or brand are
frequently called a virtual tribe or E-tribe. However, there are no automatic
tools for identifying and studying the characteristics of these virtual tribes.
Towards this aim, this paper presents Tribefinder, a system to reveal Twitter
users' tribal affiliations, by analyzing their tweets and language use. To show
the potential of this instrument, we provide an example considering three
specific tribal macro-categories: alternative realities, lifestyle, and
recreation. In addition, we discuss the different characteristics of each
identified tribe, in terms of use of language and social interaction metrics.
Tribefinder illustrates the importance of adopting a new lens for studying
virtual tribes, which is crucial for firms to properly design their marketing
strategy, and for scholars to extend prior marketing research.
