Researchers have found the emerging “tribes” – communities – on the social networking sites such as Twitter. These communities have common characters, occupation or interest and have their own particular languages.
EPJ Data Science
Researchers, in this study, worked on the publicly available messages on Twitter and found the language use of the communities on the social networking site. They found the particular pattern of language use along with the frequencies of the much used words.
“This means that by looking at the language someone uses, it is possible to predict which community he or she is likely to belong to, with up to 80% accuracy,” said Dr John Bryden from the School of Biological Sciences at Royal Holloway. “We searched for unusual words that are used a lot by one community, but relatively infrequently by the others. For example, one community often mentioned Justin Bieber, while another talked about President Obama.”
Professor Vincent Jansen from Royal Holloway added, “Interestingly, just as people have varying regional accents, we also found that communities would misspell words in different ways. The Justin Bieber fans have a habit of ending words in ‘ee’, as in ‘pleasee’, while school teachers tend to use long words.”
“This indicates a relationship between human language and social networks, and suggests that the study of online communication offers vast potential for understanding the fabric of human society.” Researchers wrote, “Our approach can be used for enriching community detection with word analysis, which provides the ability to automate the classification of communities in social networks and identify emerging social groups.”
Bryden, J., Funk, S., & Jansen, V. (2013). Word usage mirrors community structure in the online social network Twitter EPJ Data Science, 2 (1) DOI: 10.1140/epjds15