Analysis of millions of tweets finds more precise use of social media which seems to contradict idea that Twitter users want to share everything with everyone

Twitter users are forming 'tribes', each with their own language, according to a scientific analysis of millions of tweets.

The research on Twitter word usage throws up a pattern of behaviour that seems to contradict the commonly held belief that users simply want to share everything with everyone.

In fact, the findings point to a more precise use of social media where users frequently include keywords in their tweets so that they engage more effectively with other members of their community or tribe. Just like our ancestors we try to join communities based on our political interests, ethnicity, work and hobbies.

The largest group found in the analysis was made up of African Americans using the words 'Nigga', 'poppin' and 'chillin'. That community was one of the more close-knit, sending around 90% of messages within the group. Members also tended to shorten the ends of their words, replacing 'ing' with 'in' or 'er' with 'a'. (see the table below for a fuller tribal breakdown)

Prof Vincent Jansen from the School of Biological Sciences at Royal Holloway, the institution which published the Word Usage Mirrors Community Structure in the Online Social Network Twitter report with Princeton University, explained:

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'.

To group these users into communities, the researchers turned to algorithms from physics and network science. The algorithms worked by looking at publicly sent messages between users.

In the graphic above, the top word given for each tribe is the most significant one in that community. Circles represent communities, with the area of the circle proportional to the number of users. The widths of the lines between circles represent the numbers of messages between or within community. The colours of the loops represent the proportion of messages that are within users from that group - from yellow 0% to red 100% .

Dr John Bryden, also at Royal Holloway, said that his team can now work out which tribes we belong to by analysing our tweets.

Given enough data, Bryden said that this can be done "with up to 80% accuracy". The research team hopes the data gathered from the project, which has been running since 2009, could offer a more accurate insight into the changing language used by different communities on Twitter. By learning these languages researchers hope new ways will emerge of engaging with Twitter tribes – rather simply using conventional Twitter features such as hashtags.

Download the data

• DATA: download the full spreadsheet

• SOURCE: Word Usage Mirrors Community Structure in the Online Social Network Twitter

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