# Do a set of people talk more than expected across multiple events?

I have information on whether two people at an event talked to each other. Two people talking is a binary event, meaning I have an $n$ by $n$ binary matrix indicating that the pairs talked or not (the diagonal is ignored). I have this information over 30 events, for the 2000 people who were present across all 30 events.

There are a set of 50 people who I have reason to suspect talk to each other more often than any random pair selected from the 2000, across all events, and would like to test whether this is the case.

I am quite ignorant of statistical hypothesis testing, but this seems like it would be exactly the place to apply it. Having done some reading, it sounds like I might want to use something like Fisher's exact test, though I can't quite work out how to do so (I could look at the total number of times talked for my target vs the total number for the population, but that ignores the pairwise relations). The current method I am using is to look at the average number of times my target pairs talk, across all events, divided by the average number of times a pair from the total population talks across all events. I have also looked at the distribution of number of contacts between pairs for my target set vs for the whole population.

• I'd have a look at network modularity concepts. Commented May 13, 2016 at 9:06