In analysing usage of social media sites such as Twitter one of the categories often used is male/female.  On this scale there are some sites with a preponderance of males (Slashdot, Google+ and Reddit), others where they are roughly equal (Facebook and Twitter) and maybe some where females are in the majority (possibly MySpace and Bebo).

This raises the question, how do you count the numbers of males and females on a social media site?  Take Twitter as an example.  There is nothing about gender on a user’s profile and so the analyst can only deduce the gender from the name or information in the profile.  It’s often said (e.g. http://www.sysomos.com/insidetwitter/mostactiveusers/#males-vs-female) that a user’s gender can be found by looking up the first name in lists and databases.   A colleague decided to try this approach by getting the genders of the users he is currently following (his followees) on Twitter.  Hardly a representative or large sample but a simple starting point.

The results  were interesting:

 

Genders of followees on Twitter

 

In this case there were considerably more more males than females, but the surprise was the number of users who were neither. In some cases it wasn’t possible to identify gender even with the help of those lists of names.  Of course some names such as Lesley are inherently ambiguous.  Others are not on the lists, being unusual or nicknames.  He could identify gender for some users from their profile photos but did not included these in the male/female numbers as h was trying to replicate what an automated system based upon text analysis might do.

However these exceptions were only a small proportion of the Other category (some 10%).   The rest of the Other users were organisations.  One’s first impression of Twitter is that it is for people to communicate their interests to other people and this may well have been what happened in its early days.  But the results here, which are probably not atypical, show that the situation has changed as commercial and other organisations establish a presence.  A lot of questions follow from this.  What kinds of organisations have a Twitter presence?  What use do they make of it?  What interest do they attract? Does their activity vary over time?   From that perspective the ratio of males to females seems of minor importance.  It’s more a question of people versus organisations now.

 

 

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