A team of data analysts from Oxford
University may have taken a note out of Facebook founder Mark Zuckerberg's book
when they developed a social network for a population of great tits birds.

The bird species Parus major is a common social woodland songbird in
Europe and Northern Africa, and is often observed by scientists interested in
analyzing animal behavior.  Mating pairs will usually raise between three
and four hatchlings per season and the older female siblings may stick around
to help with the new members of the family.  These birds do not migrate
and although pairs live in their own tree hollows, populations of great tits
will take up residence throughout a forest area.  The social structures of
the birds can be monitored by observing how far they travel from their own tree

Parent great tit feeding hatchling.  Image courtesy madmcmojo.Parent great tit feeding hatchling. Image courtesy madmcmojo.

 In a scientifically monitored forest called
Wytham Woods, electronic recorders track when individual birds visit particular
feeding stations set up throughout the forest.  That information reveals
which birds live in which areas, and along with the family ancestry of the
birds and personal observations of the researchers, is used to interpret the
relationships between the birds.  However, the amount of electronic
recordings can become overwhelming and meaningless without a way of analyzing

To solve this problem of too much random
information, a group from the Pattern Analysis and Machine Learning Research
Group at Oxford University developed a computer program to turn two years worth
of electronic data points into a summary of meaningful facts.  Rather than a list of separate occurrences
"Bird A visits feeding station 1, 10am; Bird B visits feeding station 1,
10:05am; Bird C visits feeding station 2, 11am" the computer program summarizes
the information to interpret that Bird A and Bird B interact often, whereas
Bird C lives elsewhere in the forest and does not interact with the other two
birds.  All three birds are part of the
same population, but they are not in the same social group.  Conceptually, the program is similar to how
social networking sites can be used to differentiate between people who are
members of the site and people who are close friends by tracking how often
those individuals interact online.

Greater understanding of the birds' social
groups is valuable for researchers interested in deciphering the role of
genetics in social interaction as well as the behavioral differences between
familiar and unfamiliar birds.  The future plan for the new computer program is to adapt the basic principles for other research opportunities.

 Sources: University of Oxford and BBC Nature Wildlife