How
Yahoo Research Labs Studies Culture as a Formal Computational Concept
The
ultimate goal: a truly computational understanding of human society, say
Yahoo’s computational anthropologists.
The study of online social networks has
revolutionized the way social scientists understand human interaction on a
grand scale. It is based on the assumption that the fundamental unit of
interaction is the social tie that exists between two individuals. This tie can
be a message that one person has sent to another, that one person follows
another, that one person “likes” another and so on.
These social ties are the atoms of social
network structure. And much of the research on social networks has focused on
how these atoms join together to create complex networks of interaction.
Much less thought has been given to the atoms
themselves, whether they fall into categories themselves, whether different
atoms have different social properties and how combining atoms of different
types might be indicative of entirely different relationships.
Today, Luca Maria Aiello at Yahoo Labs in
Barcelona, Spain, and a couple of pals, change that. They tease apart the
nature of the links that form on social networks and say these atoms fall into
three different categories. They also show how to extract this information
automatically and then characterize the relationships according to the
combination of atoms that exist between individuals. Their ultimate goal: to
turn anthropology into a full-blooded subdiscipline of computer science.
Aiello and co used two data sets from a pair
of large social networks. The first consists of over 1 million messages sent
between 500,000 pairs of users of the aNobii social network, which people use
to talk about books they have read. The second is a set of 100,000 anonymized
user pairs who commented on each other’s photos on Flickr, sending around 2
million messages in total.
The team analyzes these messages based on the
type of information they convey, which they divide into three groups. The first
type of information is related to social status; messages displaying
appreciation or announcing the creation of the social tie such as a follow or
like. For example, a user might say a photograph is “an excellent shot” or say
they’ve followed somebody or acknowledged attention they’ve got by thanking
them for visiting a site.
The second category of information involves
social support of some kind. The main purpose of a message that falls into this
category is to greet or welcome someone to a website, to explicitly express
affection or to convey wishes, jokes and laughter.
The final category of information is an
exchange of knowledge. Messages that fall into this category share information
and personal experience, or ask for opinions and suggestions, or display knowledge
of a particular field.
Aiello and co then develop an algorithm that
automatically categorizes the messages sent between individuals according to
the content they contain and their similarity to messages of the same type.
Finally, they evaluate the results of the
algorithm by asking human editors to assess a sample of 1000 randomly selected
messages from each website and label them according to the three categories.
They then compared the human choices with the algorithms and found good
agreement.
The results of this analysis allow them to
work out how often people use the different modes of communication and also how
they transition from one to another during a conversation.
They find that in aNobii, the most frequent
interactions involve status giving where the archetypal message is “nice
library”, referring to a user’s collection of books.
By contrast, Flickr users communicate in a
different way. “In Flickr the proportion is very balanced instead, with no
domain being predominant on average,” say Aiello and co.
More interesting is the way that social ties
evolve over time. Aiello and co say that status exchange is particularly common
in short conversations and at the beginning of longer ones. However, the
conversations rapidly evolve into a mix of knowledge exchanges and social
support. “It thus appears that status exchange serves to set the foundation for
the future relationship, feeding to the interactional background after the
tie-formation stage,” say Aiello and co.
That’s a fascinating study that provides a new
way of looking at social ties as strings of interactions. In a way, it changes
the atomic theory of social ties into a kind of string theory.
Aiello and co clearly think this should lead
to plenty of new insights and they are optimistic about the future. “The
ultimate goal of such analysis is the unpacking of “culture” as a formal,
computational concept,” they say. And they think of the patterns of strings of
interaction as a kind of grammar of society. “We hope our work provides yet
another step towards a truly computational understanding of human societies.”
That’s an ambitious goal– a truly
computational understanding of human society. Both fantastic and a little
frightening the same time.
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