MIT 2374 Social Networking Wednesday, January 23 , 2012
A input channel – Device Output channel B
A Input Channel Device Output Channel
• Mathematical theory of Communication: There is a sender and a receiver and
every time you send a message you are throwing that message as a signal and this
message becomes encoded and decoded. Everything is being translated into
o There’s always the possibility of noise or entropy occurring that interrupts
• When we think of our social networking environment online, we are given limited
choice even though we feel that we have an abundance of choice.
• The Tour: predictive human behavior where you visit certain websites in a
• Human beings according to “technopolists” believed that human beings are
nothing but programs
• We cannot convey emotions through technology.
• We might share the same language but we differ slightly
Social Network Entropy
• The larger the network the higher the likelihood of having network entropy. When
the network is smaller, the messages become more coherent. As soon as you
introduce more people, there will be a higher chance of miscommunication
o Ex. Desert Island (0), Family (3), Workplace (375), The social web (
o The larger the network the higher the chance of social entropy
• Can represent individual or group
• Types: normal, peripheral, isolate, surrogate
o Peripheral nodes ex. A study group ordering a pizza. For a brief period of
the person who delivers the pizza is a peripheral node in the network.
o Surrogate nodes ex. A lawyer will represent a person who has committed a
• Tells us something about the social network actor
• Information about actor’s position in the network Affinities
• Is what connects us to each other
• Concerned with the flow of information/communication
• Quantitative Understanding
• Qualitative Understanding
• Why measure affinities? It determines behavior of a social network, strengths and
• When we measure affinities we are looking for the strength of ties, number of ties
(degrees), density of information and network, Flow of information (speed and
intensity), and communication clusters.
o Strength of ties: We will use weaker ties such as therapists or doctors
when there is potential for our shared information to hurt our relationships.
If you have many connections it does not mean that you have close
connections with people.
o Flow of information
Speed: the more steps communication has to go through, the
slower it will take to reach the designated recipient.
Measuring the Network
• Gestalt Theory: says that the whole is worth more than the sum of its parts. We
have to understand that just speaking of nodes and affinity will not give us more
perspective in what goes on in our networks
• Network reach: how far a network can reach as every network has its boundaries.
• Network efficiency (speed, information loss, exonetwork connections): Some
networks are more efficient than others
Closed V. Open Networks
• Pros and Cons of the Closed Network
• Pros and Cons of the Open Network
• Degrees of inclusivity and exclusivity based on RULES
Sociometry Key Terms
• Sociogram: a sociogram is a visual representation of a social network in your own
mind. Performing an abstraction for the purpose of measurement
• Social Field Theory/Field Theory
• Environment/Ecology: all social networks occur in an environment
• Groups: always form within any social networks if it’s long enough
• De/re territorialzation: coined by Gilles Deleuze and Felix Guattari, is a way of
mapping environments through many different methods
o Ex. London can be measured by zones, small areas etc Sources of Data
• Can analyze a network from an egocentric, systematic, diffusion/viral perspective.
• Egocentric: problem with this is that no two facebook accounts will look alike.
The only thing that is the same is the gridded architecture of Facebook. For the
most part our experiences and connections is what makes studying social
networks so hard. We can never get to the full picture or the Gestalt through this