- Social network analysis uses social graph constructs to understand user behavior, recommendations, and influence. A social graph models relationships between connected social objects like people, interests, and actions. Characteristics of social graphs include strong and weak ties, centrality, degree, betweenness, and closeness. Social graphs can be used for recommendation engines, interest graphs, influence networks, sentiment analysis, and searching, scoring, and ranking. The use of social graphs in marketing is still nascent but will change how marketing is done in the future.

1. Social Network Analysis
Tuesday 6th December 2011
Using Social Graph constructs to understand user
behaviour, recommendations and influence
Marketing Analytics Conference
Alpesh Doshi, Fintricity

2. Social Graphs and their application
Agenda
• What is a Social Graph? Social Network
Analysis?
• Examples of Graphs
• Characteristics of Social Graphs?
• How can you use Graphs in the real world?
• The Future
• Summary

3. What is a Social Graph? Social Network Analysis
The definitions of these set the foundation of a network of social
objects a foundation for a new business approach
• Social Network Analysis (SNA) has its origins in
both social science and network theory and graph
theory
– Network Theory concerns itself with the formulation and solution
of problems that have a network structure – usually captured in a
graph
– Graph Theory provides a set of abstract concepts and methods
for the analysis of graphs
• Social Graph - The social graph is a term coined by scientists
working in the social areas of graph theory. It has been described as
"the global mapping of everybody and how they're related". The term
was popularized at the Facebook

4. What is a Social Graph?
A Social graph can be extremely complex and models relationships
between – either inside or outside the enteprise – OR both!

5. What is a Social Graph?
People, connected. Or further, ‘social objects’ connected.
• People are connected to each other directly and indirectly.
• The way they are connected varies. It could be through
work, friendship, common interests, etc.
• More importantly, there is something common between
the people that are connected. An implicity or explicity
connection
• Connections are spread across the social web – not only on
one site or application

6. What could you capture on a Social Graph?
Capturing more than just a relationship can make a graph more useful
Demographics Interests Actions
Age, Gender, Profile-Based, Contextual, Creating, Rating, Sending,
Geography, HHI, Demonstrated, Undeclared Sharing, Uploading,
Level of Education, Watching, and more
List of friends,
Friends of Friends
Recency and Frequency Interaction Sentiment and Exposure
How often and when How people interact with What people say, what
people express interests content and ads: Clicks, time they read, and when and
or actions spent, interactions, videos how they say and read it
completed

7. Some Characteristics of a graph
Multi-relational graphs are the foundation. These are graphs where
relationships are described in more than one way.
• Strong Ties and Weak Ties
• Centrality – Defining people who are highly connected
• Degree – How many people can this person reach directly?
• Betweenness – How likely is this person to be the most direct route
between two people in the network?
• Closeness – How fast can this person reach everyone in the network?
• EigenVector – How is this person connected to well connected people?

8. Where can you use Graphs?
How can you apply social graphs, and social network analysis for business
benefit? Some examples
• Recommendation Engines
• Interest Graphs
• Influence Networks
• Sentiment Analysis
• Searching, Scoring, Ranking

9. Where can you use Graphs? Recommendation
Recommendation engines are a natural fit for graphs.
• Recommendation engines need a ‘boost’ –
and can apply to many different types of
recommendation
• Recommend to read articles/content
• Recommend collaborators
• Recommend sites to post content
• Recommend people with similar interests

10. Where can you use Graphs? Recommendation
Recommendation engines are a natural fit for graphs.
• Interest Graphs (with Linked Data)
• Represents your interests
• Represents your interest in relation to others(social graph)
• Graphs can weaken/strengthen your interests dependent on behavious
• Recommend people with similar interests

11. Where can you use Graphs? Influence
Social Media is driving the use of influence – PR Agencies, enterprise have
to now can understand influence in detail
• First generation influence tools have shown that
there is a demand (e.g. peer index, klout)
• Useful only in content (e.g. Oil/Gas, Entertainment)
• A sub-set of a Social graph
• Influence drives
many things
recommendation,
opinion, purchasing

12. Where can you use Graphs? Searching, Scoring, Ranking
This can help identify and segment users by different categories together with the
social graph
• Searching
• Combining a social graph with linked data (semantics and ontologies)
• Graphs can be searched in different ways to discover relevant information
• Scoring
• Score individuals, content, objects to create patterns of associations
• Can be used for targeted advertising, content selection
• Ranking
• Ranking use, importance, connectedness etc
• Marketing uses included finding the most important customers
(together with modelling influence

13. Conclusions
Social Graphs will change the way marketing is done in the future. It will
become a fabric and key component in any marketing activity
• Social Graphs are not new!
• But their uses in marketing are nascent
• The implementation of a scalable graph database technology is
relatively new – therefore can better implement solutions around
this space.
• Application of social graphs to marketing allow more targeted,
integrated and cost effective solutions

14. Questions?
Alpesh Doshi, Fintricity
e: alpesh.doshi@fintricity.com
o: +44 870 020 1656, m: +44 7973 822820
Linkedin: www.linkedin.com/in/alpeshdoshi
Twitter: @alpeshdoshi
Content from this presentation taken from Giorgos Cheliotis under Creative Commons