A workshop about Social Network Analysis and Condor software developed by Peter Gloor, MIT. The workshop aimed to provide an introduction for design students into SNA and this free software tool for SNA.

1. CONDOR 3 MIT SOFTWARE
/ANALYSIS AND VISUALIZATION OF SOCIAL
NETWORKS/
MAYA NINOVA, PhD
maya.ninova@gmail.com

2. 1. Brief history of Social Network Analysis
2. Basic vocabulary of Social Network Analysis
3. Professional Associations
4. References
5. Four stages of inquiry with Condor MIT
6. Case studies examples
7. Practice
KEY TOPICS
1. Brief history of Social Network Analysis
2. Basic vocabulary of Social Network Analysis
3. Professional Associations
4. References
5. Four stages of inquiry with Condor MIT
6. Case studies examples
7. Practice

3. BRIEF HISTORY OF SOCIAL NETWORK ANALYSIS

4. ANTHROPOLOGY
SOCIOLOGY
MATHEMATICS
COMMUNICATIONS
PHYSICS
COMPUTER SCIENCE
….
BRIEF HISTORY OF SOCIAL NETWORK ANALYSIS
ANTHROPOLOGY
SOCIOLOGY
MATHEMATICS
COMMUNICATIONS
PHYSICS
COMPUTER SCIENCE
….

5. BASIC VOCABULARY
Node/Actor
Vertex
Link
Edge
Tie
Arc

6. NODE/ACTOR

7. LINK

8. LINKS: DIRECTED Vs UNDIRECTED
Undirected
Directed
NOTE: Condor uses only directed links

9. RECIPROCAL LINKS

10. UNRECIPROCATED LINKS

11. BASIC VOCABULARY
NETWORK MEASURES
Degree
Density
Bridge
Centrality
Betweenness
TRIADS
NETWORK MEASURES
Degree
Density
Bridge
Centrality
Betweenness
TRIADS

12. DEGREE
The count of the number of ties to other actors in the network
Indegree /a count of the number of ties directed to the node
(popularity) /
Outdegree / the number of ties that the node directs to others/

13. 6 actual/ 6 possible = 1
The density of the network o the global density is the proportion of links
of a network in relation to the total possible links (dense versus sparse
networks)
DENSITY
A network with only a few edges, is a sparse network
2 actual/ 6 possible = .33

14.  An edge is said to be a bridge if deleting it would cause its endpoints
to lie in different components of a network
BRIDGE
Note: a network with 6 bridges (highlighted in red)

15. This measure gives a rough indication of the social power of a node
based on how well they “connect” the network.
“Betweenness”and “Degree”are all measures of centrality.
CENTRALITY

16. BETWEENNESS
 The extent to which a node lies between other nodes in the network.
Note: red= 0, blue = max

17. TRIADS
A group of three.
There are 16 possible combinations

18. NETWORK ANALYSIS

19. PROFESSIONAL ASSOCIATIONS

21. Peter Gloor – developer of Condor MIT Software
REFERENCES

22.  Basic introduction to Social Networks
REFERENCES

23. REFERENCES
Basic introduction to Social Networks (academic reading)

24. Basic introduction to Social network Analysis /Handbooks/
REFERENCES

25. Theory review
REFERENCES

26. REFERENCES
Popular reading

27. REFERENCES
Popular reading

28. COOLHUNTING
Find the big ideas from Wikipedia,
Facebook, Twitter, Blogs
Discover the innovators and influencers
USING CONDOR MIT
SOFTWARE FOR
COOLHUNTING
Find the big ideas from Wikipedia,
Facebook, Twitter, Blogs
Discover the innovators and influencers
VIRTUAL MIRRORING
Organizational health
Email/own social network analysis
Improve innovation process

29. COOLHUNTING PRINCIPLES / PETER GLOOR/
Distinguish between three information spheres:
 Crowd - mostly Twitter, and online comments
Experts – mostly Blogs
Swarm – mostly Wikipedia, Facebook and Forums, although it could
be found on Twitter too
Crowd look for ¨hot¨ (could be influenced by publicity)
Swarm look for ¨cool¨ (usually within the product)
 The more emotional the crowd, the better
 The more cohesive the swarm, the better
Distinguish between three information spheres:
 Crowd - mostly Twitter, and online comments
Experts – mostly Blogs
Swarm – mostly Wikipedia, Facebook and Forums, although it could
be found on Twitter too
Crowd look for ¨hot¨ (could be influenced by publicity)
Swarm look for ¨cool¨ (usually within the product)
 The more emotional the crowd, the better
 The more cohesive the swarm, the better

30. Coolhunting means finding trends by finding the trendsetters (cool people,
influentials) and measuring how, and how fast they influence their ¨followers¨
The key measure is betweenness in the social network
 Goes from o to 1, it controls information flow and is a proxy for influence
Sentiment analysis is based on a bag-of-words
Positive words ¨good¨, ¨great¨, ¨wonderful¨, etc
Negative words ¨bad¨, ¨sad¨, ¨horrible¨, etc
 Bag of words is customized by machine learning, large text collections, tweets
have been manually categorized to generate topic-specific bag-of-words
COOLHUNTING PRINCIPLES / PETER GLOOR/
Coolhunting means finding trends by finding the trendsetters (cool people,
influentials) and measuring how, and how fast they influence their ¨followers¨
The key measure is betweenness in the social network
 Goes from o to 1, it controls information flow and is a proxy for influence
Sentiment analysis is based on a bag-of-words
Positive words ¨good¨, ¨great¨, ¨wonderful¨, etc
Negative words ¨bad¨, ¨sad¨, ¨horrible¨, etc
 Bag of words is customized by machine learning, large text collections, tweets
have been manually categorized to generate topic-specific bag-of-words

31. Crowd– Twitter
 To tell others “how great I am”
Twitter is not useful for end user information in Germany, Twitter is useful in
US/UK/Spain, is highly representative in South America, Philippines, Malaysia
On weekdays, mostly retweets (high volume- low content), on weekends original tweets
(high content- low volume)
Content goes away very quickly
People are not complaining about long-term product problems on Twitter, only about
things that impact them “right now” (car broken, trying to get help, etc.)
Experts – Blogs
Sharing complex ideas – Blogs (opinion of experts)
Mostly journalists
 Has “stickyness” , will be found by search engines for a long time
 Boost product names, shapes longtime opinions
COOLHUNTING PRINCIPLES /PETER GLOOR/
Crowd– Twitter
 To tell others “how great I am”
Twitter is not useful for end user information in Germany, Twitter is useful in
US/UK/Spain, is highly representative in South America, Philippines, Malaysia
On weekdays, mostly retweets (high volume- low content), on weekends original tweets
(high content- low volume)
Content goes away very quickly
People are not complaining about long-term product problems on Twitter, only about
things that impact them “right now” (car broken, trying to get help, etc.)
Experts – Blogs
Sharing complex ideas – Blogs (opinion of experts)
Mostly journalists
 Has “stickyness” , will be found by search engines for a long time
 Boost product names, shapes longtime opinions

32. COOLHUNTING PRINCIPLES
Swarm– Facebook
Staying in touch with friends
 To connect with swarm – people passionate about same things
 Content is hidden, mostly not indexed by Google, Facebook search “
personalizes” results, hiding them
Hard to collect (Facebook gives no “ easy access”, no API)
• API is a set of functions/keys that allow the access of data of an operating system, application or
other service
Swarm– Wikipedia
 Open knowledge– Wikipedia (public opinion)
Written by “leftist liberals” and (paid?!) marketing staff (against the rules)
/ongoing debate/
Swarm– Facebook
Staying in touch with friends
 To connect with swarm – people passionate about same things
 Content is hidden, mostly not indexed by Google, Facebook search “
personalizes” results, hiding them
Hard to collect (Facebook gives no “ easy access”, no API)
• API is a set of functions/keys that allow the access of data of an operating system, application or
other service
Swarm– Wikipedia
 Open knowledge– Wikipedia (public opinion)
Written by “leftist liberals” and (paid?!) marketing staff (against the rules)
/ongoing debate/

33. COOLFARMING - RECOMMENDATIONS (PETER GLOOR)
 Create engaged communities – find role models
Maintain an active blog community (not just journals)
Curate the Wikipedia pages through the community (do not write your own
page)
Identify and recruit influential lead users to build community
Continuosly track progress (Twitter/Facebook/Blogs/Wikipedia as a
“microscope”)
 Create engaged communities – find role models
Maintain an active blog community (not just journals)
Curate the Wikipedia pages through the community (do not write your own
page)
Identify and recruit influential lead users to build community
Continuosly track progress (Twitter/Facebook/Blogs/Wikipedia as a
“microscope”)
BUILD THE SWARM

34. CONTACT
Collaborative Innovation Networks (COIN)
http://www.ickn.org/ckntools.html
Peter Gloor – Chief Creative Officer of Galaxyadvisors/developer of Condor
software for social network analysis and visualization
http://cci.mit.edu/pgloor/about.html
CONTACT
Collaborative Innovation Networks (COIN)
http://www.ickn.org/ckntools.html
Peter Gloor – Chief Creative Officer of Galaxyadvisors/developer of Condor
software for social network analysis and visualization
http://cci.mit.edu/pgloor/about.html

35. HOW DOES CONDOR WORKS?
Condor enables a user to explore their area of interest
through a series of user completed forms across four
broad stages of inquiry: data harvesting, processing,
visualizing and exporting.
There are two primary programs at work:
1. The Condor program is the foreground that the user
uses to select menus items and completes forms for
data harvesting, filtering, visualizing and exporting.
1. The MySQL program is in the background as is used for
the data storage.
HOW DOES CONDOR WORKS?
Condor enables a user to explore their area of interest
through a series of user completed forms across four
broad stages of inquiry: data harvesting, processing,
visualizing and exporting.
There are two primary programs at work:
1. The Condor program is the foreground that the user
uses to select menus items and completes forms for
data harvesting, filtering, visualizing and exporting.
1. The MySQL program is in the background as is used for
the data storage.

36. Step 1: Data harvesting
/FETCH/
Sereval options …
Search by:
• keyword
• phrase
• URLs
•Location
• user IDs
Step 1: Data harvesting
/FETCH/
Sereval options …
Search by:
• keyword
• phrase
• URLs
•Location
• user IDs

37. https://www.youtube.com/watch?v=QqzD1puxbTM&spfreload=10
(Video of Peter Gloor harvesting his own network on Facebook, done before
the permission changes by Facebook)

38. Step 2: Data processing
/PROCESS DATASET/
Several criteria for processing…
Calculate:
• Betweenness
• Sentiment
• Influence
• Location
Step 2: Data processing
/PROCESS DATASET/
Several criteria for processing…
Calculate:
• Betweenness
• Sentiment
• Influence
• Location

39. Step 3: Data visualization
/VIEW/
Different options for
visualization…
Create:
• Static or dynamic view
• Sentiment and activity over
time
• Create word cloud to perform
content analysis
Step 3: Data visualization
/VIEW/
Different options for
visualization…
Create:
• Static or dynamic view
• Sentiment and activity over
time
• Create word cloud to perform
content analysis

40. Analyse the actual content behind
the words from the word cloud

41. Step 4: (optional) Export data
/EXPORT/
Several options for exproting the
data to work with…
Statistical software:
•SPSS; Excel
Social Networks:
•UCINET
Step 4: (optional) Export data
/EXPORT/
Several options for exproting the
data to work with…
Statistical software:
•SPSS; Excel
Social Networks:
•UCINET

42. PRACTICE:
Explore the program using different keywords and analyse the content
following the steps /data harvesting, processing, visualization and analysis of
content from the word cloud, export data and work in Excel with the data
(optional)
•Wikipedia
•Web
•Twitter, etc.
Explore your own network via your E-mail account
PRACTICE:
Explore the program using different keywords and analyse the content
following the steps /data harvesting, processing, visualization and analysis of
content from the word cloud, export data and work in Excel with the data
(optional)
•Wikipedia
•Web
•Twitter, etc.
Explore your own network via your E-mail account