1. NETWORK ANALYSIS FOR CRIMINAL INVESTIGATIONS
Enrico M. Bucci
BIODIGITALVALLEY SRL – CEO
Social network analysis – introduction and some key issues

2. Back in time … I started as a biologist in the lab
With time, I became the scientific director of a large scale research infrastructure
Then I decided to start ANALYZING data, instead of amounting them …
Social network analysis – introduction and some key issues

3. Why I work on Networks?
Nothing makes sense in Biomedicine without Networks
Network analysis has several applications
I started analyzing networks of genes and proteins, ending up analyzing networks made of people and companies because I wanted to verify the source of fraudulent scientific data
In 2011, I started a collaboration with the General Attorney in Milan
Social network analysis – introduction and some key issues

4. Brief introduction to (criminal) social networks
Social network analysis – introduction and some key issues

5. Social network analysis – introduction and some key issues

6. We live in a 'social space'
"If we ever get to the point of charting a whole city or a whole nation, we would have … a picture of a vast solar system of intangible structures, powerfully influencing conduct, as gravitation does in space. Such an invisible structure underlies society and has its influence in determining the conduct of society as a whole."
Jacob L. Moreno
New York Times, April 13, 1933
Social network analysis – introduction and some key issues

7. We live in a connected world
“To speak of social life is to speak of the association between people – their associating in work and in play, in love and in war, to trade or to worship, to help or to hinder. It is in the social relations men establish that their interests find expression and their desires become realized.”
Peter M. Blau
Exchange and Power in Social Life, 1964
Social network analysis – introduction and some key issues

8. The network perspective
Two criminals in the same city.
Which one performs better (say, is more able to get rich):
A or B? A B
This depends on:
Cost effectiveness
Weapon possessions
Communication to victims
Flexibility
Strategy …
Social network analysis – introduction and some key issues

9. The network perspective
Two criminals in the same city.
Which one performs better (say, is more able to get rich):
A or B? A B
Note
Networks are one specific way of exploiting “criminal market inequalities”
AND … POSITION IN THE CRIMINAL NETWORK (e.g. Illegal Drug Exchange Net)
Social network analysis – introduction and some key issues

10. The network perspective
Single actor
properties determine behavior
Dyad
+ properties of partner and relation determine behavior
Network
+ network properties determine behavior
Temporal embeddedness
Network embeddedness
Social network analysis – introduction and some key issues

11. The network perspective (“structuralism”)
Relations between actors vs actor attributes
Individual characteristics are not the only thing that counts, because …
actors influence each other
Actors act on the basis of information that flows to them through relations between actors
Structuralism (vs individualism):
an emphasis on social capital
Explanation does not reside in actors, but in the connections between them
A different belief on social capital vs human capital
Social capital beats human capital (the real structuralists)
Social capital determines the extent to which your potential human capital can materialize (an interaction effect – see Burt’s Structural Holes book)
Human capital beats social capital (the real individualist)
 at least, consider how social capital can be of influence
Social network analysis – introduction and some key issues

12. A remark on social network analysis and internet research
The prevalence of Internet use shifts questions related to social capital from “neighborhood research” to “Internet Research”
Through Internet, it is possible to have connections (“ties”) with persons and institutions you could otherwise never reach
Social network data collection has become less difficult:
Through log-files of on-line behavior
Because of measurement of social networks through the Internet
Because of invasive methods (“spyware”) of data collection
Social network analysis – introduction and some key issues

13. Basic Quantitative Concepts
Social network analysis – introduction and some key issues

14. The basics: what is a network
Network A set of ties among a set of actors
(or “nodes”)
Actors persons, organizations, business-units,
countries …
Ties Any instance of ‘connection of interest’
between the actors
Social network analysis – introduction and some key issues

15. Example: kinds of relations among people
The content of ties matters
Some examples
Kinship
Mother
Has bloodband to
“Role based”
Boss of
Friend of
Communication, perception
Talks to
Knows (of)
Affection
Trusts
Protects, ...
Interaction
Gives advice to
Gets advice from
Has sex with
Affiliation
Belongs to same group/gang
Part of the same (business) unit
Social network analysis – introduction and some key issues

16. Example: relations among organizations
Criminal groups as actors
Buys from, sells to, outsources to
Has done business with
Owns shares of, is part of
Has a joint venture or alliance with, has sales agreements with
Has had quarrels with
Criminal members as actors
Has a personal friend in the group
Has a personnel tie to
Has a frequent communication with
Social network analysis – introduction and some key issues

17. Kinds of ties Directed vs undirected Undirected ties (lines)
A is in a joint venture with B
A is in the same market as B
Directed ties (arrows)
A owns B
A has bought something from B B A B A
Social network analysis – introduction and some key issues

18. Valued ties Ties can have a value attached Strength of relation
Information capacity of tie
Rates of traffic
Distance between nodes
Probabilities of passing information
Frequency of interaction … 1 4 8 2 2 5 1
Social network analysis – introduction and some key issues

19. Network representations: graph and matrix
A 1-mode, non-valued, directed network A B C D - 1 A B C D
A 1-mode, non-valued, undirected network A B C D - 9 4 1 3 A B 9 1 4 3 C D
Social network analysis – introduction and some key issues

20. AND another dimension: directed relations or undirected
Kinds of network data
AND another dimension: directed relations or undirected
Social network analysis – introduction and some key issues

21. Some network concepts Walk gets from A to X: A-C-A-D-F-X TrailB F X
Walk
gets from A to X:
A-C-A-D-F-X
Trail
Walk, but without repeating lines:
A-D-E-F-D-B-X
Path
Walk, but without repeating nodes:
A-D-E-F-X
Distance between A and X
Length of shortest path (“geodesic distance”)
Connected graph
For any couple of nodes there exists a path from one to the other
Social network analysis – introduction and some key issues

22. More network concepts CutpointsX
Cutpoints
Nodes which, if deleted, would disconnect the network.
For instance, node “D”.
Bridges
Ties which, if deleted, would disconnect the network.
For instance, the tie between A and D. E C F D A B
Social network analysis – introduction and some key issues

23. Individual Network Measures
Degree: Percentage of ties to the other actors an actor has (in directed graphs: InDegree and OutDegree)
Degree quality: Percentages of ties
to other actors the neighbors
of an actor have
Local density (=lack of structural holes): Extent to which neighbors of an actor are connected
Betweenness: extent to which pairs of actors depend on the focal actor to “communicate”
Closeness: the average minimal distance to other actors in the network A B C D - 1
Social network analysis – introduction and some key issues

24. Global Network Measures
Network size: Number of actors
Density: Percentage of ties present in the network
Centralization: Concentration of ties on limited number of actors in the network (e.g., degree variance. In general, any individual measure implies a global measure)
Transitivity: tendency of triads to be closed (how often is it the case that if i->j and j->k, then also i->k?)
Social network analysis – introduction and some key issues

25. Some typical questions in criminal network analysis
Social network analysis – introduction and some key issues

26. Networks = Y or Networks = X
In most social science applications, networks are considered as an independent variable.
For instance
Gang A performs better than B because gang A is embedded in a network with a lot of ties (a network of higher “density”) or
Person A performs better than B because person A has a lot of ties to other personsin the gang and person B doesn’t
(person A has a higher “degree”)
Social network analysis – introduction and some key issues

27. Example network: terrorists (source: Borgatti)
Social network analysis – introduction and some key issues

28. Exampe Networks: Gabbers
Social network analysis – introduction and some key issues

29. Example Network: YouTube users
Social network analysis – introduction and some key issues

30. Networks = Y or Networks = X
Sometimes: networks as the dependent variable
For instance:
How do the social networks of successful criminal groups differs from the social networks of others? (and why is that?)
And, on rare occasions: dynamic network theory
How do the alliance networks of criminal groups change over time?
Social network analysis – introduction and some key issues

31. Example Network Evolution: Financial Networks
Social network analysis – introduction and some key issues

32. Example Network Evolution: Telephone Traffic
Social network analysis – introduction and some key issues

33. Some final theoretical considerations
Social network analysis – introduction and some key issues

34. General issues in social network analysis
Think carefully about what defines an actor (often simple) and what defines a tie (often complicated)
Always think carefully about which property of the network it is, that drives the effect (closeness, betweenness, density, something else)
Think beforehand about how to tackle the data, and build in proxies in the data collection. Using (only) directly measured network data is risky.
When it comes to statistics, know that network data have their own typical problems that sometimes cannot (yet) be solved with standard SPSS-like packages.
There is still something to gain here for researchers: network research is still in its infancy.
We have just created a “weak tie”. If you have any questions related to social networks, ask!
General info on networks? Try
Social network analysis – introduction and some key issues

35. Hands On!
Social network analysis – introduction and some key issues