Keynote from SOCIAL NETWORKS AND HEALTH 2017 workshop

1. Social Networks & Health
Where we’ve been, where we’re going

2. Social Determinants of Health
“…social determinants of health refers to the complex, integrated, and overlapping
social structures and economic systems that include social and physical environments
and health services.” (CDC, 2010)
WHO Commission on Social Determinants of Health Conceptual Framework
Introduction

3. Social Determinants of Health
Social factors matter
RWJ, Health Affairs (2014) “The relative contributions of multiple determinants to health outcomes”
Introduction

4. Social Determinants of Health
Social effects hold promising multiplier effects:
Introduction

5. “Networks”
“Obesity”
Introduction
…researchers are using networks to study health more often

6. Introduction
1.History
2.Current State of the Field
3.Open Questions

7. Timeline

11. Social Science & Medicine, 2000

15. ASR
AJS
AJPH

20. Science
Social
Networks

22. PUBLIC HEALTH REPORTS, 1998

23. Mark S. Handcock, David R. Hunter,
Carter T. Butts, Steven M. Goodreau, and
Martina Morris (2003).
statnet: Software tools for the Statistical
Modeling of Network Data. URL
http://statnetproject.org

29. State of the field
Trends
English language Articles indexed in Web of Science Social
Science Citation Index on: ("health" or "well being" or
"medicine") and "network*").
There have been 18572 such papers since 2000.

30. State of the field
Big-Picture
Bibliographic Similarity Networks: 1-step neighborhood of a single paper

31. State of the field
Big-Picture
Bibliographic Similarity Networks: 2-step neighborhood of a single paper

32. State of the field
Big-Picture
Since the net is large…
Use a force-directed layout to display the full space & overlay clusters….

33. The example paper…

34. Modularity:
Top-Level: 0.798 @ 32 Clusters
2nd Level: 0.785 @ 150 Clusters

36. Rogers:

38. Valente: Various

39. Christakis & Fowler

40. Martina Morris: Concurrency

41. Heckathorn: RDS

42. House: Social Relations
& Health

43. Provan: Network
Effectiveness

44. Add Health

45. Ellison et al: Facebook

46. Edward Laumann

47. Pescosolido

51. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex Network dynamics
2. Network “life history”: relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community studies
2. Electronic Traces
3. National sample of network contexts
4. EMR

52. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR

53. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR Edge timing has profound effects on discrete transmission
dynamics

54. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR Edge timing has profound effects on discrete transmission
dynamics

55. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR But we’re just now starting to understand how timing interacts with network
structure & population turnover.
Required: New graph theoretic understanding of dynamic paths
Forward Reachable Sets; Authors: Benjamin Armbruster, Li Wang, Martina Morris
https://arxiv.org/abs/1605.03241

56. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
Current approaches cannot solve the numbers of clusters
problem unambiguously. This signals a miss-specified
question.

57. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
Need methods that can make sense of evolving group
structures. “Identity Arc” model is the right direction.

58. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
…likely a theory problem. “group” is the intersection of
cohesion and exclusion but we don’t distinguish those with
our methods.

59. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
003
(0)
012
(1)
102
021D
021U
021C
(2)
111D
111U
030T
030C
(3)
201
120D
120U
120C
(4)
210
(5)
300
(6)
Intransitive
Transitive
Mixed
Triads capture the essence of sociality: only with 3 do
you get supra-individual characteristics:
A friend of a friend is a friend…
My partner’s partner is my rival…
A periodic table of social elements

60. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
The macro structure of a network is thus summarized
by the distribution of triads.
Type Number of triads
---------------------------------------
1 - 003 21
---------------------------------------
2 - 012 26
3 - 102 11
4 - 021D 1
5 - 021U 5
6 - 021C 3
7 - 111D 2
8 - 111U 5
9 - 030T 3
10 - 030C 1
11 - 201 1
12 - 120D 1
13 - 120U 1
14 - 120C 1
15 - 210 1
16 - 300 1
---------------------------------------
Sum (2 - 16): 63
Combining elements gives you molecules…

61. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
We need to extend this work to continuous distributions
of triads.
We’re close: ERGM-style simulations build random
draws from the subset of possible graphs…but we have
no analytic solution.
Triad constraints  macro-structural constraints

62. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
Parent Parent
Child
Child
Child
Positional models are fundamentally under-
developed; yet hold the greatest promise of realizing
the potential of relational models to provide deep
insights into social organization and behavior.

63. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
Example: Social Exchange in developing contexts

64. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
Example: Social Exchange in developing contexts
Required: probably need to include content of
relation in the theory (at least valence, likely more)

65. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
Do we know how relations should change
over time?
 A 4 year old should not relate the same
way to parents as a 14 year old. But what
about old friends? Neighbors? Etc.? What
is the life-history of a relation?

66. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
The real controversy over the Framingham studies
turned on social mechanism: how do relations get
“inside”?
Current models are largely passive transmission or
stress-response; both seem much too simple.

67. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
Networks exist within an institutional
context; only way to know that is to
return to communities

68. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
Radio collar studies of people might be a bit
much (though talk to Kitts!), but we leave clear
digital traces…can we use that smartly?

69. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR
Ego-centric designs are the most tractable way to
collect network data.
To get sociometric insights from local networks,
extend k-steps.
A “network hyper-sample” is the solution

70. Open Problems
1. Methods:
1. Dynamic Diffusion
2. Community Detection
3. Triadic macro structure
2. Theory:
1. Roles & Multiplex
Network dynamics
2. Network “life history”:
relational evolution
3. Health Mechanisms:
3. Data:
1. Return to community
studies
2. Electronic Traces
3. National sample of
network contexts
4. EMR