Upload
jovita
View
22
Download
0
Embed Size (px)
DESCRIPTION
Using Social Network Analysis to Evaluate Communities of Practice: A Methodological Journey. Kathryn Everest Director, Strategy Consulting Jive Software. What is Social Network Analysis (SNA)?. A set of methods and metrics that shows how entities interact … - PowerPoint PPT Presentation
Citation preview
Using Social Network Analysis to Evaluate Communities of Practice:
A Methodological Journey
Kathryn EverestDirector, Strategy Consulting
Jive Software
What is Social Network Analysis (SNA)?
• A set of methods and metrics that shows how entities interact …– the current patterns of communication, information-sharing, decision-making and innovation within
a particular organization or group – Focuses on three elements:
• A group of entities (in this case researchers and institutions) and the roles they play• The relationship between the entities• And attributes might be present that are creating a bias in the relationship of the entities
– When applied to organizations, it can be referred to as ONA – Organizational Network Analysis
• The outcome of an SNA…– helps us to see where collaboration is breaking down, where talent and expertise could be better
leveraged, where information is getting bogged down or where opportunities for innovation are being lost
• SNA data…– gives us the picture we need to create a set of remedial actions for individuals, influencers and
stakeholder to improve productivity, efficiency and innovation
The entities, the relationship between entities, and the attributes of the entities are depicted in SNA maps
Social Entities People (Researchers, Health
Professionals, Experts)
Resources (Collaborative spaces, Information repositories)
Relationship Information sharing Advice Collaboration Trust Awareness Access
Attributes Contributing factors such as
location, tenure, specialty, language, funding, culture
SNA also provides insights about roles within the network, as well as metrics that allow us to measure where we are and
where we want to be
Network MeasuresDensity = 6%Cohesion = 4Centrality = 6
Central People DPa(34), CR(29), BB(20), MDo(19),DPr(17)
Roles Central roles – those who
many people go to (or could be bottleneck)
Peripheral people - goes to others but no-one goes to them
Boundary Spanners – connects different groups
Brokers – connects many people
Isolate - not connected
Density --- Robustness of network (group measure) Number of connections that exist in the group out of 100% possible in that network General level of linkage. More points connected means quicker and more accurate information flow
Cohesion --- Ease with which a network can connect Distance is the shortest path between two people Aggregate measure at network level reflects average distance between people
Centrality --- Identifies influential people (individual measure) Number of direct connections that individuals have with others in group Individuals who have more ties to others may be in more advantaged positions; they may have access to more of the information or knowledge in the network
Why do an SNA?
Awareness Network - Density = 4.83% 861 Ties
1: Geo 1 (Red)2: Geo 2 (Pink)3: Geo 3 (Black)4: Geo 4 (Dark Blue)5: Geo 5 (Grey)
1: Area 1 (Circle) 2: Area 2 (Square)3: Area 3 (Up Triangle)4: Area 4 (Plus)5: Area 5 (Down Triangle)
Develop “before and after” measurements (e.g. What impact has your community had on the network?)
The SNA can provide understand the potential impact losing core researchers to a network
Research collaboration with core researchers
Research collaboration without core researchers
Sample hypothesis: Without core XX researchers, collaboration supporting XXX research would be severely affected
Identify issues and opportunities in the network
N Ind/Pri Hosp Rehab Col/Uni Other
Individual/Private 14 24% 8% 31% 16% 20%
Hospitals 9 6% 17% 19% 15% 6%
Rehab Facility 10 29% 20% 27% 29% 36%
College/University 8 11% 14% 16% 20% 14%
Other 7 22% 6% 36% 30% 43%Note – Removed Gov/Agency and K-12
Identify Brokers
Liaison
GatekeeperRepresentative
Consultant
Consultant
Name Name Name Name Name Name
Representative
Name Name Name Name Name Name Name Name Name Name Name
Liaison
Name Name Name Name Name Name
Gatekeeper
Name Name Name Name Name Name Name Name Name
Out In
Mean 6.425 6.425
Std Dev. 4.53 3.33
Min 0 1
Max 21 17
Measure and identify issues in individual networks
Understand the makeup of your network
Out-degree
In-d
egre
e
Framework Source: Steve Borgatti
Authority
Low Involvement
High Involvement
Apprentice
Notes: Removed all nodes with a 0 out-degreeHigher in-degree and out-degree than the mean
13
1016
11
Provide a perspective of a person and their network
In-degree
Out-degree Mean
Aware 11
SME 10
Betweenness 51.4
Comm-Daily 1.2
Comm-Weekly + 1.8
Comm-Weekly 3.3
Comm-Monthly 6.5
XX XXX Other H *
% % %
Centrality
Network Composition by Location
Description: Awareness: Awareness describes a person is aware of the knowledge and skills of others in the network. In-degree reflects the number of people who indicated that they believe they are aware of your knowledge and skills. Out-degree reflects the number of people you selected as being aware of their knowledge and skills. The mean represents the mean or median number of the network.
SME: SME describes whether a person will call upon another person when looking for expertise related to TOC topics. In-degree reflects the number of people who indicated that they would call upon you for expertise. Out-degree reflects the number of people you selected you would call upon. The mean represents the mean or median number of the network.
Betweenness – Betweenness describes how often you fall between two people in the network. The Mean of the network is 51.4 with a maximum value of 533.
Comm: Comm (Communications) relates to how many people communicate with each other on a daily, weekly+ (once or more per week), weekly (once a week or less), or monthly (once a month or less). In-degree reflects the number of people who indicated they communicate with you, and out-degree reflects the people you selected. The mean represents the mean or median number of the network.
Network Composition by Location: This is analysis looks at location of the people in your network. XX represents the percentage of people in your network who are located in XX, XXX represents the percentage who are located in XXX, and Other represents locations other than XX and XXX. H is the value which represents the heterogeneity of your network. H is a number between 0 and 1 with 1 representing a maximum value. The average result was .46.
Example
In-degree
Out-degree Mean
Aware 12 11 11
SME 8 11 10
Betweenness 25 54.4
Comm-Daily 2 2 1.2
Comm-Weekly + 0 1 1.8
Comm-Weekly 2 4 3.3
Comm-Monthly 8 1 6.5
XX XXX Other H *
50% 31% 19% .617
Centrality
Network Composition by Location
How do you do an SNA?
1. Gather attribute/demographic and relationship data– Getting the data from public sources / mining data– Survey (bounded and unbounded)
2. Analyze the data– Pick a tool (I use UCINet, but there are others including NodeXL,
Pajek, InFlow just to name a few)
And there is a lot to both
I use Optimice – http://www.onasurveys.com
To use it, you need to register for an Optimice account
There is no charge to create and account, develop and administer a survey
A “free” account however only allows you to download a subset of the data
An account is $75USD per month or $599 per year
You only need to have a valid account when you download data
You can conduct as many surveys as you want, with as many people as you want
You can allow your account to lapse and your data is maintained
They will expunge data on request
1. Log in (after you create your account)
2. Create a new survey
19
3. About the survey
3. Cont’d
21
Create an introductory email to attach the survey (should reference another communication which puts the project in context)
Dear {Name}
• What is this project?• Why are you asking these questions?• What will happen to the results?• Will people see how I answered?• When will I hear more?
Signed by,
To answer the survey please click on this link: {URL}
22
4. About Respondents – (traditional survey and attribute questions)
Sun Life Financial SMCS - IBM/SLF Confidential | Apr 22, 2023
23
Respondent List
Sun Life Financial SMCS - IBM/SLF Confidential | Apr 22, 2023
24
Creating the list of participants
Notes:
First two columns MUST BE: “Name” and “Email”
Create as a CSV file to upload to the survey tool
No spaces in the headings
25
5. About Relationship (Network Questions) – Note: the more names you have, the fewer questions you should
consider. Make your questions count!!
Checkbox
Choice Across and Down
Matrix Question
Testing the survey
Monitor / Test
30
Tracking Progress – Two ways
31
When the data is collected, download the data
Analyze Data
What can you do? Way too much to cover, so be focused about what you need