Report
“Kenny Chen, Maggie Wu, Jessica Yu”
4/4/2021
This HTML attempts to organize all of the cohort summaries in one document. Please click on the different tabs to access information per cohort.
How to read the graphs:
Each node(circle) represents one faculty member
An arrow from node A pointing to node B means node A is mentioning or responding TO node b
Thickness of the arrow represents frequency. Thicker line = more connections.
Terminology:
Most Active Responder: refers to a faculty that comments on posts
Non-responders: refers to faculty that did not respond to other faculty’s posts
Most Popular OP: refers to a faculty that recieved the most responses on their posts
Total interactions: refers to total number of responses
Betweenness Centrality: each node(faculty) has a betweeness value. It represents how “influential” a node is over the flow of information in a network. A node with high betweeness centrality serves a “bridge” that links different nodes to each other.
Graph density: the ratio of the number of actual connections divided by the number of TOTAL POSSIBLE connections that could have occurred. Value ranges from 0 - 1. Higher density indicates a more well-connected and “sociable” network
Separate Cohorts
Cohort A
Cohort A: Week by Week
Cohort A: All 6 weeks
Cohort A: Overall Summaries Across 6 Weeks
| Overall | Values |
|---|---|
| Most Active Responder | F.76 |
| # of Non-Responders (Across all weeks) | 10 |
| Most Popular OP | F.125 |
| Total Interactions | 143 |
Cohort A: Betweenness Centrality:
The key takeaway is that there are only a few very “influential” faculty that are connected with many others.
Who is most influential? Top 5 faculty
| betweeness | |
|---|---|
| F.76 | 139.63951 |
| F.72 | 117.81838 |
| F.40 | 95.79879 |
| F.125 | 95.67387 |
| Kathy | 36.58907 |
Cohort B
Cohort B: Week by Week
Cohort B: All 6 weeks
Cohort B: Overall Summaries Across 6 Weeks
| Overall | Values |
|---|---|
| Most Active Responder | F.19 |
| # of Non-Responders (Across all weeks) | 8 |
| Most Popular OP | F.49 |
| Total Interactions | 83 |
Betweenness Centrality:
The key takeaway is that there are only a few very “influential” faculty that are connected with many others.
Who is most influential? Top 5 faculty
| betweeness | |
|---|---|
| F.49 | 101.10000 |
| F.70 | 84.40000 |
| F.67 | 46.66667 |
| F.144 | 45.33333 |
| F.28 | 41.00000 |
Cohort C
Cohort C: Week by Week
Cohort C: All 6 weeks
Cohort C: Overall Summaries Across 6 Weeks
| Overall | Values |
|---|---|
| Most Active Responder | F.46 |
| # of Non-Responders (Across all weeks) | 13 |
| Most Popular OP | F.27 |
| Total Interactions | 69 |
Betweenness Centrality:
Who is most influential? Top 5 faculty
| betweeness | |
|---|---|
| F.46 | 120.27857 |
| F.111 | 118.42857 |
| F.97 | 60.93333 |
| Megan | 60.63810 |
| F.122 | 28.63810 |
Cohort D
Cohort D: Week by Week
Cohort D: All 6 weeks
Cohort D: Overall Summaries Across 6 Weeks
| Overall | Values |
|---|---|
| Most Active Responder | F.44 |
| # of Non-Responders (Across all weeks) | 5 |
| Most Popular OP | F.05 |
| Total Interactions | 75 |
Betweenness Centrality:
Who is most influential? Top 5 faculty
| betweeness | |
|---|---|
| Kathy | 191.29048 |
| F.44 | 140.27500 |
| F.91 | 134.40476 |
| F.17 | 85.33333 |
| F.71 | 76.93571 |
Cohort E
Cohort E: Week by Week
Cohort E: All 6 weeks
Cohort E: Overall Summaries Across 6 Weeks
| Overall | Values |
|---|---|
| Most Active Responder | F.89 |
| # of Non-Responders (Across all weeks) | 4 |
| Most Popular OP | F.89 |
| Total Interactions | 77 |
Betweenness Centrality:
Who is most influential? Top 5 faculty
| betweeness | |
|---|---|
| F.89 | 116.45238 |
| F.24 | 111.11190 |
| F.35 | 95.67619 |
| F.33 | 77.50000 |
| F.98 | 65.34286 |
ALL COHORT SUMMARY
| Network | Density |
|---|---|
| A | 0.1761084 |
| E | 0.0885057 |
| D | 0.0806452 |
| B | 0.0739750 |
| C | 0.0695565 |
The higher the density, the more “well-connected” the network is. Network A has the highest density. However, overall, these networks are considered to be sparse.
