kaiserfamfound, Twitter, 9/14/2021 5:42:45 PM, 262058


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kaiserfamfound_2021-09-14_10-40-01.xlsx
kaiserfamfound_2021-09-14_10-40-01.xlsx
From:
NodeXLExcelAutomator
Uploaded on:
September 14, 2021
Short Description:
kaiserfamfound via NodeXL https://bit.ly/2VEBds8
@caffrey_usa
@iamonlycaffrey
@caffrey1_usa
@marykecaffrey1
@kaiserfamfound
@amermedicalassn
@activeretirees

Top hashtags:
#jeanquan
#kaiser
#berkeleyca
#phan
#director
#lifelongover60
#60yrs
#medical
#usa
#over60lifelong

Description:
Description
The graph represents a network of 7 Twitter users whose tweets in the requested range contained "kaiserfamfound", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 14 September 2021 at 17:40 UTC.

The requested start date was Tuesday, 14 September 2021 at 00:01 UTC and the maximum number of days (going backward) was 14.

The maximum number of tweets collected was 7,500.

The tweets in the network were tweeted over the 0-minute period from Tuesday, 07 September 2021 at 02:55 UTC to Tuesday, 07 September 2021 at 02:55 UTC.

Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".

The graph is directed.

The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.


Author Description


Overall Graph Metrics
Vertices : 7
Unique Edges : 3
Edges With Duplicates : 51
Total Edges : 54
Number of Edge Types : 4
Retweet : 7
MentionsInRetweet : 29
Replies to : 5
Mentions : 13
Self-Loops : 2
Reciprocated Vertex Pair Ratio : 0.0666666666666667
Reciprocated Edge Ratio : 0.125
Connected Components : 1
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 7
Maximum Edges in a Connected Component : 54
Maximum Geodesic Distance (Diameter) : 2
Average Geodesic Distance : 1.102041
Graph Density : 0.380952380952381
Modularity : 0.204647
NodeXL Version : 1.0.1.446
Data Import : The graph represents a network of 7 Twitter users whose tweets in the requested range contained "kaiserfamfound", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 14 September 2021 at 17:40 UTC.

The requested start date was Tuesday, 14 September 2021 at 00:01 UTC and the maximum number of days (going backward) was 14.

The maximum number of tweets collected was 7,500.

The tweets in the network were tweeted over the 0-minute period from Tuesday, 07 September 2021 at 02:55 UTC to Tuesday, 07 September 2021 at 02:55 UTC.

Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".

Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : GraphServerTwitterSearch
Graph Term : kaiserfamfound
Groups : The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.
Edge Color : Edge Weight
Edge Width : Edge Weight
Edge Alpha : Edge Weight
Vertex Radius : Betweenness Centrality

Top Influencers: Top 10 Vertices, Ranked by Betweenness Centrality
Top URLs
Top Domains
Top Hashtags
Top Hashtags in Tweet in Entire Graph:
[9] jeanquan
[7] kaiser
[4] berkeleyca
[3] phan
[2] director
[2] lifelongover60
[2] 60yrs
[2] medical
[2] usa
[2] over60lifelong



Top Hashtags in Tweet in G1:
[9] jeanquan
[7] kaiser
[4] berkeleyca
[3] phan
[2] director
[2] lifelongover60
[2] 60yrs
[2] medical
[2] usa
[2] over60lifelong

Top Words
Top Word Pairs
Top Replied-To
Top Mentioned
Top Tweeters