The graph represents a network of 774 Twitter users whose tweets in the requested range contained "CHCF", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 09 November 2019 at 21:57 UTC.
The requested start date was Wednesday, 06 November 2019 at 01:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 65-day, 23-hour, 35-minute period from Sunday, 01 September 2019 at 01:10 UTC to Wednesday, 06 November 2019 at 00:45 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
Vertices : 774
Unique Edges : 991
Edges With Duplicates : 746
Total Edges : 1737
Number of Edge Types : 3
Mentions : 1377
Tweet : 314
Replies to : 46
Self-Loops : 314
Reciprocated Vertex Pair Ratio : 0.0991561181434599
Reciprocated Edge Ratio : 0.18042226487524
Connected Components : 122
Single-Vertex Connected Components : 81
Maximum Vertices in a Connected Component : 518
Maximum Edges in a Connected Component : 1432
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 2.766377
Graph Density : 0.00174159538159658
Modularity : 0.435499
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 774 Twitter users whose tweets in the requested range contained "CHCF", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 09 November 2019 at 21:57 UTC.
The requested start date was Wednesday, 06 November 2019 at 01:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 65-day, 23-hour, 35-minute period from Sunday, 01 September 2019 at 01:10 UTC to Wednesday, 06 November 2019 at 00:45 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 : CHCF
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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[225] health,care [142] medi,cal [110] managed,care [96] cal,managed [89] california,health [79] care,foundation [63] quality,care [52] care,plans [51] mental,health [42] serious,illness Top Word Pairs in Tweet in G1:
[79] health,care [57] medi,cal [46] managed,care [38] cal,managed [33] quality,care [27] care,plans [26] mental,health [25] serious,illness [21] #whatcawants,survey [20] interactive,map Top Word Pairs in Tweet in G2:
[36] health,care [32] california,health [31] care,foundation [10] medi,cal [8] care,california [8] quality,improvement [7] cal,managed [7] managed,care [5] dependent,newborns [5] newborns,new Top Word Pairs in Tweet in G3:
[15] first,time [15] health,care [13] low,risk [13] risk,first [12] experts,neel_shah [12] neel_shah,unnecesarean [12] unnecesarean,poojakmehta [12] poojakmehta,variation [12] variation,low [12] time,#csections Top Word Pairs in Tweet in G4:
[15] health,care [12] medi,cal [11] cal,managed [11] managed,care [7] #publiccharge,rule [6] serious,illness [6] access,health [6] last,friday [6] friday,white [6] white,house Top Word Pairs in Tweet in G5:
[6] childcare,issues [6] issues,gaining [6] gaining,interest [6] interest,country [6] country,parents [6] parents,need [6] need,go [6] go,work [6] work,quality [6] quality,programs Top Word Pairs in Tweet in G6:
[20] health,care [12] medi,cal [11] health,disparities [11] california,improvement [10] managed,care [8] cal,managed [8] improvement,network [7] quality,care [7] improvement,network's [6] california,health Top Word Pairs in Tweet in G7:
[27] medi,cal [22] managed,care [19] cal,managed [14] health,care [11] quality,care [10] care,plans [8] new,study [8] shows,lagging [8] lagging,quality [8] quality,improvement Top Word Pairs in Tweet in G9:
[6] health,care [5] proud,announce [5] announce,chcfnews' [5] chcfnews',investment [5] investment,unite [5] unite,invest [5] invest,health [5] care,tech [5] tech,service [5] service,companies Top Word Pairs in Tweet in G10:
[6] proud,serve [6] serve,under [6] under,#fmrevolution [6] #fmrevolution,super [6] super,stars [6] stars,panna [6] panna,lossy [6] lossy,md [6] md,tarascottmd [6] tarascottmd,#kinkaidfire Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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