The graph represents a network of 1,153 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 Friday, 08 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 96-day, 21-hour, 59-minute period from Thursday, 01 August 2019 at 02:46 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 : 1153
Unique Edges : 1533
Edges With Duplicates : 1191
Total Edges : 2724
Number of Edge Types : 3
Mentions : 2219
Tweet : 427
Replies to : 78
Self-Loops : 427
Reciprocated Vertex Pair Ratio : 0.0882352941176471
Reciprocated Edge Ratio : 0.162162162162162
Connected Components : 161
Single-Vertex Connected Components : 100
Maximum Vertices in a Connected Component : 838
Maximum Edges in a Connected Component : 2315
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 3.527688
Graph Density : 0.00125352341717259
Modularity : 0.46617
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 1,153 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 Friday, 08 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 96-day, 21-hour, 59-minute period from Thursday, 01 August 2019 at 02:46 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:
[329] health,care [159] medi,cal [141] california,health [129] care,foundation [111] managed,care [105] mental,health [97] cal,managed [65] quality,care [53] care,plans [44] health,system Top Word Pairs in Tweet in G1:
[111] health,care [69] medi,cal [49] managed,care [46] mental,health [41] cal,managed [32] quality,care [27] serious,illness [26] care,plans [24] health,system [22] community,health Top Word Pairs in Tweet in G2:
[62] health,care [53] medi,cal [41] managed,care [38] cal,managed [25] mental,health [24] #publiccharge,rule [23] quality,care [22] care,plans [17] care,provided [14] quality,improvement Top Word Pairs in Tweet in G3:
[44] health,care [40] california,health [39] care,foundation [12] medi,cal [9] care,california [8] quality,improvement [7] nurse,practitioners [7] cal,managed [7] managed,care [6] mental,health Top Word Pairs in Tweet in G4:
[6] dedicated,increasing [6] increasing,number [6] childcare,issues [6] issues,gaining [6] gaining,interest [6] interest,country [6] country,parents [6] parents,need [6] need,go [6] go,work Top Word Pairs in Tweet in G5:
[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] first,time [12] time,#csections Top Word Pairs in Tweet in G6:
[33] tech,enabled [28] enabled,innovation [16] opportunities,tech [16] #medicaid,market [15] impact,opportunities [15] greatest,impact [15] impact,#medicaid [15] new,research [13] market,new [13] research,chcfinnovations Top Word Pairs in Tweet in G7:
[2] nbc,sptv [2] nhmc,alpfa [2] alpfa,hacrorg [2] hacrorg,naleo [2] naleo,chcf_inc [2] chcf_inc,thenilpnetwork Top Word Pairs in Tweet in G8:
[21] health,care [12] california,improvement [10] ve,never [10] never,found [10] found,single [10] primary,care [9] improvement,network [8] medi,cal [7] managed,care [7] nurse,practitioners Top Word Pairs in Tweet in G10:
[4] ty,tabling [4] tabling,partners [4] partners,uscensusbureau [4] uscensusbureau,nycimmigrants [4] nycimmigrants,africansus [4] africansus,bxlegalservices [4] bxlegalservices,cpc_nyc [4] cpc_nyc,cuny [4] cuny,mexican [3] nysenatorrivera,ty Top Replied-To in Entire Graph:
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Top Replied-To in G7:
Top Replied-To in G9:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G10: