The graph represents a network of 1,021 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 Thursday, 24 October 2019 at 20:57 UTC.
The requested start date was Wednesday, 23 October 2019 at 00:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 82-day, 20-hour, 51-minute period from Thursday, 01 August 2019 at 02:46 UTC to Tuesday, 22 October 2019 at 23:37 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 : 1021
Unique Edges : 1332
Edges With Duplicates : 1011
Total Edges : 2343
Number of Edge Types : 3
Mentions : 1904
Tweet : 366
Replies to : 73
Self-Loops : 366
Reciprocated Vertex Pair Ratio : 0.0849624060150376
Reciprocated Edge Ratio : 0.156618156618157
Connected Components : 156
Single-Vertex Connected Components : 93
Maximum Vertices in a Connected Component : 703
Maximum Edges in a Connected Component : 1939
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 3.807789
Graph Density : 0.00138560811200092
Modularity : 0.473576
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 1,021 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 Thursday, 24 October 2019 at 20:57 UTC.
The requested start date was Wednesday, 23 October 2019 at 00:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 82-day, 20-hour, 51-minute period from Thursday, 01 August 2019 at 02:46 UTC to Tuesday, 22 October 2019 at 23:37 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:
[283] health,care [153] medi,cal [122] california,health [118] care,foundation [107] managed,care [98] mental,health [95] cal,managed [60] quality,care [51] care,plans [43] health,system Top Word Pairs in Tweet in G1:
[121] health,care [108] medi,cal [79] managed,care [68] cal,managed [49] mental,health [48] quality,care [41] care,plans [30] health,system [28] public,mental [26] interactive,map Top Word Pairs in Tweet in G2:
[42] health,care [38] california,health [37] 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 G3:
[14] first,time [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 [12] #csections,largely Top Word Pairs in Tweet in G4:
[33] health,care [18] #publiccharge,rule [18] mental,health [13] kff,poll [10] reminder,mental [10] care,1 [10] 1,health [10] care,priority [10] priority,californians [10] californians,recent Top Word Pairs in Tweet in G5:
[32] tech,enabled [27] 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 G6:
[4] naacp,hispanicfed [4] hispanicfed,thenewschool [4] thenewschool,tcfdotorg [4] tcfdotorg,appleseedny [4] appleseedny,integratenyc [4] integratenyc,uft [4] uft,metronyu [4] metronyu,teacherscollege [4] teacherscollege,afcnewyork [3] thank,mayawiley Top Word Pairs in Tweet in G7:
[6] dedicated,increasing [6] increasing,number [5] learn,more [5] attending,chcf_inc [5] chcf_inc,s [5] s,backpack [5] backpack,giveaway [5] giveaway,children [5] children,ps [5] ps,279 Top Word Pairs in Tweet in G8:
[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 G10:
[2] br4nd032,fixourcongress [2] fixourcongress,w_lemn [2] w_lemn,kittybhagat [2] kittybhagat,crisis187 [2] crisis187,mariecountryman [2] mariecountryman,anastasiosmanol [2] anastasiosmanol,harry_blunden [2] harry_blunden,peepeepoopoo0 Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G8:
Top Replied-To in G9:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
Top Mentioned in G8:
Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
Top Tweeters in G2:
Top Tweeters in G3:
Top Tweeters in G4:
Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: