The graph represents a network of 9,572 Twitter users whose tweets in the requested range contained "healthcare", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 12 September 2022 at 05:10 UTC.
The requested start date was Monday, 12 September 2022 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 3-day, 0-hour, 26-minute period from Thursday, 08 September 2022 at 10:42 UTC to Sunday, 11 September 2022 at 11:09 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 : 9572
Unique Edges : 5463
Edges With Duplicates : 11162
Total Edges : 16625
Number of Edge Types : 5
Retweet : 5013
MentionsInRetweet : 6197
Tweet : 2145
Mentions : 2258
Replies to : 1012
Self-Loops : 2201
Reciprocated Vertex Pair Ratio : 0.00907543959160522
Reciprocated Edge Ratio : 0.0179876335019674
Connected Components : 2282
Single-Vertex Connected Components : 900
Maximum Vertices in a Connected Component : 2941
Maximum Edges in a Connected Component : 6868
Maximum Geodesic Distance (Diameter) : 36
Average Geodesic Distance : 10.180394
Graph Density : 9.70925586909509E-05
Modularity : 0.573291
NodeXL Version : 1.0.1.504
Data Import : The graph represents a network of 9,572 Twitter users whose tweets in the requested range contained "healthcare", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 12 September 2022 at 05:10 UTC.
The requested start date was Monday, 12 September 2022 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 3-day, 0-hour, 26-minute period from Thursday, 08 September 2022 at 10:42 UTC to Sunday, 11 September 2022 at 11:09 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 : healthcare
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 Domains
Top Word Pairs in Tweet in Entire Graph:
[621] ãƒ,ム[425] united,states [417] life,expectancy [402] drop,top [402] top,50 [400] states,soon [400] soon,drop [400] 50,nations [400] nations,terms [400] terms,life Top Word Pairs in Tweet in G1:
[48] global,healthcare [46] healthcare,conference [40] morgan,stanley [37] present,morgan [37] ãƒ,ム[29] 20th,annual [29] annual,global [26] healthcare,system [26] ø,ø [24] stanley,20th Top Word Pairs in Tweet in G2:
[393] life,expectancy [392] united,states [392] states,soon [392] soon,drop [392] drop,top [392] top,50 [392] 50,nations [392] nations,terms [392] terms,life [392] expectancy,country Top Word Pairs in Tweet in G3:
[351] healthcare,service [335] service,medicine [335] medicine,food [335] food,telecommunications [329] telecommunications,banking [280] banking,million [232] #tigrayisbleeding,healthcare [173] million,people [83] selamse71964761,#tigrayisbleeding [83] million,peopâ Top Word Pairs in Tweet in G4:
[220] against,lowering [164] 19th,amendment [163] question,think [163] think,repeal [163] repeal,19th [163] amendment,boebert [163] boebert,question [163] question,exception [163] exception,rape [163] rape,incest Top Word Pairs in Tweet in G5:
[167] universal,healthcare [166] forced,birth [166] birth,country [166] family,medical [165] country,universal [165] healthcare,universal [165] universal,childcare [165] childcare,paid [165] paid,family [165] medical,leave Top Word Pairs in Tweet in G6:
[84] mps,spend [84] spend,one [84] one,day [84] day,nurse [84] nurse,medical [84] medical,ward [84] ward,gp [84] gp,practice [84] practice,immediately [84] immediately,doing Top Word Pairs in Tweet in G7:
[252] george,bush [252] bush,war [252] war,recession [128] economic,growth [126] recession,bill [126] bill,clinton [126] clinton,economic [126] growth,balanced [126] balanced,budget [126] budget,george Top Word Pairs in Tweet in G8:
[21] canada,capita [13] acute,care [12] fewer,acute [11] healthcare,system [11] #healthcare,#digitalhealth [10] capita,45 [10] 45,more [10] more,covid [10] covid,patients [10] patients,hospital Top Word Pairs in Tweet in G9:
[105] khairykj,dont [105] dont,know [105] know,reach [105] reach,hoping [105] hoping,see [105] see,psychiatric [105] psychiatric,patient [104] mirstheveil,khairykj [95] patient,cur [9] patient,curâ Top Word Pairs in Tweet in G10:
[17] gave,kred [17] kred,#influence [12] #iot,#iiot [11] #healthcare,#healthtech [11] #ehealth,#mhealth [11] #healthtech,#ehealth [10] healthcare,#ai [10] #ai,#usecases [10] #usecases,#trends [10] #trends,#executivebrief 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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Top Tweeters in G10: