The graph represents a network of 405 Twitter users whose recent tweets were included in a list (Tweet ID List #Lives40) of 1455 tweet IDs, or who were replied to or mentioned in those tweets. 1366 out of 1455 tweets were collected. The network was obtained from Twitter on Sunday, 15 May 2022 at 08:19 UTC.
The tweets in the network were tweeted over the 11-day, 3-hour, 4-minute period from Tuesday, 03 May 2022 at 15:02 UTC to Saturday, 14 May 2022 at 18:06 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 : 405
Unique Edges : 1312
Edges With Duplicates : 2016
Total Edges : 3328
Self-Loops : 139
Reciprocated Vertex Pair Ratio : 0.0781153130812151
Reciprocated Edge Ratio : 0.144910868315124
Connected Components : 3
Single-Vertex Connected Components : 2
Maximum Vertices in a Connected Component : 403
Maximum Edges in a Connected Component : 3326
Maximum Geodesic Distance (Diameter) : 5
Average Geodesic Distance : 2.606979
Graph Density : 0.0106282850507273
Modularity : 0.266072
NodeXL Version : 1.0.1.449
Graph Gallery URL : https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=276352
Data Import : The graph represents a network of 405 Twitter users whose recent tweets were included in a list (Tweet ID List #Lives40) of 1455 tweet IDs, or who were replied to or mentioned in those tweets. 1366 out of 1455 tweets were collected. The network was obtained from Twitter on Sunday, 15 May 2022 at 08:19 UTC.
The tweets in the network were tweeted over the 11-day, 3-hour, 4-minute period from Tuesday, 03 May 2022 at 15:02 UTC to Saturday, 14 May 2022 at 18:06 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 : TwitterIDList
Graph Term : Tweet ID List #Lives40
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
Vertex Alpha : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[202] #lives40,esicm [131] esicm,#lives40 [100] esicm,euroelso [74] ground,breaking [74] breaking,release [59] #ecmo,workshop [52] day,mortality [52] youricm,ground [52] release,#lives40 [49] critically,ill Top Word Pairs in Tweet in G1:
[72] #lives40,esicm [60] esicm,#lives40 [20] prof,jordi [20] jordi,mancebo [19] honorary,membership [19] membership,esicm [19] esicm,prof [19] mancebo,#lives40 [14] mechanical,power [14] power,dark Top Word Pairs in Tweet in G2:
[27] #lives40,esicm [20] intensive,care [16] poster,#lives40 [16] heart,failure [15] next,up [14] esicm,#lives40 [13] guidelines,#lives40 [12] esicm,euroelso [11] critically,ill [10] #togethericu,#intensivecare Top Word Pairs in Tweet in G3:
[71] esicm,euroelso [46] #ecmo,workshop [46] #lives40,esicm [32] prxamonnet,#lives40 [32] vercaemstleen,dieterdauwe [29] madrid,#lives40 [28] euroelso,#ecmo [27] next,week [25] hemodynamic,monitoring [23] very,low Top Word Pairs in Tweet in G4:
[55] #lives40,esicm [52] ground,breaking [52] breaking,release [36] esicm,#lives40 [35] day,mortality [35] youricm,ground [35] release,#lives40 [34] editor,chief [29] 8,vs [29] vs,15 Top Word Pairs in Tweet in G5:
[11] further,evidence [11] evidence,33c [11] 33c,causes [11] causes,clinically [11] clinically,harmful [11] harmful,hemodynamic [11] hemodynamic,instability [11] instability,ttm2trial [11] ttm2trial,nielsen_niklas [11] nielsen_niklas,#lives40 Top Word Pairs in Tweet in G6:
[7] #lives40,margaret [7] margaret,herridge [7] herridge,talking [7] talking,trajectories [7] trajectories,critically [7] critically,ill [7] ill,patients [7] patients,reminding [7] reminding,importance [7] importance,pre Top Word Pairs in Tweet in G7:
[6] great,presentation [6] presentation,dr_romster [6] dr_romster,#lives40 [6] #lives40,prognostic [6] prognostic,information [6] information,gained [6] gained,hyperferritinaemia [6] hyperferritinaemia,ards [6] ards,independent [6] independent,validation Top Word Pairs in Tweet in G8:
[2] variable,pressure [2] pressure,support [2] support,vs [2] vs,nava [2] nava,first [2] first,randomized [2] randomized,controlled [2] controlled,trial [2] trial,#patients [2] #patients,#ards Top Word Pairs in Tweet in G9:
[3] sharing,learning [3] learning,international [3] international,stage [3] stage,#lives40 Top Word Pairs in Tweet in G10:
[2] new,antibiotics [2] antibiotics,coverage [2] coverage,resistance [2] resistance,mechanisms [2] mechanisms,ferrer_ricard [2] ferrer_ricard,#lives40 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 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 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: