The graph represents a network of 4,767 Twitter users whose tweets in the requested range contained "meded", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 06 April 2020 at 06:43 UTC.
The requested start date was Monday, 06 April 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 2-day, 16-hour, 56-minute period from Thursday, 02 April 2020 at 18:43 UTC to Sunday, 05 April 2020 at 11:40 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 : 4767
Unique Edges : 6423
Edges With Duplicates : 1830
Total Edges : 8253
Number of Edge Types : 4
MentionsInRetweet : 5116
Mentions : 2096
Tweet : 811
Replies to : 230
Self-Loops : 811
Reciprocated Vertex Pair Ratio : 0.0382782719186785
Reciprocated Edge Ratio : 0.0737341288052624
Connected Components : 318
Single-Vertex Connected Components : 109
Maximum Vertices in a Connected Component : 3622
Maximum Edges in a Connected Component : 6957
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 4.783551
Graph Density : 0.000287726123815457
Modularity : 0.709236
NodeXL Version : 1.0.1.429
Data Import : The graph represents a network of 4,767 Twitter users whose tweets in the requested range contained "meded", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 06 April 2020 at 06:43 UTC.
The requested start date was Monday, 06 April 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 2-day, 16-hour, 56-minute period from Thursday, 02 April 2020 at 18:43 UTC to Sunday, 05 April 2020 at 11:40 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 : meded
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:
[562] senden,meded [430] thread,#covid19 [413] physician,draft [412] draft,wow [412] wow,comparing [412] comparing,doctors [412] doctors,soldiers [412] soldiers,deal [412] deal,thread [411] agnessolberg,physician Top Word Pairs in Tweet in G1:
[48] training,faculty [47] orthopodreg,call [47] call,#nhs [47] #nhs,#nightingale [47] #nightingale,ll [47] ll,#meded [47] #meded,training [47] faculty,amazing [47] amazing,humans [47] humans,working Top Word Pairs in Tweet in G2:
[390] physician,draft [389] draft,wow [389] wow,comparing [389] comparing,doctors [389] doctors,soldiers [389] soldiers,deal [389] deal,thread [389] thread,#covid19 [388] agnessolberg,physician [388] #covid19,#physiciand Top Word Pairs in Tweet in G3:
[84] powerful,depiction [84] depiction,burdens [84] burdens,carried [84] carried,#womeninmedicine [84] #womeninmedicine,amazing [84] amazing,physician [84] physician,artist [84] artist,dr [84] dr,saira [84] saira,malik Top Word Pairs in Tweet in G4:
[88] #cardiotwitter,check [88] check,#tweetorial [88] #tweetorial,cv [88] cv,considerations [88] considerations,#covid19 [88] #covid19,viral [88] viral,cell [88] cell,entry [88] entry,using [88] using,ace2 Top Word Pairs in Tweet in G5:
[510] senden,meded [255] meded,senden [128] meded,ey [126] ey,vâhid [126] vâhid,ferd [126] ferd,samed [126] samed,senden [126] ey,lem [126] lem,yekûn [126] yekûn,küfven Top Word Pairs in Tweet in G6:
[129] #meded,#foamed [70] #foamed,#usmle [70] #usmle,#medtwitter [35] covid,19 [35] sars,cov [34] pathogenesis,covid [34] 19,sars [34] cov,virus [34] virus,#meded [34] #foamed,#covid19 Top Word Pairs in Tweet in G7:
[21] telephone,consultations [18] more,telephone [18] consultations,#gp [18] #gp,#covid2019 [18] #covid2019,#covidlockdown [18] #covidlockdown,#meded [18] #meded,#graphicmedicine [18] #graphicmedicine,#nhs [18] #nhs,#stayhomesavelives [17] thebaddr,more Top Word Pairs in Tweet in G8:
[11] senden,meded [6] #medtwitter,#meded [6] #meded,#medtwitter [5] meded,senden [4] covid,19 [3] meded,ey [3] infazda,adaletistiyoruz [3] top,tips [3] yâ,rab [3] rab,garibem Top Word Pairs in Tweet in G9:
[101] sars,cov [101] covid,19 [71] #foam,#foamed [67] supersummary,sars [67] cov,infection [67] infection,covid [67] 19,pathogenesis [67] pathogenesis,#sketchnote [67] #sketchnote,#quickreview [67] #quickreview,#meded Top Word Pairs in Tweet in G10:
[50] phdhpe,thread [43] resident,doctors [28] thread,going [28] going,sharing [28] sharing,stories [28] stories,resident [28] doctors,whose [28] whose,lives [28] lives,impacted [28] impacted,royal_college Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G7:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
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Top Mentioned in G6:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: