The graph represents a network of 4,173 Twitter users whose recent tweets contained "meded", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/12/2023 5:00:36 PM. The network was obtained from Twitter on Monday, 13 March 2023 at 06:38 UTC.
The tweets in the network were tweeted over the 1708-day, 4-hour, 41-minute period from Sunday, 08 July 2018 at 19:18 UTC to Monday, 13 March 2023 at 00:00 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
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 : 4173
Unique Edges : 1720
Edges With Duplicates : 9829
Total Edges : 11549
Number of Edge Types : 9
Retweet : 4428
MentionsInRetweet : 5396
Tweet : 522
Replies to : 230
MentionsInReplyTo : 366
Mentions : 453
MentionsInQuote : 81
Quote : 57
MentionsInQuoteReply : 16
Self-Loops : 655
Reciprocated Vertex Pair Ratio : 0.012093023255814
Reciprocated Edge Ratio : 0.0238970588235294
Connected Components : 267
Single-Vertex Connected Components : 76
Maximum Vertices in a Connected Component : 3107
Maximum Edges in a Connected Component : 9401
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 3.757937
Graph Density : 0.000312468480316439
Modularity : 0.40245
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 4,173 Twitter users whose recent tweets contained "meded", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/12/2023 5:00:36 PM. The network was obtained from Twitter on Monday, 13 March 2023 at 06:38 UTC.
The tweets in the network were tweeted over the 1708-day, 4-hour, 41-minute period from Sunday, 08 July 2018 at 19:18 UTC to Monday, 13 March 2023 at 00:00 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch2
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:
[1805] #meded,#medtwitter [498] blood,#meded [498] kind,blood [498] receive,kind [465] #foamed,#meded [342] year,old [322] innov_medicine,receive [306] #medtwitter,#meded [299] immune,cells [297] cells,functions Top Word Pairs in Tweet in G1:
[591] #meded,#medtwitter [292] receive,kind [292] kind,blood [292] blood,#meded [288] innov_medicine,receive [246] immune,cells [246] cells,functions [246] functions,#meded [245] innov_medicine,immune [126] coronary,angioplasty Top Word Pairs in Tweet in G2:
[325] #meded,#medtwitter [204] year,old [166] receive,kind [166] kind,blood [166] blood,#meded [156] great,summary [156] summary,receive [155] brownjhm,great [123] old,man [107] #medtwitter,#foamed Top Word Pairs in Tweet in G3:
[468] #meded,#medtwitter [314] #foamed,#meded [186] #medtwitter,#medicalstudent [105] #medicaleducation,#emergency [105] #medicalstudent,#medicaleducation [80] #medtwitter,#foamed [68] abdominal,pain [61] pain,based [61] location,#foamed [61] differential,diagnosis Top Word Pairs in Tweet in G4:
[158] #meded,#medtwitter [72] pill,travels [72] ghostmedical,slava__bobrov [72] #medtwitter,#biology [72] stomach,#meded [72] #biology,ghostmedical [72] travels,stomach [71] paul_wischmeyer,pill [61] inotropes,essentials [61] vasopressors,inotropes Top Word Pairs in Tweet in G5:
[79] neuroimaging,#meded [79] forms,neuroimaging [78] drkeithsiau,forms [68] compatibility,simplified [68] blood,transfusion [68] transfusion,compatibility [68] simplified,#meded [67] drkeithsiau,blood [56] #meded,#medtwitter [26] #tipsfornewdocs,#meded Top Word Pairs in Tweet in G6:
[112] question,feel [112] wobbly,comes [112] wacky,wobbly [112] bit,wacky [112] comes,calling [112] call,question [112] call,call [112] calling,normal [112] feel,bit [111] teachplaygrub,call Top Word Pairs in Tweet in G7:
[34] pericardial,effusion [32] patient,systemic [32] strands,patient [32] lupus,erythematosus [32] effusion,fibrin [32] circumferential,pericardial [32] fibrin,strands [32] erythematosus,#pocus [32] systemic,lupus [32] large,circumferential Top Word Pairs in Tweet in G8:
[107] nociception,simply [107] stimuli,sensory [107] biological,detection [107] noxious,stimuli [107] sensory,experience [107] detection,noxious [107] put,biological [107] simply,put [106] drmiketodorovic,nociception [106] experience,assoc Top Word Pairs in Tweet in G9:
[74] year,old [66] old,man [61] exam,notable [61] blunt,trauma [61] presented,wk [61] soccer,practice [61] pain,swelling [61] swelling,blunt [61] trauma,during [61] hx,pain Top Word Pairs in Tweet in G10:
[88] #twitterx,#medtwitter [83] #pharmed,#meded [83] #medtwitter,#pharmed [66] pharmacotherapy,#twitterx [61] heart,failure [58] failure,pharmacotherapy [57] pyrlsapp,heart [21] #meded,#medtwitter [10] #foamed,#meded [10] attemp,localize Top Replied-To in Entire Graph:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G9:
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: