The graph represents a network of 5,110 Twitter users whose recent tweets contained "@CDCgov OR @CDC_eHealth OR @CDCemergency", 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 1/12/2023 5:00:35 PM. The network was obtained from Twitter on Friday, 13 January 2023 at 20:58 UTC.
The tweets in the network were tweeted over the 2257-day, 5-hour, 45-minute period from Monday, 07 November 2016 at 19:15 UTC to Friday, 13 January 2023 at 01:00 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 : 5110
Unique Edges : 4917
Edges With Duplicates : 14449
Total Edges : 19366
Number of Edge Types : 9
MentionsInReplyTo : 6513
Replies to : 2963
Mentions : 1093
MentionsInRetweet : 4038
Retweet : 1958
MentionsInQuote : 1009
Quote : 325
Tweet : 246
MentionsInQuoteReply : 1221
Self-Loops : 504
Reciprocated Vertex Pair Ratio : 0.0143995098039216
Reciprocated Edge Ratio : 0.0283902144367261
Connected Components : 2
Single-Vertex Connected Components : 1
Maximum Vertices in a Connected Component : 5109
Maximum Edges in a Connected Component : 19365
Maximum Geodesic Distance (Diameter) : 7
Average Geodesic Distance : 2.773546
Graph Density : 0.000380472815901029
Modularity : 0.361791
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 5,110 Twitter users whose recent tweets contained "@CDCgov OR @CDC_eHealth OR @CDCemergency", 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 1/12/2023 5:00:35 PM. The network was obtained from Twitter on Friday, 13 January 2023 at 20:58 UTC.
The tweets in the network were tweeted over the 2257-day, 5-hour, 45-minute period from Monday, 07 November 2016 at 19:15 UTC to Friday, 13 January 2023 at 01:00 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 : @CDCgov OR @CDC_eHealth OR @CDCemergency
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:
[313] cdcgov,cdcmmwr [302] covid,19 [208] alexberenson,cdcgov [183] gas,stoves [149] stoves,risky [148] paid,attention [147] attention,fight [147] know,pushback [147] risky,barely [147] pushback,more Top Word Pairs in Tweet in G1:
[93] cdcgov,cdc [80] flu,vaccine [80] cdcgov,sara [75] immune,system [56] flu,shot [50] cdcgov,stop [38] cdcgov,flu [37] ebola,outbreak [36] keep,dancing [35] vaccine,help Top Word Pairs in Tweet in G2:
[84] cdcgov,cdcdirector [45] us_fda,cdcgov [43] cdcgov,us_fda [34] cdcdirector,cdcgov [27] cdcgov,potus [27] pfizer,moderna_tx [24] covid,19 [23] cdcgov,nih [22] senronjohnson,cdcgov [20] cdcgov,pfizer Top Word Pairs in Tweet in G3:
[295] cdcgov,cdcmmwr [88] covid,19 [63] serious,adverse [60] 11,years [59] ages,11 [58] children,ages [58] reports,serious [57] finds,children [57] cdcmmwr,finds [56] booster,reports Top Word Pairs in Tweet in G4:
[127] pandemic,unvaccinated [127] 79,adults [127] sept,2021 [127] biden,declared [127] president,biden [127] 2021,president [127] adults,completed [127] declared,pandemic [127] unvaccinated,79 [123] epochtimes,sept Top Word Pairs in Tweet in G5:
[199] alexberenson,cdcgov [174] gas,stoves [144] paid,attention [144] stoves,risky [143] fight,know [143] know,pushback [143] attention,fight [143] barely,paid [143] risky,barely [143] pushback,more Top Word Pairs in Tweet in G6:
[97] lowest,decade [88] vax,rates [88] measles,vax [88] data,childhood [88] decade,cdcgov [88] kids,entering [88] fallen,lowest [88] entering,kindergarten [88] rates,kids [88] cdcgov,data Top Word Pairs in Tweet in G7:
[99] drcaliff_fda,cdcgov [57] covid,19 [53] hospitalization,death [52] significant,reduction [52] bivalent,covid [52] associated,significant [52] reduction,hospitalization [52] vaccines,associated [52] 19,vaccines [51] drcaliff_fda,bivalent Top Word Pairs in Tweet in G8:
[6] amermedicalassn,cdcgov [5] cdcgov,cdcmmwr [4] lawhern1,louiseshoger [4] drugpolicyorg,amermedicalassn [4] cdcinjury,deahq [4] louiseshoger,oldheadfighta [4] jonelleelgaway,lawhern1 [4] cdcgov,cdcinjury [4] oldheadfighta,drugpolicyorg [4] oigathhs,cdcgov Top Word Pairs in Tweet in G9:
[16] molegdems,mosendems [8] theheartlandpod,erictrump [8] johnjrizzo,pdbeth [8] kcstar,parock [8] cwg18,englishteach07 [8] vp,cdcgov [8] fema,cdcgov [8] maddow,tishaura [8] nettaaaaaaaa,johnwoodmo [8] lauraannstl,laraleatrump Top Word Pairs in Tweet in G10:
[6] erictopol,nejm [4] cdcgov,cdcdirector [4] jan,12 [3] #covid19,mtosterholm [3] cdcgov,nytimes [3] covidwatch,drericding [3] drericding,erictopol [3] erictopol,cdcgov [3] mtosterholm,covidwatch [3] nejm,cdcgov 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 G5:
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: