The graph represents a network of 5,645 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 3/2/2023 5:00:36 PM. The network was obtained from Twitter on Friday, 03 March 2023 at 20:59 UTC.
The tweets in the network were tweeted over the 2722-day, 7-hour, 10-minute period from Friday, 18 September 2015 at 17:49 UTC to Friday, 03 March 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 : 5645
Unique Edges : 7193
Edges With Duplicates : 16399
Total Edges : 23592
Number of Edge Types : 9
MentionsInReplyTo : 7792
Replies to : 2615
Retweet : 2071
MentionsInRetweet : 5076
Tweet : 263
Mentions : 1920
Quote : 354
MentionsInQuoteReply : 2354
MentionsInQuote : 1147
Self-Loops : 652
Reciprocated Vertex Pair Ratio : 0.0133613445378151
Reciprocated Edge Ratio : 0.0263703457998176
Connected Components : 4
Single-Vertex Connected Components : 3
Maximum Vertices in a Connected Component : 5642
Maximum Edges in a Connected Component : 23589
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 2.848295
Graph Density : 0.000378495171746225
Modularity : 0.354854
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 5,645 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 3/2/2023 5:00:36 PM. The network was obtained from Twitter on Friday, 03 March 2023 at 20:59 UTC.
The tweets in the network were tweeted over the 2722-day, 7-hour, 10-minute period from Friday, 18 September 2015 at 17:49 UTC to Friday, 03 March 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] pregnant,women [309] still,pushing [308] cdcgov,ignore [303] ignore,data [303] women,cdcgov [303] vaccines,pregnant [303] pushing,vaccines [303] data,continually [251] cdcgov,cdc [204] covid,19 Top Word Pairs in Tweet in G1:
[227] cdcgov,cdc [149] drug,resistant [132] extensively,drug [121] health,alert [119] health,advisory [118] network,health [118] alert,network [117] cdc,issues [117] resistant,shigellosis [117] issues,health Top Word Pairs in Tweet in G2:
[104] #covidvaccine,campaign [103] enormous,loss [103] life,disability [103] disability,injuries [103] global,debacle [103] debacle,enormous [103] campaign,global [103] loss,life [102] p_mcculloughmd,#covidvaccine [102] injuries,amplifie Top Word Pairs in Tweet in G3:
[303] pregnant,women [301] still,pushing [301] vaccines,pregnant [301] cdcgov,ignore [301] pushing,vaccines [301] women,cdcgov [301] data,continually [301] ignore,data [191] theredactedinc,still [108] efenigson,still Top Word Pairs in Tweet in G4:
[161] cdcgov,fema [158] epa,cdcgov [147] whitehouse,potus [86] potus,direction [84] east,palestine [80] potus,epa [78] check,families [78] palestine,check [78] direction,epa [78] families,provide Top Word Pairs in Tweet in G5:
[23] cia,fbi [22] fbi,cdcgov [20] btysonmd,cia [12] lab,energy [12] idea,covid [12] department,one [12] leaked,lab [12] covid,leaked [12] energy,department [12] cdcgov,idea Top Word Pairs in Tweet in G6:
[49] covid,19 [34] cdcgov's,nchstats [33] death,certificates [32] 19,death [31] alexander_tin,cdcgov's [29] updated,guidance [28] guidance,covid [28] addresses,possibility [28] nchstats,updated [28] certificates,addresses Top Word Pairs in Tweet in G7:
[14] free,skywarn [14] class,storm [14] 2023,month [14] month,resolution [14] take,free [14] spotter,class [14] #resolvetobeready,2023 [14] skywarn,storm [14] resolution,take [14] storm,spotter Top Word Pairs in Tweet in G8:
[24] barackobama,realdonaldtrump [23] yougov,andrewromano [23] realdonaldtrump,nra [23] yahoonews,yougov [23] peterbakernyt,yahoonews [23] bigrossi69,peterbakernyt [23] nra,justintrudeau [23] andrewromano,joebiden [23] joebiden,barackobama [18] ohioepa,cdcgov Top Word Pairs in Tweet in G9:
[32] molegdems,mosendems [18] vp,cdcgov [16] jewelcommittee,lucaskuncemo [16] eric_schmitt,mogov [16] j_hancock,jacksuntrup [16] the_mip,hawleymo [16] mizzoulaw,molegdems [16] pdbeth,nettaaaaaaaa [16] lucaskuncemo,scottsifton [16] efmoriarty,the_mip Top Word Pairs in Tweet in G10:
[33] wole_m_fayemi,queenelizabeth [33] motorious_eu,wole_m_fayemi [33] onyx_project,motorious_eu [33] katemiddstyle,dukecambridgeuk [33] dukecambridgeuk,governorpataki [33] queenelizabeth,katemiddstyle [31] governorpataki,nychra [27] v1sionzero_tech,nhtsagov [27] nyccouncil,mmtconline [27] ledzeppelin,nyccouncil 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:
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Top Tweeters in G9:
Top Tweeters in G10: