The graph represents a network of 6,715 Twitter users whose tweets in the requested range contained "@CDCgov OR @CDC_eHealth OR @CDCemergency", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 25 March 2022 at 20:33 UTC.
The requested start date was Friday, 25 March 2022 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 2-day, 3-hour, 27-minute period from Tuesday, 22 March 2022 at 20:33 UTC to Friday, 25 March 2022 at 00:01 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 : 6715
Unique Edges : 9662
Edges With Duplicates : 19647
Total Edges : 29309
Number of Edge Types : 5
Replies to : 3430
Mentions : 14079
MentionsInRetweet : 8050
Retweet : 3692
Tweet : 58
Self-Loops : 146
Reciprocated Vertex Pair Ratio : 0.0264539972767944
Reciprocated Edge Ratio : 0.0515444381277241
Connected Components : 1
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 6715
Maximum Edges in a Connected Component : 29309
Maximum Geodesic Distance (Diameter) : 7
Average Geodesic Distance : 2.751591
Graph Density : 0.000351140558032016
Modularity : 0.369854
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 6,715 Twitter users whose tweets in the requested range contained "@CDCgov OR @CDC_eHealth OR @CDCemergency", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 25 March 2022 at 20:33 UTC.
The requested start date was Friday, 25 March 2022 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 2-day, 3-hour, 27-minute period from Tuesday, 22 March 2022 at 20:33 UTC to Friday, 25 March 2022 at 00:01 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 : @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:
[574] cdcgov,us_fda [512] rubin_allergy,cdcgov [503] covid,19 [373] cdcgov,cdcdirector [278] cdcdirector,cdcgov [230] kcmohealthdept,cdcgov [203] indoor,air [202] aerosols,fill [202] fill,room [200] share,same Top Word Pairs in Tweet in G1:
[389] covid,19 [155] safe,effective [134] #covid19,vaccines [133] vaccines,safe [127] 19,vaccines [122] side,effects [116] cdcgov,cdc [103] large,doses [88] growing,evidence [88] #covid19,vaccination Top Word Pairs in Tweet in G2:
[548] cdcgov,us_fda [504] rubin_allergy,cdcgov [99] cdcdirector,cdcgov [92] us_fda,cdcgov [92] cdcgov,cdcdirector [63] us_fda,uncpublichealth [63] uncpublichealth,nih [57] cdcgov,pfizer [53] dmitry_kats,rubin_allergy [44] needed,corruption Top Word Pairs in Tweet in G3:
[113] mild,cases [112] obama,hilary [112] hilary,psaki [112] psaki,credit [112] credit,vaccines [112] vaccines,mild [112] cases,don [112] don,many [112] many,vax [112] vax,efficacy Top Word Pairs in Tweet in G4:
[165] cdcgov,cdcdirector [158] chest,pain [157] cdcdirector,cdcgov [157] took,teen [157] teen,last [157] last,week [157] week,having [157] having,chest [157] pain,particularly [157] particularly,hard Top Word Pairs in Tweet in G5:
[187] indoor,air [185] share,same [185] same,indoor [185] air,nothing [185] nothing,magical [185] magical,ft [185] ft,aerosols [185] aerosols,fill [185] fill,room [185] room,cigaratte Top Word Pairs in Tweet in G6:
[229] kcmohealthdept,cdcgov [70] cdcgov,published [70] published,updated [70] updated,faq [70] faq,visitors [70] visitors,healthcare [70] healthcare,facilities [70] facilities,allowed [70] allowed,use [70] use,clean Top Word Pairs in Tweet in G7:
[28] usembassyaddis,cdcgov [27] cdcgov,pepfar [19] covid,19 [18] vaccines,safe [15] tuberculosis,tb [13] 19,vaccines [10] #dyk,tornadoes [10] tornadoes,occur [10] occur,btw [10] btw,driving Top Word Pairs in Tweet in G8:
[11] former,cdcgov [11] read,sentences [11] sentences,read [11] read,again [11] again,disastrously [11] disastrously,true [11] true,cdcgov [11] cdcgov,under [11] under,previous [11] previous,administration Top Word Pairs in Tweet in G9:
[9] tppf,repbethvanduyne [8] commentary,townhallcom [8] townhallcom,time [8] time,end [8] end,#bidenadministration [8] #bidenadministration,mask [8] mask,mandates [8] mandates,tppf [7] robhenneke,commentary [4] cdcgov,fema Top Word Pairs in Tweet in G10:
[21] tsa,cdcgov [20] jimmypatronis,tsa [12] cdcgov,delta [12] delta,jetblue [12] jetblue,americanair [12] americanair,united [12] united,hawaiianair [12] hawaiianair,alaskaair [12] alaskaair,spiritairlines [10] mask,mandate Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G9:
Top Tweeters in G10: