The graph represents a network of 7,348 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, 16 December 2022 at 20:59 UTC.
The requested start date was Friday, 16 December 2022 at 01:01 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, 8-hour, 9-minute period from Tuesday, 13 December 2022 at 16:50 UTC to Friday, 16 December 2022 at 00:59 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 : 7348
Unique Edges : 9573
Edges With Duplicates : 14386
Total Edges : 23959
Number of Edge Types : 5
Retweet : 3899
MentionsInRetweet : 7797
Mentions : 9230
Replies to : 2998
Tweet : 35
Self-Loops : 97
Reciprocated Vertex Pair Ratio : 0.0131454766077929
Reciprocated Edge Ratio : 0.0259498303280325
Connected Components : 1
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 7348
Maximum Edges in a Connected Component : 23959
Maximum Geodesic Distance (Diameter) : 7
Average Geodesic Distance : 2.850525
Graph Density : 0.000278388247448086
Modularity : 0.436576
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 7,348 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, 16 December 2022 at 20:59 UTC.
The requested start date was Friday, 16 December 2022 at 01:01 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, 8-hour, 9-minute period from Tuesday, 13 December 2022 at 16:50 UTC to Friday, 16 December 2022 at 00:59 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:
[688] infection,check [686] saying,covid [686] check,know [686] fine,infection [686] covid,fine [686] know,half [685] half,fo [685] laurieallee,saying [333] covid,19 [288] gun,control Top Word Pairs in Tweet in G1:
[272] gun,control [267] defensive,gun [265] gun,use [263] cdcgov,removed [263] control,advocates [260] removed,defensive [260] corrupt,cdcgov [260] emails,show [259] officials,private [259] use,stats Top Word Pairs in Tweet in G2:
[192] cdcgov,cdcdirector [98] long,covid [89] us_fda,cdcgov [87] people,died [84] died,long [83] covid,claim [83] claim,essentially [83] claimed,3500 [83] week,cdcgov [83] 3500,people Top Word Pairs in Tweet in G3:
[664] infection,check [663] fine,infection [663] saying,covid [663] know,half [663] covid,fine [663] check,know [662] laurieallee,saying [662] half,fo [75] alexander_tin,cdcgov [62] school,change Top Word Pairs in Tweet in G4:
[226] study,found [226] dr,josephfraiman [224] found,pfizer [224] risk,serious [224] serious,adverse [224] exhibited,37 [224] higher,risk [224] josephfraiman,study [224] pfizer,trial [224] trial,exhibited Top Word Pairs in Tweet in G5:
[79] remain,top [79] congress,need [79] top,mind [79] few,weeks [79] left,congress [79] weeks,left [79] dementia,remain [77] need,alzheimer [77] alzheimer,dementia [27] please,include Top Word Pairs in Tweet in G6:
[221] whitehouse,cdcgov [111] creasonjana,whitehouse [26] creasonjana,ilegvm [26] ilegvm,whitehouse [22] berice556,creasonjana [10] creasonjana,its_the_dr [10] its_the_dr,whitehouse [9] cdcgov,whitehouse [9] covid,19 [7] preparedness,plan Top Word Pairs in Tweet in G7:
[31] during,winter [31] alone,rely [31] rely,medical [31] especially,those [31] equipment,during [31] older,live [31] weather,stop [31] medical,equipment [31] neighbors,especially [31] check,neighbors Top Word Pairs in Tweet in G8:
[94] cdcdirector,cdcgov [93] cdcgov,acfb [31] michael_hoerger,cdcgov [28] social,media [26] cdcgov,dear [26] reading,follow [26] media,manager [26] dear,social [26] lot,people [26] manager,reading Top Word Pairs in Tweet in G9:
[18] carlosdelrio7,lopezdoriga [15] drericding,erictopol [15] cdcgov,nytimes [15] mtosterholm,covidwatch [15] covidwatch,drericding [14] #covid19,mtosterholm [13] vacunar,jovenes [13] ayuda,prevenir [13] transmision,mas [13] jovenes,ayuda Top Word Pairs in Tweet in G10:
[33] cdcgov,guidance [23] community,levels [23] wear,mask [21] indoors,public [20] theangryepi,cdcgov [17] theangryepi,azdhs [12] mask,community [12] guidance,wear [12] accurate,cdcgov [12] providing,accurate 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 G10: