The graph represents a network of 5,764 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, 03 July 2020 at 20:47 UTC.
The requested start date was Friday, 03 July 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 1-day, 21-hour, 38-minute period from Wednesday, 01 July 2020 at 02:22 UTC to Friday, 03 July 2020 at 00:00 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 : 5764
Unique Edges : 8881
Edges With Duplicates : 11378
Total Edges : 20259
Number of Edge Types : 5
Replies to : 2304
Mentions : 9539
Retweet : 2492
MentionsInRetweet : 5881
Tweet : 43
Self-Loops : 96
Reciprocated Vertex Pair Ratio : 0.0141364957197832
Reciprocated Edge Ratio : 0.0278788817470766
Connected Components : 2
Single-Vertex Connected Components : 1
Maximum Vertices in a Connected Component : 5763
Maximum Edges in a Connected Component : 20258
Maximum Geodesic Distance (Diameter) : 7
Average Geodesic Distance : 2.872001
Graph Density : 0.000388735818954654
Modularity : 0.442276
NodeXL Version : 1.0.1.437
Data Import : The graph represents a network of 5,764 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, 03 July 2020 at 20:47 UTC.
The requested start date was Friday, 03 July 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 1-day, 21-hour, 38-minute period from Wednesday, 01 July 2020 at 02:22 UTC to Friday, 03 July 2020 at 00:00 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:
[1030] nanwhaley,cdcgov [1014] govmikedewine,nanwhaley [362] public,health [347] health,workers [346] former,cdcgov [346] cdcgov,head [346] head,drtomfrieden [346] drtomfrieden,stunning [346] stunning,furloughing [346] furloughing,public Top Word Pairs in Tweet in G1:
[351] public,health [346] former,cdcgov [346] cdcgov,head [346] head,drtomfrieden [346] drtomfrieden,stunning [346] stunning,furloughing [346] furloughing,public [346] health,workers [346] workers,amid [345] amid,pandemic Top Word Pairs in Tweet in G2:
[79] realdonaldtrump,cdcgov [55] cdcgov,joebiden [54] richardvassar1,govtimwalz [54] govtimwalz,tinasmithmn [54] tinasmithmn,realdonaldtrump [54] joebiden,barackobama [42] chell1459,richardvassar1 [38] hhsgov,cdcgov [34] cdcgov,nih [29] cdcgov,hhsgov Top Word Pairs in Tweet in G3:
[1024] nanwhaley,cdcgov [1008] govmikedewine,nanwhaley [125] masks,public [122] use,masks [121] public,places [120] support,mayor [120] mayor,nanwhaley [119] nanwhaley,dayton's [119] dayton's,decision [119] decision,require Top Word Pairs in Tweet in G4:
[138] socrates,belongs [117] peace,corps [78] corps,volunteer [76] fellow,named [76] named,socrates [76] belongs,american [76] american,peace [76] volunteer,quarantine [76] quarantine,option [75] senatordole,fellow Top Word Pairs in Tweet in G5:
[168] surgeon_general,cdcgov [38] cdcgov,surgeon_general [37] potus,thejusticedept [24] cvspharmacy,washspirit [24] washspirit,cvshealth [24] cvshealth,potus [24] thejusticedept,surgeon_general [24] cdcgov,cvspharmacy [24] cvspharmacy,cvsinaction [23] stephenspeaksup,cvspharmacy Top Word Pairs in Tweet in G6:
[94] huge,massive [94] massive,cdc [94] cdc,fraud [94] fraud,uncovered [94] uncovered,cdc [94] cdc,grossly [94] grossly,overcounting [94] overcounting,active [94] active,china [94] china,coronavirus Top Word Pairs in Tweet in G7:
[3] gavinnewsom,cdcgov [3] wear,masks [3] govmikedewine,nanwhaley [3] nanwhaley,cdcgov [3] londonbreed,gavinnewsom [2] kassandrakitson,gavinnewsom [2] cdcgov,drsanjaygupta [2] drsanjaygupta,lapublichealth [2] lapublichealth,cnnvalencia [2] therightmelissa,gavinnewsom Top Word Pairs in Tweet in G8:
[19] supportprop,cdcgov [6] chronic,pain [5] great,doc [5] doc,ruined [5] ruined,overzealous [5] overzealous,anti [5] anti,opioid [5] opioid,supportprop [5] cdcgov,know [5] know,nothing Top Word Pairs in Tweet in G9:
[39] cdcgov,azdhs [28] brahmresnik,cdcgov [13] gila,river [13] robert,washington [12] river,tribe [12] tribe,reopening [12] reopening,casinos [12] casinos,thursday [12] thursday,closed [12] closed,weeks Top Word Pairs in Tweet in G10:
[76] senronjohnson,cdcgov [47] columbus,day [10] rid,columbus [7] eliminate,columbus [5] getting,rid [5] day,go [5] away,columbus [5] day,spineless [4] cdcgov,cancelling [4] cancelling,columbus 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:
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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:
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Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
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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: