The graph represents a network of 2,704 Twitter users whose tweets in the requested range contained "#CDC", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 18 December 2019 at 15:13 UTC.
The requested start date was Wednesday, 18 December 2019 at 01:01 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 13-day, 23-hour, 54-minute period from Wednesday, 04 December 2019 at 01:01 UTC to Wednesday, 18 December 2019 at 00:56 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 : 2704
Unique Edges : 2913
Edges With Duplicates : 1888
Total Edges : 4801
Number of Edge Types : 3
Mentions : 3557
Tweet : 1039
Replies to : 205
Self-Loops : 1039
Reciprocated Vertex Pair Ratio : 0.0117354196301565
Reciprocated Edge Ratio : 0.0231985940246046
Connected Components : 579
Single-Vertex Connected Components : 331
Maximum Vertices in a Connected Component : 1175
Maximum Edges in a Connected Component : 2314
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 4.235383
Graph Density : 0.000389250821462894
Modularity : 0.597321
NodeXL Version : 1.0.1.422
Data Import : The graph represents a network of 2,704 Twitter users whose tweets in the requested range contained "#CDC", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 18 December 2019 at 15:13 UTC.
The requested start date was Wednesday, 18 December 2019 at 01:01 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 13-day, 23-hour, 54-minute period from Wednesday, 04 December 2019 at 01:01 UTC to Wednesday, 18 December 2019 at 00:56 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 : #CDC
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:
[285] lotusoak2,#cdc [177] #didyouknow,50 [177] 50,granted [177] granted,#vaccine [177] #vaccine,patents [177] patents,#cdc [177] #cdc,listed [177] listed,assignee [175] assignee,huge [173] lotusoak2,#didyouknow Top Word Pairs in Tweet in G1:
[252] lotusoak2,#cdc [163] #didyouknow,50 [163] 50,granted [163] granted,#vaccine [163] #vaccine,patents [163] patents,#cdc [163] #cdc,listed [163] listed,assignee [161] assignee,huge [159] lotusoak2,#didyouknow Top Word Pairs in Tweet in G2:
[130] #cdc,#cdc7words [130] #cdc7words,#bannedwords [130] #bannedwords,#orwell [130] #orwell,#doubleplusgoodspeak [130] #doubleplusgoodspeak,#maga [130] #maga,#trumphasdementia [39] based,#cdc [21] science,based [20] evidence,based [20] vulnerable,#cdc Top Word Pairs in Tweet in G3:
[98] jeremyrhammond,#cdc [50] #cdc,views [50] views,growing [50] growing,health [50] health,literacy [50] literacy,obstacle [50] obstacle,overcome [50] overcome,toward [50] toward,goal [50] goal,increasing Top Word Pairs in Tweet in G4:
[71] cdcgov,#cdc [64] thc,containing [62] containing,products [61] #cdc,found [61] found,vitamin [61] vitamin,acetate [61] acetate,additive [61] additive,thc [61] products,lung [61] lung,fluid Top Word Pairs in Tweet in G5:
[23] pain,patients [15] sudden,death [15] death,chronic [15] chronic,pain [15] patients,joke [15] joke,death [15] death,happens [15] happens,pain [15] pain,flares [15] flares,under Top Word Pairs in Tweet in G6:
[41] juntsxcat,#cdc [27] #cdc,esquerra_erc [10] règim,78 [8] tsunami_dem,juntsxcat [8] juntsxcat,esquerra_erc [7] els,mossos [7] #tombemelrègim,#independència [6] lluisbanyoles,deivistimbaler [6] deivistimbaler,patolucas48 [6] patolucas48,fartovich1 Top Word Pairs in Tweet in G7:
[3] #cdc,#fda [2] childrenshd,shame [2] shame,npr [2] npr,piling [2] piling,rfk [2] rfk,jr [2] jr,reminder [2] reminder,#bigpharma [2] #bigpharma,#bigchem [2] #bigchem,#cdc Top Word Pairs in Tweet in G8:
[18] #cdc,#fda [9] #vaxxed,#gmo [8] #dothestudy,clarity [8] vs,#unvaccinated [7] boysek,delbigtree [7] delbigtree,#dothestudy [7] clarity,#vaccinated [7] #vaccinated,vs [7] #unvaccinated,#cdc [7] #cdc,refuses Top Word Pairs in Tweet in G9:
[37] cult,dead [37] dead,cow [36] josephmenn,#cdc [36] starting,project [36] project,looking [36] looking,bullying [36] bullying,weapons [36] weapons,school [36] school,first [36] first,conclusion Top Word Pairs in Tweet in G10:
[18] energycommerce,repdianadegette [18] repdianadegette,repgregwalden [18] repgregwalden,susanwbrooks [18] susanwbrooks,frankpallone [18] frankpallone,repguthrie [18] repguthrie,drnancym_cdc [15] drnancym_cdc,nih [12] nih,phegov [11] #vaccines,#vaccineswork [10] #influenza,#vaccines Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: