The graph represents a network of 3,178 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, 06 November 2019 at 12:40 UTC.
The requested start date was Wednesday, 06 November 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, 45-minute period from Wednesday, 23 October 2019 at 01:03 UTC to Wednesday, 06 November 2019 at 00:48 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 : 3178
Unique Edges : 4051
Edges With Duplicates : 1916
Total Edges : 5967
Number of Edge Types : 3
Mentions : 4190
Tweet : 1567
Replies to : 210
Self-Loops : 1567
Reciprocated Vertex Pair Ratio : 0.0098065922092073
Reciprocated Edge Ratio : 0.0194227137847316
Connected Components : 719
Single-Vertex Connected Components : 483
Maximum Vertices in a Connected Component : 1557
Maximum Edges in a Connected Component : 3421
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 4.586959
Graph Density : 0.000367156717383222
Modularity : 0.582029
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 3,178 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, 06 November 2019 at 12:40 UTC.
The requested start date was Wednesday, 06 November 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, 45-minute period from Wednesday, 23 October 2019 at 01:03 UTC to Wednesday, 06 November 2019 at 00:48 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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[233] #didyouknow,50 [233] 50,granted [233] granted,#vaccine [233] #vaccine,patents [233] patents,#cdc [233] #cdc,listed [233] listed,assignee [227] vaccine,injured [175] #cdc,tells [167] cdc,worker Top Word Pairs in Tweet in G1:
[149] #didyouknow,50 [149] 50,granted [149] granted,#vaccine [149] #vaccine,patents [149] patents,#cdc [149] #cdc,listed [149] listed,assignee [148] pregnant,women [142] #cdc,tells [134] #cdc,recommends Top Word Pairs in Tweet in G2:
[77] viraburnayeva,#didyouknow [77] #didyouknow,50 [77] 50,granted [77] granted,#vaccine [77] #vaccine,patents [77] patents,#cdc [77] #cdc,listed [77] listed,assignee [64] viraburnayeva,#cdc [24] tells,mothers Top Word Pairs in Tweet in G3:
[115] sallykp,cdc [115] cdc,worker [115] worker,flips [115] flips,mother [115] mother,vaccine [115] vaccine,injured [115] injured,child [115] child,unbelievable [115] unbelievable,cdcgov [115] cdcgov,#masonsmom Top Word Pairs in Tweet in G4:
[60] kaiser,permanente [60] permanente,letter [60] letter,blaming [60] blaming,#opioidcrisis [60] #opioidcrisis,reason [60] reason,restricting [60] restricting,opioids [60] opioids,50mme [60] 50mme,longer [59] canadapain,kaiser Top Word Pairs in Tweet in G5:
[48] before,reach [48] reach,adulthood [47] scary,american [47] american,kids [47] kids,regularly [47] regularly,watch [47] watch,tv [47] tv,witnessed [47] witnessed,thousands [47] thousands,murders Top Word Pairs in Tweet in G6:
[22] juntsxcat,#cdc [11] #cdc,esquerra_erc [11] règim,78 [8] #tombemelrègim,#independència [6] esquerra_erc,són [6] ni,amb [6] cupnacional,juntsxcat [5] esquerra_erc,juntsxcat [4] d,juntsxcat [4] amb,esquerra_erc Top Word Pairs in Tweet in G7:
[8] self,made [6] hodder,people [6] people,struggling [6] struggling,meet [6] meet,daily [6] daily,needs [6] needs,income [6] income,management [6] management,makes [6] makes,life Top Word Pairs in Tweet in G8:
[49] l'ex,direttore [49] direttore,#cdc [49] #cdc,julie [49] julie,gerberding [49] gerberding,ha [49] ha,ammesso [49] ammesso,alla [49] alla,cnn [49] cnn,che [49] che,#vaccini Top Word Pairs in Tweet in G10:
[66] seu,ingresso [66] ta,acabando [36] é,amanhã [36] amanhã,#cdc [36] #cdc,lá [36] lá,salão [36] salão,kadão [36] kadão,na [36] na,cancela [36] cancela,preta Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
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Top Tweeters in G10: