The graph represents a network of 6,939 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, 19 January 2022 at 10:53 UTC.
The requested start date was Wednesday, 19 January 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 6-day, 13-hour, 11-minute period from Wednesday, 12 January 2022 at 11:46 UTC to Wednesday, 19 January 2022 at 00:57 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 : 6939
Unique Edges : 3411
Edges With Duplicates : 10671
Total Edges : 14082
Number of Edge Types : 5
Retweet : 4460
MentionsInRetweet : 5345
Replies to : 563
Mentions : 1436
Tweet : 2278
Self-Loops : 2391
Reciprocated Vertex Pair Ratio : 0.00845113706207744
Reciprocated Edge Ratio : 0.0167606277616943
Connected Components : 1563
Single-Vertex Connected Components : 997
Maximum Vertices in a Connected Component : 2870
Maximum Edges in a Connected Component : 6606
Maximum Geodesic Distance (Diameter) : 22
Average Geodesic Distance : 7.615727
Graph Density : 0.000136323654914666
Modularity : 0.49817
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 6,939 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, 19 January 2022 at 10:53 UTC.
The requested start date was Wednesday, 19 January 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 6-day, 13-hour, 11-minute period from Wednesday, 12 January 2022 at 11:46 UTC to Wednesday, 19 January 2022 at 00:57 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:
[879] trust,#cdc [867] retweet,trust [866] judicialwatch,retweet [354] #cdc,#nft [326] #nft,#wavysaturday [320] compagnies,croisière [319] #cdc,vient [319] vient,d'annuler [319] d'annuler,toutes [319] toutes,obligations Top Word Pairs in Tweet in G1:
[62] covid,19 [60] #cdc,#cdc7words [60] #cdc7words,#bannedwords [60] #bannedwords,#orwell [60] #orwell,#doubleplusgoodspeak [60] #doubleplusgoodspeak,#maga [60] #maga,#trumphasdementia [35] #cdc,#covid19 [33] #cdc,#covid [30] #covid19,#cdc Top Word Pairs in Tweet in G2:
[864] trust,#cdc [859] retweet,trust [858] judicialwatch,retweet [4] judicialwatch,trust Top Word Pairs in Tweet in G3:
[320] #cdc,#nft [294] #nft,#wavysaturday [245] #wavysaturday,#giveaway [189] round,#wavysaturdays [174] one,guess [138] #wavysaturdays,pick [138] pick,# [138] #,100 [138] 100,one [128] #cro,#fftb Top Word Pairs in Tweet in G4:
[318] #cdc,vient [318] vient,d'annuler [318] d'annuler,toutes [318] toutes,obligations [318] obligations,vakc1nales [318] vakc1nales,compagnies [318] compagnies,croisière [318] croisière,compagnies [318] compagnies,aériennes [317] _2019_ncov,#cdc Top Word Pairs in Tweet in G5:
[18] cdcgov,cdcdirector [13] #cdcrecommends,#cdc [12] #cdc,#omicron [11] #cdc,cdcgov [11] #covaxin,#usa [11] #usa,#cdc [11] #omicron,#delta [11] #delta,#ocugen [11] #ocugen,covaxin [11] covaxin,neutralizes Top Word Pairs in Tweet in G6:
[86] cdcdirector,#cdc [84] #n95s,necessary [84] necessary,distribute [84] distribute,congress [84] congress,cdcdirector [84] #cdc,mask [83] lzj961,#n95s [83] mask,recommendatio [28] left,right [14] follow,#cdc Top Word Pairs in Tweet in G7:
[183] maxinelai2019,#cdc [74] #cdc,我真的很不喜歡記者的問法 [74] 我真的很不喜歡記者的問法,台灣防疫團隊人員辛苦了 [65] #cdc,好想幫記者會換桌布啊 [26] #cdc,我懷疑羅副當下4這樣想可是我沒有證據 [22] #cdc,ㄋㄧㄠˊㄋㄧㄠˊ Top Word Pairs in Tweet in G8:
[119] took,22 [119] 22,months [119] months,national [119] national,emergency [119] emergency,government [119] government,cdc [119] cdc,finally [119] finally,acknowledge [119] acknowledge,#n95 [119] #n95,better Top Word Pairs in Tweet in G9:
[104] protect,each [89] leonardroxon,time [84] fight,amongst [84] amongst,ourselves [83] time,protect [83] each,politicians [83] politicians,dividing [83] dividing,fight [83] ourselves,massively [83] massively,enrich Top Word Pairs in Tweet in G10:
[63] during,recent [63] recent,tv [63] tv,interview [63] interview,director [63] director,#cdc [63] #cdc,admitted [63] admitted,over [63] over,75 [63] 75,people [63] people,died Top Replied-To in Entire Graph:
Top Replied-To in G3:
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Top Replied-To in G9:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G7:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G3:
Top Tweeters in G4:
Top Tweeters in G5:
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Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: