The graph represents a network of 4,591 Twitter users whose recent tweets contained "#CDC", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 2/14/2023 5:00:35 PM. The network was obtained from Twitter on Wednesday, 15 February 2023 at 11:00 UTC.
The tweets in the network were tweeted over the 2372-day, 6-hour, 29-minute period from Wednesday, 17 August 2016 at 18:30 UTC to Wednesday, 15 February 2023 at 01:00 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
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 : 4591
Unique Edges : 2330
Edges With Duplicates : 8630
Total Edges : 10960
Number of Edge Types : 9
Retweet : 3121
MentionsInRetweet : 3741
Tweet : 1406
Quote : 402
Mentions : 574
MentionsInQuote : 199
Replies to : 452
MentionsInReplyTo : 1004
MentionsInQuoteReply : 61
Self-Loops : 1722
Reciprocated Vertex Pair Ratio : 0.0110610405571487
Reciprocated Edge Ratio : 0.0218800648298217
Connected Components : 729
Single-Vertex Connected Components : 386
Maximum Vertices in a Connected Component : 1787
Maximum Edges in a Connected Component : 5289
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 5.736073
Graph Density : 0.000234236825009052
Modularity : 0.463013
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 4,591 Twitter users whose recent tweets contained "#CDC", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 2/14/2023 5:00:35 PM. The network was obtained from Twitter on Wednesday, 15 February 2023 at 11:00 UTC.
The tweets in the network were tweeted over the 2372-day, 6-hour, 29-minute period from Wednesday, 17 August 2016 at 18:30 UTC to Wednesday, 15 February 2023 at 01:00 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch2
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:
[719] #cdc,#fda [341] #ファイザー社,#心筋炎 [339] とにかくワクチン接種を推し進めた,#ファイザー社 [336] #心筋炎,#cdc [334] 多くの身体障害や死亡が発生している,ファイザー社は [334] ワクチン接種によって,多くの身体障害や死亡が発生している [334] 自社のワクチンが10代の若者の心を傷つける可能性があることを知りながら,とにかくワクチン接種を推し進めた [334] ファイザー社は,自社のワクチンが10代の若者の心を傷つける可能性があることを知りながら [322] himalayajapan,ワクチン接種によって [322] #fda,#mrna Top Word Pairs in Tweet in G1:
[327] #cdc,#fda [326] #ファイザー社,#心筋炎 [325] とにかくワクチン接種を推し進めた,#ファイザー社 [321] #心筋炎,#cdc [319] 多くの身体障害や死亡が発生している,ファイザー社は [319] ワクチン接種によって,多くの身体障害や死亡が発生している [319] 自社のワクチンが10代の若者の心を傷つける可能性があることを知りながら,とにかくワクチン接種を推し進めた [319] ファイザー社は,自社のワクチンが10代の若者の心を傷つける可能性があることを知りながら [317] #fda,#mrna [317] himalayajapan,ワクチン接種によって Top Word Pairs in Tweet in G2:
[59] #ourinterestingtimes,#caesarmessiah [59] #impfquote,gg [59] #luther,#maskenrunter [59] #lauterbach,#luther [59] gg,#impftote [59] #buildbackbetter,#lauterbach [59] #caesarmessiah,#buildbackbetter [49] #cdc7words,#bannedwords [49] #doubleplusgoodspeak,#maga [49] #maga,#trumphasdementia Top Word Pairs in Tweet in G3:
[63] learn,more [63] risk,death [62] safety,study [62] showed,increased [62] study,showed [62] increased,risk [62] vaccine,safety [62] death,linked [61] vaccination,learn [61] #cdc,vaccine Top Word Pairs in Tweet in G4:
[165] #cdc,alle [164] wirklich,medizinische [164] medizinische,fehlinformationen [164] #petermccullogh,wirklich [164] fehlinformationen,verbreitet [164] die,#cdc [164] verbreitet,die [164] #robertmalone,#petermccullogh [163] george_orwell3,#robertmalone [46] #cdc,signalanalysen Top Word Pairs in Tweet in G5:
[45] #cdc,#fda [16] #fda,#who [13] answer,#nuremberg2 [13] #nuremberg2,#unitedwewin [13] #crimesagainsthumanity,#cdc [13] #cdc,#who [12] #cdc,#vaccinedeaths [12] systematically,culled [12] #vaccinedeaths,#vaccinegenocide [12] being,systematically Top Word Pairs in Tweet in G6:
[22] anti,mrna [22] changes,everything [22] til,anti [22] anti,vax [22] everything,#cdc [22] gatewaypundit,til [22] mrna,changes [22] #cdc,#antivax [22] vax,anti [21] portcitybob,gatewaypundit Top Word Pairs in Tweet in G7:
[62] #biden,forc [62] approving,conspiring [62] #cdc,looked [62] adverse,reactions [62] looked,adverse [62] conspiring,#biden [62] drugs,before [62] fordmb1,#cdc [62] before,approving [62] reactions,drugs Top Word Pairs in Tweet in G8:
[22] wish,see [22] see,death [16] genew22614687,plwin49 [16] plwin49,dawnimatrix [16] mediaclymer,genew22614687 [14] ibdgirl76,thomasklinemd [14] thomasklinemd,mediaclymer [14] dawnimatrix,headdock [14] headdock,faithgirlee [12] death,harm Top Word Pairs in Tweet in G9:
[74] #cdc,#fda [72] #pfizer,#moderna [56] #nih,#cdc [46] #informedconsent,#nurembergcode [39] asherpress,#informedconsent [29] people,die [29] nih,director [29] #mrna,dismissed [29] #moderna,#mrna [29] dismissed,senator Top Word Pairs in Tweet in G10:
[19] quarantine,authority [19] nord,stream [19] masks,again [19] false,flag [19] emergency,nord [19] cdc's,quarantine [19] stream,false [19] authority,require [19] require,emergency [19] flag,masks Top Replied-To in Entire Graph:
Top Replied-To in G3:
Top Replied-To in G5:
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:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
Top Mentioned in G8:
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:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: