The graph represents a network of 4,448 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 3/7/2023 5:00:33 PM. The network was obtained from Twitter on Wednesday, 08 March 2023 at 11:00 UTC.
The tweets in the network were tweeted over the 1063-day, 3-hour, 34-minute period from Wednesday, 08 April 2020 at 21:25 UTC to Wednesday, 08 March 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 : 4448
Unique Edges : 2694
Edges With Duplicates : 9127
Total Edges : 11821
Number of Edge Types : 9
Retweet : 3254
MentionsInRetweet : 4413
Replies to : 551
Tweet : 1333
Mentions : 575
Quote : 253
MentionsInReplyTo : 1190
MentionsInQuote : 229
MentionsInQuoteReply : 23
Self-Loops : 1655
Reciprocated Vertex Pair Ratio : 0.0114545454545455
Reciprocated Edge Ratio : 0.0226496494697106
Connected Components : 578
Single-Vertex Connected Components : 304
Maximum Vertices in a Connected Component : 2486
Maximum Edges in a Connected Component : 7464
Maximum Geodesic Distance (Diameter) : 16
Average Geodesic Distance : 6.411653
Graph Density : 0.000281240040573792
Modularity : 0.471188
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 4,448 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 3/7/2023 5:00:33 PM. The network was obtained from Twitter on Wednesday, 08 March 2023 at 11:00 UTC.
The tweets in the network were tweeted over the 1063-day, 3-hour, 34-minute period from Wednesday, 08 April 2020 at 21:25 UTC to Wednesday, 08 March 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:
[411] cdcを誰も信じない理由だ,#心臓病 [411] 常識のある親であれば,子供にワクチンを接種させ続けることはないだろう [411] cdcは,ワクチンによる心筋炎から回復した子供は [411] ワクチンによる心筋炎から回復した子供は,次のワクチン接種を受けることを推奨している [411] これが,cdcを誰も信じない理由だ [411] 子供にワクチンを接種させ続けることはないだろう,これが [411] 次のワクチン接種を受けることを推奨している,常識のある親であれば [409] #心臓病,#ワクチン接種 [409] #ワクチン接種,#cdc [372] himalayajapan,cdcは Top Word Pairs in Tweet in G1:
[385] これが,cdcを誰も信じない理由だ [385] cdcは,ワクチンによる心筋炎から回復した子供は [385] 常識のある親であれば,子供にワクチンを接種させ続けることはないだろう [385] 次のワクチン接種を受けることを推奨している,常識のある親であれば [385] ワクチンによる心筋炎から回復した子供は,次のワクチン接種を受けることを推奨している [385] cdcを誰も信じない理由だ,#心臓病 [385] 子供にワクチンを接種させ続けることはないだろう,これが [383] #心臓病,#ワクチン接種 [383] #ワクチン接種,#cdc [368] himalayajapan,cdcは Top Word Pairs in Tweet in G2:
[166] covid,vaccine [160] overwhelming,covid [160] killed,thousands [160] thousands,within [160] vaccine,killed [160] data,clear [160] clear,overwhelming [159] within,first [159] first,48 [159] 48,hours Top Word Pairs in Tweet in G3:
[75] #fda,#cdc [65] #ccpvaccines,#ccpvirus [63] #cdc,#mrna [62] #doubleplusgoodspeak,#maga [62] #cdc7words,#bannedwords [62] #cdc,#cdc7words [62] #bannedwords,#orwell [62] #maga,#trumphasdementia [62] #orwell,#doubleplusgoodspeak [52] #ccpvirus,#covid Top Word Pairs in Tweet in G4:
[29] big,pharma [28] realdailywire,chickfrmontario [28] chickfrmontario,nohj_85 [28] potus,realdailywire [28] cdcgov,pfizer [28] pharma,cdcgov [28] really,big [28] cdc,really [28] pfizer,potus [27] nohj_85,iambrookjac Top Word Pairs in Tweet in G5:
[149] ecosystem,prizes [149] #cronos,ecosystem [149] #freemintnft,enter [149] collab,#giveaway [149] #cro,project [149] project,#cronos [149] prizes,1x [149] #giveaway,#107 [149] #107,#cro [149] 1x,#freemintnft Top Word Pairs in Tweet in G6:
[112] 居然说没有足够的资料可以推动每年打新冠加强针,但仔细一看是他们在说大多数就不用打了 [112] 但仔细一看是他们在说大多数就不用打了,但是老人和那些免疫力系统被破坏的人还是要多打 [112] 但是老人和那些免疫力系统被破坏的人还是要多打,这是要把老弱病残彻底消灭的节奏 [112] 这是要把老弱病残彻底消灭的节奏,不过还是可以用这篇文章说 [112] 不过还是可以用这篇文章说,cdc认为打加新冠加针没用 [112] 主流媒体和cdc,居然说没有足够的资料可以推动每年打新冠加强针 [111] bob20227,主流媒体和cdc [111] cdc认为打加新冠加针没用,ht [100] vaccines,everything [100] #nobody,trusts Top Word Pairs in Tweet in G7:
[32] pain,patients [30] #cdc,#prop [30] #dea,#cdc [24] #prop,#antiopioidrxfanatics [20] #cdc,#dea [17] ibdgirl76,thomasklinemd [14] sentence,meds [14] joeallennewman,cmerandi [14] death,sentence [14] treat,diabetes Top Word Pairs in Tweet in G8:
[139] atf,doj [139] last,one [139] fbi,cdc [139] one,come [139] heel,gaetz [139] come,heel [139] repmattgaetz,called [139] doj,last [139] cdc,atf [139] gaetz,repmattgaetz Top Word Pairs in Tweet in G9:
[53] during,pandemic [53] government,#plandemic [53] states,government [53] #plandemic,#feds [53] greatest,perpetrator [53] pandemic,united [53] misinformation,during [53] united,states [53] perpetrator,misinformation [52] seaseabee,greatest Top Word Pairs in Tweet in G10:
[69] government,data [69] increased,mentral [69] mentral,abnormalities [69] 57,fold [69] #covidvaccine,increased [69] shows,#covidvaccine [69] fold,increase [69] 1200,fold [69] data,shows [69] abnormalities,1200 Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G4:
Top Replied-To in G7:
Top Replied-To in G8:
Top Replied-To in G9:
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: