The graph represents a network of 4,665 Twitter users whose recent tweets contained "@CDCgov OR @CDC_eHealth OR @CDCemergency", 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 12/29/2022 5:00:32 PM. The network was obtained from Twitter on Friday, 30 December 2022 at 20:57 UTC.
The tweets in the network were tweeted over the 1742-day, 0-hour, 22-minute period from Saturday, 24 March 2018 at 00:37 UTC to Friday, 30 December 2022 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 : 4665
Unique Edges : 5916
Edges With Duplicates : 14356
Total Edges : 20272
Number of Edge Types : 9
Retweet : 2409
MentionsInRetweet : 6365
Replies to : 2657
MentionsInReplyTo : 7094
Tweet : 156
Mentions : 616
MentionsInQuote : 578
Quote : 193
MentionsInQuoteReply : 204
Self-Loops : 428
Reciprocated Vertex Pair Ratio : 0.0139612807148176
Reciprocated Edge Ratio : 0.02753809436387
Connected Components : 1
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 4665
Maximum Edges in a Connected Component : 20272
Maximum Geodesic Distance (Diameter) : 7
Average Geodesic Distance : 2.53288
Graph Density : 0.000500699526969017
Modularity : 0.365987
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 4,665 Twitter users whose recent tweets contained "@CDCgov OR @CDC_eHealth OR @CDCemergency", 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 12/29/2022 5:00:32 PM. The network was obtained from Twitter on Friday, 30 December 2022 at 20:57 UTC.
The tweets in the network were tweeted over the 1742-day, 0-hour, 22-minute period from Saturday, 24 March 2018 at 00:37 UTC to Friday, 30 December 2022 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 : @CDCgov OR @CDC_eHealth OR @CDCemergency
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:
[690] whitehouse,cdcgov [539] cdcgov,know [530] more,effective [526] covid,spread [525] effective,policy [525] hey,whitehouse [525] slowing,covid [525] know,more [525] spread,travel [525] policy,slowing Top Word Pairs in Tweet in G1:
[200] cdcgov,cdcmmwr [172] cdcgov,flu [163] prevent,infection [159] reduce,risk [159] flu,vaccination [158] always,prevent [158] less,severe [157] symptoms,less [157] vaccination,always [157] make,symptoms Top Word Pairs in Tweet in G2:
[411] cdcgov,cdcdirector [240] cdcdirector,day [240] day,11 [239] ton,sars [239] sars,cov [239] still,producing [239] producing,ton [239] cov,protein [239] symptom,onset [239] hi,cdcgov Top Word Pairs in Tweet in G3:
[665] whitehouse,cdcgov [522] cdcgov,know [521] policy,slowing [521] hey,whitehouse [521] covid,spread [521] know,more [521] slowing,covid [521] effective,policy [521] spread,travel [521] more,effective Top Word Pairs in Tweet in G4:
[306] cdcgov,us_fda [300] nih,cdcgov [215] cleveland,clinic [214] clinic,study [213] study,bivalent [213] us_fda,acknowledge [213] bivalent,boosters [213] acknowledge,cleveland [213] wonder,nih [212] senronjohnson,wonder Top Word Pairs in Tweet in G5:
[177] lzj961,peoplescdc [113] member,reductionist [113] red,baiting [113] question,emmaogreen [113] nonsense,question [113] baiting,nonsense [113] peoplescdc,member [113] reductionist,red [113] emmaogreen,fringe [77] emmaogreen,cdcgov Top Word Pairs in Tweet in G6:
[29] x08714617,sethpedigo [25] bertkreischer,billburr [24] billburr,boringcompany [22] tomsegura,alexa99 [22] bretweinstein,cdcgov [21] berryrazi,bertkreischer [21] 50cent,benshapiro [21] boringcompany,tesla [21] sethpedigo,tomsegura [21] benshapiro,berryrazi Top Word Pairs in Tweet in G7:
[79] karl_lauterbach,bmg_bund [78] cdcgov,karl_lauterbach [55] dokhollidays,cdcgov [47] mrna,booster [47] altersgruppe,65 [47] daten,cdcgov [47] bivalente,mrna [47] breaking,neue [47] cdcgov,zeigt [47] neue,daten Top Word Pairs in Tweet in G8:
[77] education,parents [77] public,education [77] cking,bs [77] administration,place [77] biden,administration [77] bs,biden [77] more,cking [77] absolutely,more [77] place,public [76] parents,dis Top Word Pairs in Tweet in G9:
[12] single,adult [11] fema,cdcgov [10] repmaxinewaters,fema [10] nysdos,repmaxinewaters [10] newyorkstateag,nysdos [10] cdcgov,hudgov [10] #congregate,single [9] yale,scholars [9] hudgov,usichgov [9] pathological,leader Top Word Pairs in Tweet in G10:
[5] cdcdirector,cdc_ehealth [5] cdcgov,cdcdirector [3] bensalem_owen,epilepsy_center [3] epilepsyc,epilepsyfdn [3] epilepsy_center,epilepsyc [3] cdc_ehealth,10tv [3] foxnews,amepilepsysoc [3] amepilepsysoc,cdcgov [2] epilepsyfdn,brainablaze [2] silent,types Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
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: