The graph represents a network of 367 Twitter users whose tweets in the requested range contained "SARS-NCOV", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Sunday, 11 December 2022 at 11:14 UTC.
The requested start date was Sunday, 11 December 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 5-day, 8-hour, 56-minute period from Sunday, 27 November 2022 at 02:45 UTC to Friday, 02 December 2022 at 11:41 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 : 367
Unique Edges : 193
Edges With Duplicates : 599
Total Edges : 792
Number of Edge Types : 5
Tweet : 64
Retweet : 289
MentionsInRetweet : 312
Replies to : 51
Mentions : 76
Self-Loops : 68
Reciprocated Vertex Pair Ratio : 0.0133779264214047
Reciprocated Edge Ratio : 0.0264026402640264
Connected Components : 95
Single-Vertex Connected Components : 34
Maximum Vertices in a Connected Component : 112
Maximum Edges in a Connected Component : 498
Maximum Geodesic Distance (Diameter) : 4
Average Geodesic Distance : 1.908592
Graph Density : 0.00225577343994282
Modularity : 0.387447
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 367 Twitter users whose tweets in the requested range contained "SARS-NCOV", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Sunday, 11 December 2022 at 11:14 UTC.
The requested start date was Sunday, 11 December 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 5-day, 8-hour, 56-minute period from Sunday, 27 November 2022 at 02:45 UTC to Friday, 02 December 2022 at 11:41 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 : SARS-NCOV
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:
[252] casos,nuevos [252] diario,#covid_19 [252] fallecidos,registrados [252] casos,activos [252] informe,diario [246] ministeriosalud,informe [156] registrados,62 [57] 28,noviembre [57] 11,150 [57] #covid_19,28 Top Word Pairs in Tweet in G1:
[252] diario,#covid_19 [252] informe,diario [252] casos,activos [252] fallecidos,registrados [252] casos,nuevos [246] ministeriosalud,informe [156] registrados,62 [57] 28,noviembre [57] #covid_19,28 [57] nuevos,11 Top Word Pairs in Tweet in G2:
[15] spike,protein [15] micro,clotting [14] associated,systemic [14] protein,induced [14] ncov,associated [14] sars,ncov [14] induced,hemolysis [14] hemolysis,resulting [14] due,spike [14] amyloid,plaque Top Word Pairs in Tweet in G4:
[10] 重症化予防効果には影響がないと予測されている,2022c [10] また,治療薬やワクチンの有効性について [10] 疫学的な評価はされていない,今後の国内外での検出状況 [10] 2022c,また [10] 今後の国内外での検出状況,感染者数や重症者数の推移を注視する必要がある [10] 治療薬やワクチンの有効性について,疫学的な評価はされていない [10] 示唆されているが,重症化予防効果には影響がないと予測されている [9] c45425,示唆されているが Top Word Pairs in Tweet in G5:
[2] emilyakopp,emanymton90 [2] rebecca21951651,hl3133 [2] r_h_ebright,katherineeban [2] tomselliott,emilyakopp [2] hl3133,tomselliott [2] emanymton90,r_h_ebright [2] katherineeban,project [2] defuse,daszak [2] daszak,notes [2] project,defuse Top Word Pairs in Tweet in G6:
[3] dr,jessica [3] emwresearch,kylefarq [3] jessica,rose [3] rose,emwresearch [3] empireinwinter,finleyc01827804 [3] sundawg31,esme_saysno [3] p_sapergia,empireinwinter [3] esme_saysno,p_sapergia [3] kylefarq,sundawg31 [2] hclarke2022,dr Top Word Pairs in Tweet in G9:
[6] riddle,sars [6] studied,biosafety [6] sars,cov [6] level,laboratory [6] biosafety,level [6] ok,kids [6] cov,studied [6] laboratory,ok [5] kids,contr [5] youarelobbylud,riddle Top Word Pairs in Tweet in G10:
[3] prion,misfolding [3] given,unique [3] unique,never [3] seen,before [3] appears,prion [3] nature,appears [3] jplatte11,drjamesolsson [3] never,seen [3] before,nature [3] drjamesolsson,given Top Replied-To in Entire Graph:
Top Replied-To in G3:
Top Replied-To in G5:
Top Replied-To in G7:
Top Replied-To in G8:
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: