The graph represents a network of 881 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 Tuesday, 21 June 2022 at 13:45 UTC.
The requested start date was Tuesday, 21 June 2022 at 00:01 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 13-day, 19-hour, 51-minute period from Tuesday, 07 June 2022 at 00:10 UTC to Monday, 20 June 2022 at 20:01 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 : 881
Unique Edges : 537
Edges With Duplicates : 746
Total Edges : 1283
Number of Edge Types : 5
Retweet : 341
MentionsInRetweet : 370
Replies to : 106
Mentions : 386
Tweet : 80
Self-Loops : 85
Reciprocated Vertex Pair Ratio : 0.00359281437125748
Reciprocated Edge Ratio : 0.00715990453460621
Connected Components : 126
Single-Vertex Connected Components : 27
Maximum Vertices in a Connected Component : 112
Maximum Edges in a Connected Component : 223
Maximum Geodesic Distance (Diameter) : 6
Average Geodesic Distance : 1.972462
Graph Density : 0.0010808998039418
Modularity : 0.648148
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 881 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 Tuesday, 21 June 2022 at 13:45 UTC.
The requested start date was Tuesday, 21 June 2022 at 00:01 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 13-day, 19-hour, 51-minute period from Tuesday, 07 June 2022 at 00:10 UTC to Monday, 20 June 2022 at 20:01 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:
[112] informe,diario [112] diario,#covid_19 [112] #covid_19,20 [112] 20,junio [112] junio,149 [112] 149,casos [112] casos,nuevos [112] nuevos,48 [112] 48,730 [112] 730,casos Top Word Pairs in Tweet in G1:
[112] informe,diario [112] diario,#covid_19 [112] #covid_19,20 [112] 20,junio [112] junio,149 [112] 149,casos [112] casos,nuevos [112] nuevos,48 [112] 48,730 [112] 730,casos Top Word Pairs in Tweet in G2:
[77] 神経を壊すよう,プログラムされている [77] プログラムされている,nature [77] nature,新たな発見 [77] 新たな発見,sars [77] sars,ncov [77] ncov,2には [77] 2には,凝集すると強い細胞毒性のあるアミロイドを高速で [77] 凝集すると強い細胞毒性のあるアミロイドを高速で,凝集 [77] 凝集,し [77] し,神経細胞の Top Word Pairs in Tweet in G3:
[2] ic_lib,jeffbernard1 [2] rustyaway,navybrat59 [2] incytometry,sndhsbl [2] sndhsbl,jaisans [2] jaisans,usamriidca [2] usamriidca,debrammason1 [2] debrammason1,guardia56241490 [2] guardia56241490,trumpbangskids [2] trumpbangskids,chrisbbacon3 [2] chrisbbacon3,6lennybravo Top Word Pairs in Tweet in G5:
[28] cdc,evidence [28] evidence,benefits [28] benefits,masks [28] masks,encompassing [28] encompassing,covers [28] covers,lot [28] lot,here's [27] dgurdasani1,cdc [27] here's,mor [6] fatality,rate Top Word Pairs in Tweet in G7:
[37] avusturya,parlamentosu [37] parlamentosu,1950 [37] 1950,tarihli [37] tarihli,epidemi [37] epidemi,kanunu'nda [37] kanunu'nda,bildirim [37] bildirim,mecburiyeti [37] mecburiyeti,olan [37] olan,bulaşıcı [37] bulaşıcı,hastalıkları Top Word Pairs in Tweet in G8:
[30] legalnego,testu [30] testu,który [30] który,dokładnie [30] dokładnie,identyfikowałby [30] identyfikowałby,obecność [30] obecność,sars [30] sars,cov [30] cov,dokumentu [30] dokumentu,ponieważ [30] ponieważ,żadne Top Word Pairs in Tweet in G9:
[25] sars,cov [9] 2019,ncov [5] covid,19 [5] 19,vaccine [5] sars,ncov [4] cov,の変異株について [4] の変異株について,第17報 [4] drml350phd,interesting [4] delta,variant [4] chadox1,ncov Top Replied-To in Entire Graph:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
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: