The graph represents a network of 544 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 Thursday, 08 September 2022 at 11:06 UTC.
The requested start date was Thursday, 08 September 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, 9-hour, 53-minute period from Thursday, 25 August 2022 at 02:36 UTC to Wednesday, 07 September 2022 at 12:29 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 : 544
Unique Edges : 255
Edges With Duplicates : 1226
Total Edges : 1481
Number of Edge Types : 5
Tweet : 75
Replies to : 75
Retweet : 591
MentionsInRetweet : 597
Mentions : 143
Self-Loops : 80
Reciprocated Vertex Pair Ratio : 0.00220264317180617
Reciprocated Edge Ratio : 0.0043956043956044
Connected Components : 102
Single-Vertex Connected Components : 34
Maximum Vertices in a Connected Component : 190
Maximum Edges in a Connected Component : 1087
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 2.143017
Graph Density : 0.00154032607518145
Modularity : 0.306651
NodeXL Version : 1.0.1.504
Data Import : The graph represents a network of 544 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 Thursday, 08 September 2022 at 11:06 UTC.
The requested start date was Thursday, 08 September 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, 9-hour, 53-minute period from Thursday, 25 August 2022 at 02:36 UTC to Wednesday, 07 September 2022 at 12:29 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:
[550] informe,diario [550] diario,#covid_19 [550] casos,nuevos [550] casos,activos [550] fallecidos,registrados [527] ministeriosalud,informe [251] #covid_19,septiembre [163] nuevos,33 [138] nuevos,24 [127] activos,fallecidos Top Word Pairs in Tweet in G1:
[535] informe,diario [535] diario,#covid_19 [535] casos,nuevos [535] casos,activos [535] fallecidos,registrados [525] ministeriosalud,informe [243] #covid_19,septiembre [161] nuevos,33 [130] nuevos,24 [127] activos,fallecidos Top Word Pairs in Tweet in G2:
[23] sars,cov [13] sars,ncov [10] covid,19 [8] scholars,portal [6] paper,published [6] published,2017 [6] 2017,provides [6] provides,compelling [6] compelling,evidence [6] evidence,sars Top Word Pairs in Tweet in G4:
[14] summary,cdc [14] cdc,documents [14] documents,studies [14] studies,more [13] dgurdasani1,summary [4] cultures,#sarscov2 [4] #sarscov2,handled [4] handled,#biosafety [4] #biosafety,level [4] level,#bsl Top Word Pairs in Tweet in G6:
[2] elizavetaka,try [2] cdc,summarizes [2] masks,work [2] read,more Top Word Pairs in Tweet in G7:
[6] sars,ncov [2] ncov,olympic [2] olympic,sports [2] sports,team [2] team,conquered [2] conquered,world [2] world,took [2] took,home [2] home,championship [2] championship,last Top Word Pairs in Tweet in G8:
[2] stohr_klaus,welt [2] welt,große [2] große,studie [2] studie,cdc [2] cdc,die [2] die,sicher [2] sicher,kennen [2] kennen,scrollen [2] scrollen,runter [2] runter,gibts Top Word Pairs in Tweet in G9:
[2] 国立感染研の研究では無症状者であっても感染性のあるウイルスの排出は診断7日目までは見られている,有症状者に比べると少ないとは言え [2] 有症状者に比べると少ないとは言え,無視していい数字なのか [2] ba,japan [2] japan,multiple [2] multiple,nucleotide [2] nucleotide,reversions [2] reversions,root [2] root,including [2] including,t9i [2] t9i,t9t Top Word Pairs in Tweet in G10:
[15] informe,diario [15] diario,#covid_19 [15] casos,nuevos [15] casos,activos [15] fallecidos,registrados [13] registrados,60 [10] natho47,informe [8] #covid_19,septiembre [8] nuevos,24 [5] septiembre,639 Top Replied-To in Entire Graph:
Top Replied-To in G3:
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Top Replied-To in G5:
Top Replied-To in G6:
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Top Replied-To in G8:
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:
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Top Tweeters in G5:
Top Tweeters in G6:
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Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: