The graph represents a network of 8,260 Twitter users whose tweets in the requested range contained "NCoV", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 25 September 2020 at 08:46 UTC.
The requested start date was Friday, 25 September 2020 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 3-day, 1-hour, 16-minute period from Monday, 21 September 2020 at 22:44 UTC to Friday, 25 September 2020 at 00:00 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 : 8260
Unique Edges : 2666
Edges With Duplicates : 13251
Total Edges : 15917
Number of Edge Types : 5
Retweet : 6257
MentionsInRetweet : 6954
Tweet : 928
Mentions : 1287
Replies to : 491
Self-Loops : 947
Reciprocated Vertex Pair Ratio : 0.00228585178055823
Reciprocated Edge Ratio : 0.00456127715760413
Connected Components : 810
Single-Vertex Connected Components : 334
Maximum Vertices in a Connected Component : 4534
Maximum Edges in a Connected Component : 9741
Maximum Geodesic Distance (Diameter) : 18
Average Geodesic Distance : 4.697731
Graph Density : 0.000122120794484379
Modularity : 0.510775
NodeXL Version : 1.0.1.440
Data Import : The graph represents a network of 8,260 Twitter users whose tweets in the requested range contained "NCoV", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 25 September 2020 at 08:46 UTC.
The requested start date was Friday, 25 September 2020 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 3-day, 1-hour, 16-minute period from Monday, 21 September 2020 at 22:44 UTC to Friday, 25 September 2020 at 00:00 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 : 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:
[2730] survival,rates [2693] updated,survival [2641] 20,49 [2474] 99,997 [2467] 997,20 [2463] 19,99 [2433] rates,infected [2421] last,week [2411] week,updated [2402] govt,last Top Word Pairs in Tweet in G1:
[2272] govt,last [2272] last,week [2272] week,updated [2272] updated,survival [2272] survival,rates [2266] rates,infected [2266] infected,covid19 [2266] covid19,19 [2265] 19,99 [2265] 99,997 Top Word Pairs in Tweet in G2:
[633] cdc,declared [633] declared,federal [633] federal,ban [633] ban,evictions [633] evictions,prevent [633] prevent,evictions [633] evictions,tenants [633] tenants,sign [633] sign,present [633] present,following Top Word Pairs in Tweet in G3:
[182] covid,19 [78] slow,spread [76] wash,hands [67] stay,feet [63] extremadamente,importante [63] importante,cdc [63] cdc,usa [63] usa,acaba [63] acaba,reconocer [63] reconocer,transmisión Top Word Pairs in Tweet in G4:
[190] covid,cases [190] cases,increase [122] 2019,ncov [103] covid,19 [96] recombinomics,inc [95] ncov,recombinomics [15] protect,yourself [14] learn,more [13] trick,treating [12] dakota,covid Top Word Pairs in Tweet in G5:
[277] updated,survival [277] survival,rates [270] updated,estimated [270] fatality,rates [267] cdc,recently [267] recently,updated [267] estimated,infection [267] infection,fatality [267] rates,covid [267] covid,updated Top Word Pairs in Tweet in G6:
[240] 2019,ncov [237] recomendaciones,población [237] población,acerca [237] acerca,coronavirus [237] coronavirus,2019 [231] ncov,organización [231] organización,mundial [231] mundial,salud [229] somos_ejercito,recomendaciones [18] salud,wh Top Word Pairs in Tweet in G7:
[154] infection,fatality [154] 20,49 [152] 19,years [152] years,003 [152] 003,20 [152] 49,years [152] years,02 [152] 02,50 [152] 50,69 [110] age,group Top Word Pairs in Tweet in G8:
[161] south,dakota [161] dakota,purple [161] purple,usa [161] usa,gray [161] gray,source [161] source,cdc [160] maddow,south [3] 20,49 [3] 50,69 [2] dotcomcto,maddow Top Word Pairs in Tweet in G9:
[87] cdcによる,covid [87] covid,19の広がり方 [87] 19の広がり方,汚染された物を触って [87] 汚染された物を触って,その手で自分の目 [87] その手で自分の目,口 [87] 口,鼻を触るというのは主な感染ルートではなく [87] 鼻を触るというのは主な感染ルートではなく,dropletやaerosolが直接 [87] dropletやaerosolが直接,鼻 [87] 鼻,口 [87] 口,気道につくのが多い Top Word Pairs in Tweet in G10:
[64] datos,#covid19 [61] #covid19,españa [35] padecer,dolencia [35] dolencia,crónica [35] crónica,aumentar [35] aumentar,riesgo [35] riesgo,caso [35] caso,contagio [35] contagio,#covid19 [35] #covid19,personas Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
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: