The graph represents a network of 258 Twitter users whose recent tweets were included in a list (Tweet ID List - cdcgov - reconstructed) of 3200 tweet IDs, or who were replied to or mentioned in those tweets. 3200 out of 3200 tweets were collected. The network was obtained from Twitter on Wednesday, 31 March 2021 at 15:55 UTC.
The tweets in the network were tweeted over the 328-day, 0-hour, 37-minute period from Wednesday, 06 May 2020 at 20:28 UTC to Tuesday, 30 March 2021 at 21:05 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 : 258
Unique Edges : 309
Edges With Duplicates : 4353
Total Edges : 4662
Self-Loops : 2549
Reciprocated Vertex Pair Ratio : 0.0793269230769231
Reciprocated Edge Ratio : 0.146993318485523
Connected Components : 1
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 258
Maximum Edges in a Connected Component : 4662
Maximum Geodesic Distance (Diameter) : 2
Average Geodesic Distance : 1.979749
Graph Density : 0.00677163454287696
Modularity : 0.060995
NodeXL Version : 1.0.1.444
Data Import : The graph represents a network of 258 Twitter users whose recent tweets were included in a list (Tweet ID List - cdcgov - reconstructed) of 3200 tweet IDs, or who were replied to or mentioned in those tweets. 3200 out of 3200 tweets were collected. The network was obtained from Twitter on Wednesday, 31 March 2021 at 15:55 UTC.
The tweets in the network were tweeted over the 328-day, 0-hour, 37-minute period from Wednesday, 06 May 2020 at 20:28 UTC to Tuesday, 30 March 2021 at 21:05 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 : TwitterIDList
Graph Term : Tweet ID List - cdcgov - reconstructed
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 : Followers
Vertex Alpha : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[1158] learn,more [658] covid,19 [281] spread,#covid19 [253] slow,spread [233] cdc,s [233] protect,yourself [210] wash,hands [184] during,#covid19 [182] 6,feet [174] stay,6 Top Word Pairs in Tweet in G1:
[953] learn,more [592] covid,19 [219] spread,#covid19 [216] slow,spread [211] cdc,s [185] protect,yourself [183] wash,hands [167] 6,feet [164] stay,6 [143] u,s Top Word Pairs in Tweet in G2:
[42] learn,more [23] spread,#covid19 [19] loved,ones [18] mental,health [17] check,out [15] during,#covid19 [15] covid,19 [15] face,covering [14] prevent,spread [13] make,sure Top Word Pairs in Tweet in G3:
[24] learn,more [19] covid,19 [16] slow,spread [14] spread,#covid19 [13] social,distancing [12] public,health [10] #covid19,pandemic [10] wash,hands [7] against,#covid19 [7] hands,frequently Top Word Pairs in Tweet in G4:
[9] learn,more [5] covid,19 [4] healthcare,workers [4] workers,join [4] join,cdcgov [4] thursday,8am [4] 8am,edt [4] edt,latest [4] latest,#covid19 [4] #covid19,infection Top Word Pairs in Tweet in G5:
[30] learn,more [8] more,#vetoviolence [5] older,adults [5] help,prevent [4] loved,ones [4] violence,learn [3] more,#rxawareness [3] loved,one [3] youth,violence [3] young,people Top Word Pairs in Tweet in G6:
[41] learn,more [12] spread,#covid19 [11] flu,season [11] flu,vaccine [10] protect,yourself [9] during,#covid19 [9] cloth,face [9] face,covering [9] more,#prepyourhealth [9] flu,activity Top Word Pairs in Tweet in G7:
[37] learn,more [18] protect,yourself [12] carbon,monoxide [11] stay,safe [10] important,information [10] hand,sanitizer [9] cdc,s [8] through,flooded [8] don,t [8] website,important Top Word Pairs in Tweet in G8:
[13] learn,more [9] spread,#covid19 [8] covid,19 [7] slow,spread [7] more,cdcgov [6] help,prevent [6] prevent,spread [5] help,protect [5] protect,yourself [5] during,#covid19 Top Word Pairs in Tweet in G10:
[8] learn,more [3] #hiv,testing [3] prevention,treatment [3] epidemic,initiative [3] awareness,day [3] share,resources [3] prevention,care [3] affected,#covid19 [3] covid,19 [3] ending,#hiv Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
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: