The graph represents a network of 10,199 Twitter users whose recent tweets contained "#publichealth", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Saturday, 17 April 2021 at 19:09 UTC.
The tweets in the network were tweeted over the 8-day, 4-hour, 21-minute period from Friday, 09 April 2021 at 13:36 UTC to Saturday, 17 April 2021 at 17:57 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 : 10199
Unique Edges : 17586
Edges With Duplicates : 5474
Total Edges : 23060
Number of Edge Types : 5
Retweet : 6793
MentionsInRetweet : 8313
Tweet : 2853
Mentions : 4480
Replies to : 621
Self-Loops : 3076
Reciprocated Vertex Pair Ratio : 0.0281509916826615
Reciprocated Edge Ratio : 0.0547604231487243
Connected Components : 1321
Single-Vertex Connected Components : 628
Maximum Vertices in a Connected Component : 6989
Maximum Edges in a Connected Component : 18956
Maximum Geodesic Distance (Diameter) : 15
Average Geodesic Distance : 4.727244
Graph Density : 0.000169955789189135
Modularity : 0.703929
NodeXL Version : 1.0.1.445
Data Import : The graph represents a network of 10,199 Twitter users whose recent tweets contained "#publichealth", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Saturday, 17 April 2021 at 19:09 UTC.
The tweets in the network were tweeted over the 8-day, 4-hour, 21-minute period from Friday, 09 April 2021 at 13:36 UTC to Saturday, 17 April 2021 at 17:57 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 : TwitterSearch
Graph Term : #publichealth
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:
[1238] public,health [776] covid,19 [382] learn,more [260] #publichealth,#covid19 [242] stay,home [239] 19,vaccine [216] #covid19,#publichealth [196] #publichealth,measures [190] health,care [165] mental,health Top Word Pairs in Tweet in G1:
[384] public,health [176] covid,19 [92] learn,more [84] mental,health [66] #publichealth,#gis [66] #gis,#maps [66] #maps,#publichealthmaps [62] #covid19,#publichealth [60] #publichealth,issue [53] building,#covid19 Top Word Pairs in Tweet in G2:
[100] public,health [41] covid,19 [25] #publichealth,#covid19 [23] health,week [21] take,action [20] #publichealth,promote [19] building,#covid19 [19] #covid19,resilience [19] resilience,key [19] key,moving Top Word Pairs in Tweet in G3:
[35] #journalism,#publichealth [33] bill,gates [33] gates,vaccine [33] vaccine,monster [33] monster,republic [33] republic,excellent [33] excellent,investigative [33] investigative,piece [33] piece,#journalism [22] public,health Top Word Pairs in Tweet in G4:
[58] health,wellbeing [55] poor,health [55] health,necessarily [55] necessarily,result [55] result,bad [55] bad,choices [55] choices,people [55] people,take [55] take,responsibility [55] responsibility,control Top Word Pairs in Tweet in G5:
[34] #publichealth,measures [29] premier,fordnation [28] chhrn,chamberlandrowe [28] chamberlandrowe,lindsaykhedden [28] lindsaykhedden,drkateleslie [28] drkateleslie,gayle_halas [28] gayle_halas,bukolaksalami [28] bukolaksalami,danyaalraza [28] danyaalraza,mwaltonroberts [28] mwaltonroberts,denniskendel Top Word Pairs in Tweet in G6:
[25] public,health [23] healthcare,delivery [23] delivery,organizations [21] #nationalpublichealthweek,re [18] re,celebrating [18] #publichealth,work [17] covid,19 [14] learn,more [13] released,three [13] three,resources Top Word Pairs in Tweet in G7:
[208] stay,home [114] learn,more [106] #publichealth,measures [105] health,care [104] home,order [104] order,currently [104] currently,effect [104] effect,ontario [104] ontario,leave [104] leave,home Top Word Pairs in Tweet in G8:
[112] #publichealth,india [112] #covidemergency,safe [107] india,ashamed [107] ashamed,common [107] common,citizens [107] citizens,words [107] words,tip [107] tip,iceberg [107] iceberg,#covidemergency [19] #covidemergency,#publichealth Top Word Pairs in Tweet in G9:
[35] #publichealth,#covid19 [19] roll,sleeves [19] sleeves,campaign [19] campaign,encourages [19] encourages,people [19] people,vaccinated [19] vaccinated,help [19] help,address [19] address,inequities [19] inequities,vaccine Top Word Pairs in Tweet in G10:
[82] #drinkingwater,wastewater [82] wastewater,#infrastructure [81] protect,#greatlakes [64] support,robust [64] robust,federal [59] confront,#wateraffordability [59] #wateraffordability,crisis [50] federal,investment [42] #greatlakes,#publichealth [41] over,next Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G6:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G3:
Top Tweeters in G4:
Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
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Top Tweeters in G9:
Top Tweeters in G10: