The graph represents a network of 9,706 Twitter users whose tweets in the requested range contained "public health", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 26 September 2020 at 12:42 UTC.
The requested start date was Saturday, 26 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 2-day, 0-hour, 50-minute period from Wednesday, 23 September 2020 at 07:03 UTC to Friday, 25 September 2020 at 07:53 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 : 9706
Unique Edges : 5572
Edges With Duplicates : 12634
Total Edges : 18206
Number of Edge Types : 5
Mentions : 2038
Retweet : 6013
MentionsInRetweet : 7950
Replies to : 793
Tweet : 1412
Self-Loops : 1437
Reciprocated Vertex Pair Ratio : 0.00661489790048893
Reciprocated Edge Ratio : 0.0131428571428571
Connected Components : 1624
Single-Vertex Connected Components : 445
Maximum Vertices in a Connected Component : 4292
Maximum Edges in a Connected Component : 10142
Maximum Geodesic Distance (Diameter) : 32
Average Geodesic Distance : 9.50255
Graph Density : 0.000111468837612516
Modularity : 0.585894
NodeXL Version : 1.0.1.440
Data Import : The graph represents a network of 9,706 Twitter users whose tweets in the requested range contained "public health", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 26 September 2020 at 12:42 UTC.
The requested start date was Saturday, 26 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 2-day, 0-hour, 50-minute period from Wednesday, 23 September 2020 at 07:03 UTC to Friday, 25 September 2020 at 07:53 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 : public health
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:
[5188] public,health [467] covid,19 [304] health,crisis [291] test,trace [281] health,problem [273] solve,economic [271] solve,public [265] re,going [264] going,solve [264] economic,problems Top Word Pairs in Tweet in G1:
[730] public,health [261] solve,economic [254] solve,public [254] health,problem [252] going,solve [252] economic,problems [251] unless,solve [251] problem,re [251] re,going [170] test,trace Top Word Pairs in Tweet in G2:
[351] public,health [73] covid,19 [31] mental,health [19] health,officials [16] health,measures [14] health,england [11] health,crisis [8] social,distancing [8] 19,vaccine [8] health,care Top Word Pairs in Tweet in G3:
[103] public,health [97] lessons,easing [97] easing,lockdowns [97] lockdowns,matters [97] matters,trust [97] trust,clear [97] clear,communication [97] communication,active [97] active,case [97] case,finding Top Word Pairs in Tweet in G4:
[245] public,health [240] health,majors [240] majors,saying [240] saying,shouldn [240] shouldn,universal [240] universal,healthcare [240] healthcare,doctors [240] doctors,paid [240] paid,less [239] roygaybiv,public Top Word Pairs in Tweet in G5:
[128] public,health [100] health,agency [96] sweden's,public [96] agency,discussing [96] discussing,imposing [96] imposing,coronavirus [96] coronavirus,restrictions [94] sweden,herd [94] herd,nope [94] nope,sorry Top Word Pairs in Tweet in G6:
[101] public,health [25] test,trace [19] vital,public [19] wrap,brain [19] brain,around [19] around,msp's [19] msp's,paid [19] paid,regardless [19] regardless,whether [19] whether,parliament Top Word Pairs in Tweet in G7:
[68] public,health [41] govt,used [41] used,behavioural [41] behavioural,psychologists [41] psychologists,mount [41] mount,assault [41] assault,mental [41] mental,health [41] health,criminal [41] criminal,act Top Word Pairs in Tweet in G8:
[97] public,health [14] health,funding [13] uk,government [13] government,show [12] work,centre [12] centre,health [12] health,economics [12] economics,york [12] york,shown [12] shown,spending Top Word Pairs in Tweet in G9:
[120] many,lives [120] lives,lost [120] lost,lost [120] lost,thanks [120] thanks,political [120] political,suppression [120] suppression,#hydroxychloroquine [120] #hydroxychloroquine,mostly [119] tomfitton,many [119] mostly,unde Top Word Pairs in Tweet in G10:
[66] public,health [38] drphilhammond,life [38] life,near [38] near,munich [38] munich,very [38] very,near [38] near,normal [38] normal,masks [38] masks,inside [38] inside,buildings Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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