The graph represents a network of 9,711 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, 20 November 2021 at 12:39 UTC.
The requested start date was Saturday, 20 November 2021 at 01:01 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, 1-hour, 26-minute period from Wednesday, 17 November 2021 at 09:40 UTC to Friday, 19 November 2021 at 11:07 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 : 9711
Unique Edges : 5284
Edges With Duplicates : 12325
Total Edges : 17609
Number of Edge Types : 5
Retweet : 5833
MentionsInRetweet : 7496
Tweet : 1446
Mentions : 2035
Replies to : 799
Self-Loops : 1480
Reciprocated Vertex Pair Ratio : 0.00962512664640324
Reciprocated Edge Ratio : 0.0190667335674862
Connected Components : 1717
Single-Vertex Connected Components : 490
Maximum Vertices in a Connected Component : 4337
Maximum Edges in a Connected Component : 9542
Maximum Geodesic Distance (Diameter) : 24
Average Geodesic Distance : 7.326548
Graph Density : 0.00010568031984284
Modularity : 0.583113
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 9,711 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, 20 November 2021 at 12:39 UTC.
The requested start date was Saturday, 20 November 2021 at 01:01 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, 1-hour, 26-minute period from Wednesday, 17 November 2021 at 09:40 UTC to Friday, 19 November 2021 at 11:07 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:
[4903] public,health [1202] mask,wearing [1086] effective,public [1052] single,effective [1050] wearing,single [790] health,measure [592] well,well [576] doctors,nurses [575] pandemic,desperately [575] desperately,hire Top Word Pairs in Tweet in G1:
[565] pandemic,desperately [565] desperately,hire [565] hire,many [565] many,doctors [565] doctors,nurses [565] nurses,certainly [565] certainly,fire [564] drelidavid,pandemic [15] public,health [7] remember,dr Top Word Pairs in Tweet in G2:
[394] public,health [69] covid,19 [27] health,measures [21] mental,health [18] reducing,incidence [15] health,crisis [15] mask,wearing [14] health,measure [13] effective,public [12] health,care Top Word Pairs in Tweet in G3:
[270] public,health [178] mask,wearing [178] effective,public [176] wearing,single [176] single,effective [174] health,measure [171] measure,tackling [171] tackling,covid [168] covid,reducing [168] reducing,incidence Top Word Pairs in Tweet in G4:
[552] well,well [313] public,health [290] mask,wearing [285] wearing,single [285] single,effective [285] effective,public [276] well,looks [276] looks,wearing [276] wearing,masks [276] masks,doesn Top Word Pairs in Tweet in G5:
[224] public,health [123] mask,wearing [122] health,measures [79] systematic,review [76] bmj_latest,systematic [76] review,72 [76] 72,studies [76] studies,public [76] measures,vs [76] vs,covid Top Word Pairs in Tweet in G6:
[205] public,health [132] health,measures [109] sympathising,anti [109] anti,vaxxer [109] vaxxer,nazis [109] nazis,opposing [109] opposing,public [109] measures,saved [109] saved,thousands [109] thousands,australian Top Word Pairs in Tweet in G7:
[222] public,health [196] mask,wearing [196] effective,public [195] wearing,single [195] single,effective [194] health,measure [191] case,didn [191] didn,already [191] already,know [191] know,masks Top Word Pairs in Tweet in G8:
[78] public,health [17] best,friend [17] friend,quit [17] quit,nursing [17] nursing,phenomenal [17] phenomenal,nurse [17] nurse,masters [17] masters,degree [17] degree,huge [17] huge,loss Top Word Pairs in Tweet in G9:
[119] public,health [57] health,advice [56] feel,bbc [56] bbc,damaged [56] damaged,scottish [56] scottish,govt [56] govt,public [56] advice,political [56] political,reasons [56] reasons,genuinely Top Word Pairs in Tweet in G10:
[108] health,secretary [106] secretary,answers [106] answers,valid [106] valid,question [106] question,public [106] public,know [106] know,time [106] time,gone [105] penelopemkz,health [105] gone,sa Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: