The graph represents a network of 5,044 Twitter users whose recent tweets contained "sdoh", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 1/14/2023 5:00:35 PM. The network was obtained from Twitter on Sunday, 15 January 2023 at 06:55 UTC.
The tweets in the network were tweeted over the 1910-day, 10-hour, 53-minute period from Sunday, 22 October 2017 at 14:02 UTC to Sunday, 15 January 2023 at 00:56 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
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 : 5044
Unique Edges : 4208
Edges With Duplicates : 8359
Total Edges : 12567
Number of Edge Types : 9
Retweet : 2484
MentionsInRetweet : 4064
Replies to : 818
MentionsInReplyTo : 1554
Mentions : 1786
Quote : 225
Tweet : 1285
MentionsInQuote : 262
MentionsInQuoteReply : 89
Self-Loops : 1954
Reciprocated Vertex Pair Ratio : 0.0594741904456557
Reciprocated Edge Ratio : 0.112271145407777
Connected Components : 756
Single-Vertex Connected Components : 377
Maximum Vertices in a Connected Component : 3097
Maximum Edges in a Connected Component : 8741
Maximum Geodesic Distance (Diameter) : 21
Average Geodesic Distance : 7.37494
Graph Density : 0.000259819477945655
Modularity : 0.508634
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 5,044 Twitter users whose recent tweets contained "sdoh", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 1/14/2023 5:00:35 PM. The network was obtained from Twitter on Sunday, 15 January 2023 at 06:55 UTC.
The tweets in the network were tweeted over the 1910-day, 10-hour, 53-minute period from Sunday, 22 October 2017 at 14:02 UTC to Sunday, 15 January 2023 at 00:56 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch2
Graph Term : sdoh
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:
[641] determinants,health [563] social,determinants [390] health,equity [176] learn,more [125] equity,network [112] health,sdoh [106] #healthequity,#sdoh [99] health,#sdoh [93] #sdoh,#healthequity [89] sdoh,data Top Word Pairs in Tweet in G1:
[64] social,determinants [61] determinants,health [46] prior,authorization [45] health,equity [39] authorization,rationing [38] codes,document [37] delayed,changed [35] due,insurer [35] abandoned,care [35] changed,abandoned Top Word Pairs in Tweet in G2:
[119] determinants,health [118] social,determinants [39] health,sdoh [37] health,equity [34] sdoh,data [27] health,#sdoh [26] bring,progress [26] 2023,bring [23] progress,sdoh [23] tech,telehealth Top Word Pairs in Tweet in G3:
[54] determinants,health [36] social,determinants [23] health,equity [21] show,matters [21] frame,discussions [21] health,show [21] healthfdn,frame [21] fantastic,resource [21] resource,healthfdn [21] discussions,social Top Word Pairs in Tweet in G4:
[22] black,women [21] affected,#cvd [21] disproportionately,affected [20] looking,forward [20] cv,mortality [19] take,achieve [19] mortality,take [19] #cvd,face [19] higher,cv [19] women,disproportionately Top Word Pairs in Tweet in G5:
[33] social,determinants [33] determinants,health [23] #digitalhealth,#web3 [23] #ehealth,#finserv [23] #cx,#ehealth [23] #healthtech,#smartcity [23] #csuite,#digitalhealth [23] #datascientist,#csuite [23] #web3,#cx [23] #smartcity,#datascientist Top Word Pairs in Tweet in G6:
[180] health,equity [122] equity,network [76] learn,more [50] landg_group,learn [50] network,landg_group [49] maybe,haven't [49] heard,launching [49] launching,interdisciplinary [49] interdisciplinary,health [49] haven't,heard Top Word Pairs in Tweet in G7:
[18] health,equity [16] #pdoh,#sdoh [10] based,inequities [10] responding,place [10] read,more [10] health,care [10] one,way [10] zones,read [10] equity,improvement [10] improvement,zones Top Word Pairs in Tweet in G8:
[33] view,health [33] endeavour,wencyleung [33] collective,endeavour [33] personal,matter [33] exclusively,personal [33] matter,collective [33] health,exclusively [30] wencyleung,globeandma [30] picardonhealth,view [19] homeless,people Top Word Pairs in Tweet in G9:
[34] people,live [34] food,kids [34] enough,food [34] mental,illness [34] tents,families [34] hungry,people [34] live,tents [34] go,school [34] families,enough [34] people,suffer Top Word Pairs in Tweet in G10:
[13] determinants,health [9] social,determinants [8] bps,factors [7] daily,thanks [7] vmb's,population [7] latest,vmb's [7] health,daily [7] population,health [5] estimates,rules [5] limits,harmful Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: