The graph represents a network of 6,507 Twitter users whose recent tweets contained "healthcare", 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 2/12/2023 5:00:35 PM. The network was obtained from Twitter on Monday, 13 February 2023 at 06:04 UTC.
The tweets in the network were tweeted over the 2028-day, 4-hour, 41-minute period from Tuesday, 25 July 2017 at 20:18 UTC to Monday, 13 February 2023 at 01:00 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 : 6507
Unique Edges : 3079
Edges With Duplicates : 10532
Total Edges : 13611
Number of Edge Types : 9
Retweet : 3533
MentionsInRetweet : 4202
Tweet : 994
Replies to : 1375
MentionsInReplyTo : 2645
MentionsInQuote : 72
Mentions : 602
Quote : 162
MentionsInQuoteReply : 26
Self-Loops : 1284
Reciprocated Vertex Pair Ratio : 0.0268378063010502
Reciprocated Edge Ratio : 0.0522727272727273
Connected Components : 1142
Single-Vertex Connected Components : 319
Maximum Vertices in a Connected Component : 2783
Maximum Edges in a Connected Component : 6871
Maximum Geodesic Distance (Diameter) : 26
Average Geodesic Distance : 10.417128
Graph Density : 0.000166294464695047
Modularity : 0.529005
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 6,507 Twitter users whose recent tweets contained "healthcare", 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 2/12/2023 5:00:35 PM. The network was obtained from Twitter on Monday, 13 February 2023 at 06:04 UTC.
The tweets in the network were tweeted over the 2028-day, 4-hour, 41-minute period from Tuesday, 25 July 2017 at 20:18 UTC to Monday, 13 February 2023 at 01:00 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 : healthcare
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:
[380] healthcare,funding [342] over,west [341] madrid,healthcare [340] show,weeks [340] media,won [340] won,show [340] weeks,flatten [340] west,media [340] collapsing,over [340] healthcare,collapsing Top Word Pairs in Tweet in G1:
[62] public,healthcare [55] healthcare,system [52] private,healthcare [39] healthcare,education [38] attack,greenbelt [38] tax,increases [38] needs,stay [38] ford,attack [38] increases,ford's [38] greenbelt,healthcare Top Word Pairs in Tweet in G2:
[318] spain,madrid [318] show,weeks [318] collapsing,over [318] won,show [318] madrid,healthcare [318] healthcare,collapsing [318] over,west [318] weeks,flatten [318] media,won [318] west,media Top Word Pairs in Tweet in G3:
[15] healthcare,system [14] free,healthcare [9] healthcare,workers [8] #health,#healthcare [8] healthcare,professionals [8] better,healthcare [7] protesters,stage [7] madrid,better [7] stage,huge [7] huge,rally Top Word Pairs in Tweet in G4:
[248] justin,trudeau [248] provincial,premiers [245] healthcare,funding [244] agree,digital [243] premiers,cut [243] threatened,provincial [243] trudeau,threatened [243] unless,agree [243] funding,unless [243] cut,healthcare Top Word Pairs in Tweet in G5:
[210] million,need [107] need,humanitarian [107] need,healthcare [107] humanitarian,assistance [107] around,million [103] including,million [100] assistance,tigray [100] tigray,including [33] healthcare,acco [33] bettyvegas3,around Top Word Pairs in Tweet in G6:
[92] proposed,defund [92] help,billionaires [92] maga,republicans [92] two,months [92] defund,irs [92] power,two [92] republicans,power [92] months,proposed [92] less,tax [92] billionaires,less Top Word Pairs in Tweet in G7:
[47] risk,people [47] access,healthcare [47] people,avoid [47] high,risk [46] recommendations,high [46] crowded,areas [46] lol,cdcs [46] cdcs,recommendations [46] avoid,crowded [46] lose,access Top Word Pairs in Tweet in G8:
[81] sharp,owns [81] news,'richard [81] owns,multimillion [81] pound,stake [81] stake,healthcare [81] 'richard,sharp [81] healthcare,company [81] multimillion,pound [80] granted,nearly [80] woodgnomology,news Top Word Pairs in Tweet in G9:
[88] 53,foreign [88] deporting,53 [88] european,judges [88] human,rights [88] judges,breach [88] terrorists,european [88] foreign,terrorists [88] britain,banned [88] banned,deporting [88] breach,human Top Word Pairs in Tweet in G10:
[105] healthcare,funding [94] canadians,healthcare [93] party,canada [93] kind,pm [93] canada,trying [93] pm,demands [93] liberal,party [93] blackmail,canadians [93] funding,kind [93] trying,blackmail Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G8:
Top Replied-To in G9:
Top Replied-To in G10:
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: