The graph represents a network of 7,069 Twitter users whose recent tweets contained "#apha2019 OR #apha19", 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 Thursday, 07 November 2019 at 07:58 UTC and adds to an earlier extract - http://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=215366.
The tweets in the network were tweeted 10 day period from Sunday, 27 October 2019 at 14:00 UTC to Thursday, 07 November 2019 at 07:40 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 : 7069
Unique Edges : 22758
Edges With Duplicates : 35277
Total Edges : 58035
Self-Loops : 4653
Reciprocated Vertex Pair Ratio : 0.0856618322012117
Reciprocated Edge Ratio : 0.157805735930736
Connected Components : 162
Single-Vertex Connected Components : 113
Maximum Vertices in a Connected Component : 6829
Maximum Edges in a Connected Component : 57727
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 3.061535
Graph Density : 0.000591789734033266
Modularity : 0.277747
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 4,721 Twitter users whose recent tweets contained "#apha2019 OR #apha19 since:2019-11-05", 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 Thursday, 07 November 2019 at 07:58 UTC.
The tweets in the network were tweeted over the 2-day, 7-hour, 40-minute period from Tuesday, 05 November 2019 at 00:00 UTC to Thursday, 07 November 2019 at 07:40 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 : #apha2019 OR #apha19 since:2019-11-05
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 : Followers
Vertex Alpha : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[3771] public,health [999] aphaannualmtg,#apha2019 [866] check,out [692] #apha2019,aphaannualmtg [568] #aphatweetup,#apha2019 [521] publichealth,#apha2019 [509] learn,more [509] looking,forward [480] publichealth,aphaannualmtg [457] health,equity Top Word Pairs in Tweet in G1:
[1708] public,health [359] #aphatweetup,#apha2019 [357] #apha2019,aphaannualmtg [351] aphaannualmtg,#apha2019 [274] check,out [216] health,#apha2019 [210] publichealth,#apha2019 [201] looking,forward [197] social,determinants [192] publichealth,aphaannualmtg Top Word Pairs in Tweet in G2:
[529] public,health [185] aphaannualmtg,#apha2019 [144] check,out [142] #bfresearch,#apha2019 [125] publichealth,#apha2019 [122] #apha2019,#bfresearch [119] health,equity [105] aphaannualmtg,publichealth [95] don,t [79] #apha2019,aphaannualmtg Top Word Pairs in Tweet in G3:
[694] public,health [239] aphaannualmtg,#apha2019 [227] check,out [139] #apha2019,aphaannualmtg [134] learn,more [120] #apha2019,publichealth [103] looking,forward [97] social,media [88] stop,booth [85] publichealth,#apha2019 Top Word Pairs in Tweet in G4:
[389] public,health [158] aphaannualmtg,#apha2019 [115] check,out [112] publichealth,aphaannualmtg [67] learn,more [67] looking,forward [64] #aphatweetup,#apha2019 [60] #apha2019,aphaannualmtg [57] health,equity [55] stop,booth Top Word Pairs in Tweet in G5:
[84] public,health [48] global,health [41] #globalhealth,workforce [40] amalia,riego [37] women,s [36] #women,make [36] make,up [36] up,#majority [36] #majority,#globalhealth [36] workforce,women Top Word Pairs in Tweet in G6:
[166] pro,tip [166] tip,meet [166] meet,someone [166] someone,conference [166] conference,never [166] never,make [166] make,assumption [166] assumption,being [166] being,asked [166] asked,student Top Word Pairs in Tweet in G7:
[55] public,health [17] air,quality [16] health,officials [16] tell,truth [16] today,#apha2019 [15] systematic,review [15] climate,change [13] climate,health [13] trump,administration [13] quality,standards Top Word Pairs in Tweet in G8:
[16] public,health [8] apha,2019 [6] health,#apha2019 [4] #apha19,#opengeneralsession [4] #apha2019,#opengeneralsession [4] 2019,photo [4] photo,station [4] station,sponsored [4] sponsored,kaiser [4] kaiser,permanente Top Word Pairs in Tweet in G9:
[21] digital,literacy [20] older,adults [16] literacy,skills [14] skills,older [12] #apha2019,abtassociates [12] public,health [11] abtassociates,booth [10] stop,booth [9] owning,successfully [9] successfully,using Top Word Pairs in Tweet in G10:
[30] public,health [26] booth,#1327 [19] learn,more [17] stop,booth [14] booth,1301 [12] program,director [11] thenci,booth [10] dr,verma [10] verma,nciepi [10] nciepi,attend 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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