The graph represents a network of 892 Twitter users whose recent tweets contained "#QEvent2019 OR #QEvent19 OR #QExchange OR #Qcommunity", 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 Wednesday, 20 November 2019 at 18:04 UTC.
The tweets in the network were tweeted over the 8-day, 21-hour, 9-minute period from Monday, 11 November 2019 at 20:43 UTC to Wednesday, 20 November 2019 at 17:52 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 : 892
Unique Edges : 3266
Edges With Duplicates : 2544
Total Edges : 5810
Self-Loops : 231
Reciprocated Vertex Pair Ratio : 0.0983698707138842
Reciprocated Edge Ratio : 0.179119754350051
Connected Components : 16
Single-Vertex Connected Components : 8
Maximum Vertices in a Connected Component : 868
Maximum Edges in a Connected Component : 5785
Maximum Geodesic Distance (Diameter) : 6
Average Geodesic Distance : 2.831428
Graph Density : 0.00491713346720821
Modularity : 0.356364
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 892 Twitter users whose recent tweets contained "#QEvent2019 OR #QEvent19 OR #QExchange OR #Qcommunity", 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 Wednesday, 20 November 2019 at 18:04 UTC.
The tweets in the network were tweeted over the 8-day, 21-hour, 9-minute period from Monday, 11 November 2019 at 20:43 UTC to Wednesday, 20 November 2019 at 17:52 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 : #QEvent2019 OR #QEvent19 OR #QExchange OR #Qcommunity
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:
[153] theqcommunity,#qevent2019 [136] looking,forward [90] #qevent2019,theqcommunity [89] find,out [72] theqcommunity,fabnhsstuff [68] quality,improvement [64] today,s [54] s,#qevent2019 [52] out,more [51] theqcommunity,#qevent19 Top Word Pairs in Tweet in G1:
[41] theqcommunity,#qevent2019 [35] looking,forward [24] #qevent2019,theqcommunity [24] theqcommunity,futuregov [22] #qevent19,theqcommunity [19] learning,failure [18] today,s [18] find,out [17] here,s [17] great,session Top Word Pairs in Tweet in G2:
[58] theqcommunity,#qevent2019 [49] find,out [33] looking,forward [30] quality,improvement [27] out,more [27] #qevent2019,theqcommunity [23] head,over [22] more,info [20] interested,senior [20] senior,leaders Top Word Pairs in Tweet in G3:
[60] theqcommunity,fabnhsstuff [41] winning,#qexchange [39] theqcommunity,#qevent2019 [32] looking,forward [29] quality,improvement [29] #evidencebasedqi,project [28] #qevent2019,theqcommunity [27] help,winning [27] #qexchange,#evidencebasedqi [27] project,help Top Word Pairs in Tweet in G4:
[32] five,trusts [32] trusts,implemented [32] implemented,vmi [32] vmi,widely [32] widely,varying [32] varying,results [32] results,drnicolaburgess [32] drnicolaburgess,describes [32] describes,different [32] different,levels Top Word Pairs in Tweet in G5:
[8] #qexchange,#qcommunity [8] fionacloud,rajthur [8] rajthur,cievertltd [8] #qevent2019,traditional [8] traditional,approach [8] approach,learn [8] learn,safety [8] safety,goes [8] goes,wrong [8] wrong,learning Top Word Pairs in Tweet in G6:
[20] members,voted [20] #cop,#humanfactors [20] #humanfactors,#ergonomics [20] #ergonomics,#qi [17] thank,theqcommunity [17] theqcommunity,members [17] voted,nhs_education [17] nhs_education,partners [17] partners,receive [17] receive,healthfdn Top Word Pairs in Tweet in G7:
[10] co,design [7] nhsgwccg,surreyheartland [6] feeling,very [6] very,privileged [6] privileged,part [6] part,8 [6] 8,amazing [6] amazing,winners [6] winners,outpatient [6] outpatient,improvement Top Word Pairs in Tweet in G8:
[13] official,#ambulanceq [13] #ambulanceq,win [13] win,#qexchange [13] #qexchange,2019 [13] 2019,erinqipayne [13] erinqipayne,aparker2sas [13] aparker2sas,davemorgan_neas [13] davemorgan_neas,smewni [13] smewni,clairebevanwast [13] clairebevanwast,claireroche19 Top Word Pairs in Tweet in G9:
[8] personalised,care [7] voted,very [7] very,grateful [7] outpatient,transformation [6] delighted,winner [6] winner,years [6] years,#qevent2019 [6] #qevent2019,huge [6] huge,thanks [6] thanks,supported Top Word Pairs in Tweet in G10:
[9] mental,health [9] bjeeves,paulawoods5 [8] team_mis,keeleiau [7] keeleiau,rachel66mckeown [6] msk,mental [5] couple,days [5] rachel66mckeown,neilcarrmpft [5] neilcarrmpft,mpftnhs [5] mpftnhs,bjeeves [4] busy,couple Top Replied-To in Entire Graph:
Top Replied-To in G1:
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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:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G3:
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Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: