The graph represents a network of 2,585 Twitter users whose tweets in the requested range contained "InsurTech", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 13 May 2022 at 12:32 UTC.
The requested start date was Friday, 13 May 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 2-day, 16-hour, 1-minute period from Tuesday, 10 May 2022 at 08:00 UTC to Friday, 13 May 2022 at 00:01 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 : 2585
Unique Edges : 3350
Edges With Duplicates : 15218
Total Edges : 18568
Number of Edge Types : 5
Mentions : 2930
Retweet : 5473
MentionsInRetweet : 8592
Replies to : 168
Tweet : 1405
Self-Loops : 1507
Reciprocated Vertex Pair Ratio : 0.0515873015873016
Reciprocated Edge Ratio : 0.0981132075471698
Connected Components : 493
Single-Vertex Connected Components : 410
Maximum Vertices in a Connected Component : 1952
Maximum Edges in a Connected Component : 17631
Maximum Geodesic Distance (Diameter) : 9
Average Geodesic Distance : 3.453015
Graph Density : 0.000912474324963621
Modularity : 0.256553
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 2,585 Twitter users whose tweets in the requested range contained "InsurTech", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 13 May 2022 at 12:32 UTC.
The requested start date was Friday, 13 May 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 2-day, 16-hour, 1-minute period from Tuesday, 10 May 2022 at 08:00 UTC to Friday, 13 May 2022 at 00:01 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 : InsurTech
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:
[1604] #iot,#iiot [1532] #fintech,#insurtech [1522] #javascript,#reactjs [1381] #reactjs,#wordpress [1302] #wordpress,#security [1200] #python,#iot [1190] #security,#defi [1101] #iiot,#pytorch [1008] #aiethics,#machinelearning [972] #machinelearning,#ai Top Word Pairs in Tweet in G1:
[237] #fintech,#insurtech [132] #fintech,#finserv [126] enricomolinari,#ai [123] #aiethics,#machinelearning [120] #machinelearning,#ai [116] #ai,#python [112] bcg,enricomolinari [104] #finserv,#insurtech [98] #ai,#vr [98] #vr,#ar Top Word Pairs in Tweet in G2:
[58] #aiethics,#machinelearning [55] #insurtech,#insurance [53] #machinelearning,#ai [51] #ai,#python [46] #fintech,#insurtech [38] #women,#usa [36] #insurtech,#fintech [34] #insurance,#insurtech [32] #fashion,enilev [31] #healthtech,#datascientist Top Word Pairs in Tweet in G3:
[395] #fintech,#insurtech [391] #mining,#fintech [387] #insurtech,#crypto [386] #crypto,#bitcoin [383] #helios,#mining [15] project,#helios [14] insurtech,startup [14] insurtech,firm [13] helios,fund [11] growing,insurtech Top Word Pairs in Tweet in G4:
[1555] #iot,#iiot [1464] #javascript,#reactjs [1329] #reactjs,#wordpress [1250] #wordpress,#security [1142] #python,#iot [1138] #security,#defi [1052] #iiot,#pytorch [825] #pytorch,#javascript [691] #aiethics,#machinelearning [668] #machinelearning,#ai Top Word Pairs in Tweet in G5:
[104] #aiethics,#machinelearning [102] #machinelearning,#ai [98] #ai,#python [38] #python,#deeplearning [32] #fintech,#insurtech [29] #robotics,#aiethics [28] sign,free [28] free,middlemen [28] middlemen,#robotics [26] #deeplearning,#iot Top Word Pairs in Tweet in G6:
[212] #fintech,#insurtech [208] #mining,#fintech [204] #insurtech,#crypto [199] #helios,#mining [199] #crypto,#bitcoin [35] fundhelios,#helios [33] #bitcoin,fundhelios [12] helios,fund [11] project,great [11] project,#helios Top Word Pairs in Tweet in G7:
[13] rapprochement,aux [13] aux,allures [13] allures,d'évidence [13] d'évidence,deux [13] deux,pépites [13] pépites,l'#insurtech [13] l'#insurtech,leocare_assure [13] leocare_assure,jette [13] jette,dévolu [12] eficiens,rapprochement Top Word Pairs in Tweet in G8:
[121] nigerian,fintechs [66] fintechs,payment [66] lending,23 [55] assumption,nigerian [55] payment,faulty [55] faulty,nigerian [55] fintechs,actually [55] actually,lending [54] adetolaov,assumption [12] 23,savings Top Word Pairs in Tweet in G9:
[22] #aiethics,#machinelearning [21] #machinelearning,#ai [20] #ai,#python [18] although,ai [18] ai,deployment [18] deployment,poses [18] poses,several [18] several,risks [18] risks,benefits [18] benefits,insurance Top Word Pairs in Tweet in G10:
[25] insurtech,summit [12] day,insurtech [12] hosted,eblosfieldcm [9] summit,2022 [7] eblosfieldcm,carriermgmt [6] today,day [5] summit,it'll [5] it'll,filled [5] filled,expert [5] expert,panels Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G7:
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Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: