The graph represents a network of 3,198 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, 22 November 2019 at 06:21 UTC.
The requested start date was Friday, 22 November 2019 at 01:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 3-day, 18-hour, 23-minute period from Sunday, 17 November 2019 at 17:30 UTC to Thursday, 21 November 2019 at 11:54 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 : 3198
Unique Edges : 5668
Edges With Duplicates : 4547
Total Edges : 10215
Number of Edge Types : 3
Tweet : 1254
Mentions : 8905
Replies to : 56
Self-Loops : 1254
Reciprocated Vertex Pair Ratio : 0.0537472875980638
Reciprocated Edge Ratio : 0.102011721843814
Connected Components : 404
Single-Vertex Connected Components : 262
Maximum Vertices in a Connected Component : 2487
Maximum Edges in a Connected Component : 9262
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 4.409978
Graph Density : 0.000617468338731413
Modularity : 0.454578
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 3,198 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, 22 November 2019 at 06:21 UTC.
The requested start date was Friday, 22 November 2019 at 01:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 3-day, 18-hour, 23-minute period from Sunday, 17 November 2019 at 17:30 UTC to Thursday, 21 November 2019 at 11:54 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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[898] #fintech,#insurtech [432] #insurtech,#fintech [401] gt,gt [204] #fintech,#banking [193] #vc,#fintech [183] #banking,#finserv [173] #insurance,#insurtech [128] #insurtech,#insurance [123] #finserv,#cryptocurrency [121] #ai,#fintech Top Word Pairs in Tweet in G1:
[424] #fintech,#insurtech [216] #insurtech,#fintech [109] 5,things [107] things,need [107] need,know [99] gt,gt [77] #ai,#fintech [77] #insurance,#insurtech [70] #fintech,changing [70] changing,lives Top Word Pairs in Tweet in G2:
[213] gt,gt [151] #insurtech,#fintech [110] guidewire,#hiring [104] #fintech,#tweetmyjobs [94] #fintech,#insurtech [92] #tweetmyjobs,#jobopening [82] #jobopening,#jobs [65] #jobs,#job [48] ishnae,guidewire [46] software,engineer Top Word Pairs in Tweet in G3:
[19] #insurtech,#insurance [19] #fintech,#insurtech [19] here,fintech [19] fintech,track [19] fintech,germany [17] stand,along [17] along,podcast [16] asr,#ico [16] #ico,#tge [16] #tge,#asure Top Word Pairs in Tweet in G4:
[191] #fintech,#insurtech [39] #insurtech,#artificialintelligence [32] #machinelearning,#deeplearning [28] gt,gt [24] #ai,#fintech [22] good,read [22] #artificialintelligence,#machinelearning [21] using,#ai [19] #ai,#talent [19] #insurtech,#artificialintelli Top Word Pairs in Tweet in G5:
[27] #insurtech,#fintech [18] digitalscoutings,top [18] digital,#insurance [18] #insurance,companies [18] companies,ranking [18] ranking,congrats [17] #fintech,#insurtech [15] #fintech,#ai [15] #ai,team [15] #insurance,#insurtech Top Word Pairs in Tweet in G6:
[147] #vc,#fintech [146] #fintech,#banking [144] #banking,#finserv [101] #finserv,#cryptocurrency [89] #cryptocurrency,#finance [70] #finance,#banks [52] #regtech,#insurtech [51] #banks,#blockchain [48] #blockchain,#regtech [46] ottlegalrebels,neirajones Top Word Pairs in Tweet in G7:
[18] súper,happy [18] happy,announce [18] announce,acquisition [18] acquisition,coverwallet [18] coverwallet,aon [18] aon,very [18] very,proud [18] proud,great [18] great,job [18] job,done Top Word Pairs in Tweet in G8:
[26] 20,millions [23] lève,20 [18] millions,d'euros [17] luko,lève [17] d'euros,pour [14] p2,prototype [14] déploiement,sa [14] sa,plate [14] plate,forme [13] pour,accélérer Top Word Pairs in Tweet in G9:
[36] #insurtech,#insuretech [27] amazon,search [27] search,tranquilo [27] tranquilo,hemp [27] hemp,oil [27] #fintech,#ai [27] #ai,#blockchain [27] #blockchain,#bigdata [27] #bigdata,#ff [23] paris,#fintech Top Word Pairs in Tweet in G10:
[82] #emergingtechnologies,impacting [82] impacting,industries [82] #bigdata,#datascience [82] #datascience,#ai [80] industries,#bigdata [48] kirkdborne,#emergingtechnologies [48] #ai,#machinelearn [28] #ai,#machinele [20] thomas_harrer,#emergingtechnologies [14] #fintech,#insurtech 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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Top Tweeters in G10: