The graph represents a network of 3,150 Twitter users whose recent tweets contained "#insurtech", 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 Friday, 05 November 2021 at 11:39 UTC.
The tweets in the network were tweeted over the 8-day, 18-hour, 47-minute period from Wednesday, 27 October 2021 at 15:29 UTC to Friday, 05 November 2021 at 10:17 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 : 3150
Unique Edges : 15959
Edges With Duplicates : 47405
Total Edges : 63364
Number of Edge Types : 5
Retweet : 14398
MentionsInRetweet : 39391
Mentions : 7761
Replies to : 213
Tweet : 1601
Self-Loops : 2194
Reciprocated Vertex Pair Ratio : 0.0575244207446558
Reciprocated Edge Ratio : 0.108790718429273
Connected Components : 95
Single-Vertex Connected Components : 56
Maximum Vertices in a Connected Component : 2996
Maximum Edges in a Connected Component : 63181
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 2.744424
Graph Density : 0.00225922061425396
Modularity : 0.180158
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 3,150 Twitter users whose recent tweets contained "#insurtech", 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 Friday, 05 November 2021 at 11:39 UTC.
The tweets in the network were tweeted over the 8-day, 18-hour, 47-minute period from Wednesday, 27 October 2021 at 15:29 UTC to Friday, 05 November 2021 at 10:17 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 : #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:
[6962] #fintech,#insurtech [4818] #bigdata,#deeplearning [4810] #deeplearning,#iot [4800] #aiethics,#machinelearning [4796] #iot,#100daysofcode [4793] #machinelearning,#ai [4792] #insurtech,#nocode [4784] #robots,#fintech [4782] #100daysofcode,#robots [4755] #python,#datascience Top Word Pairs in Tweet in G1:
[1965] #fintech,#insurtech [896] #frenchtech,#flutter [893] #linux,#insurtech [891] #javascript,#frenchtech [890] #100daysofcode,#javascript [889] #ces2022,#socialmedia [886] betamoroney,enilev [886] enilev,evasmartai [883] #bigdata,#100daysofcode [835] #datascience,#finserv Top Word Pairs in Tweet in G2:
[1199] #fintech,#insurtech [753] #machinelearning,#ai [741] #aiethics,#machinelearning [741] #bigdata,#deeplearning [739] #robotics,#aiethics [739] #deeplearning,#iot [738] #iot,#100daysofcode [735] #insurtech,#nocode [734] #100daysofcode,#robots [733] #python,#datascience Top Word Pairs in Tweet in G3:
[3603] #fintech,#insurtech [3466] #bigdata,#deeplearning [3462] #deeplearning,#iot [3454] #iot,#100daysofcode [3449] #aiethics,#machinelearning [3446] #insurtech,#nocode [3445] #100daysofcode,#robots [3445] #robots,#fintech [3425] #machinelearning,#ai [3424] #ai,#python Top Word Pairs in Tweet in G4:
[94] #fintech,#insurtech [48] #insurance,#insurtech [48] #bigdata,#100daysofcode [48] #100daysofcode,#javascript [48] #javascript,#frenchtech [48] #frenchtech,#flutter [48] #linux,#insurtech [47] #ces2022,#socialmedia [46] #datascience,#finserv [46] betamoroney,enilev Top Word Pairs in Tweet in G5:
[16] round,#fintech [13] #fintech,#insurtech [13] #bigdata,#100daysofcode [13] #100daysofcode,#javascript [13] #javascript,#frenchtech [13] #frenchtech,#flutter [13] #linux,#insurtech [13] #technology,#ces2022 [13] #ces2022,#socialmedia [13] betamoroney,enilev Top Word Pairs in Tweet in G6:
[14] inclusive,insurance [10] learn,more [10] channel,hopping [8] #channelhopping,#insurance [8] #insurance,#insurtech [7] last,thursday [7] thursday,etherisc [7] etherisc,cio [7] cio,mrmichael78 [7] mrmichael78,spoke Top Word Pairs in Tweet in G7:
[11] #insurance,#insurtech [7] #ico,#insurtech [6] #fintech,#insurtech [4] #insurtech,#finance [4] #finance,#financial [4] #financial,#insuranceindustry [4] #insuranceindustry,#insuranceinnovation [4] catching,do' [4] do',businesses [4] businesses,improving Top Word Pairs in Tweet in G8:
[6] #insurtech,#insurance [5] #innovazione,#insurtech [3] #insurtech,#smartcity [3] mondo,assicurativo [3] #innovazione,#insurance [3] insurtech,association [2] milioni,dollari [2] #insurtech,compagnie [2] compagnie,devono [2] devono,concentrarsi Top Word Pairs in Tweet in G9:
[9] #fintech,#insurtech [4] #robotics,#aiethics [4] #aiethics,#machinelearning [4] #machinelearning,#ai [4] #ai,#python [4] #python,#datascience [4] #datascience,#bigdata [4] #bigdata,#deeplearning [4] #deeplearning,#iot [4] #iot,#100daysofcode Top Word Pairs in Tweet in G10:
[24] #fintech,#insurtech [11] fin,tech [10] #insurtech,italiano [8] dalle,15 [8] 15,30 [8] offre,all'ecosistema [8] all'ecosistema,#fintech [7] #insurtech,#bigdata [6] sale,#infographic [6] #infographic,#tech Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G8:
Top Replied-To in G9:
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: