The graph represents a network of 2,220 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, 28 January 2022 at 13:09 UTC.
The requested start date was Friday, 28 January 2022 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 6-day, 5-hour, 30-minute period from Friday, 21 January 2022 at 19:30 UTC to Friday, 28 January 2022 at 01:00 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 : 2220
Unique Edges : 3696
Edges With Duplicates : 16155
Total Edges : 19851
Number of Edge Types : 5
Tweet : 1037
Retweet : 5436
MentionsInRetweet : 8448
Mentions : 4816
Replies to : 114
Self-Loops : 1400
Reciprocated Vertex Pair Ratio : 0.05100905768314
Reciprocated Edge Ratio : 0.0970668279407318
Connected Components : 237
Single-Vertex Connected Components : 143
Maximum Vertices in a Connected Component : 1790
Maximum Edges in a Connected Component : 19269
Maximum Geodesic Distance (Diameter) : 9
Average Geodesic Distance : 3.461619
Graph Density : 0.00134262247826917
Modularity : 0.24084
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 2,220 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, 28 January 2022 at 13:09 UTC.
The requested start date was Friday, 28 January 2022 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 6-day, 5-hour, 30-minute period from Friday, 21 January 2022 at 19:30 UTC to Friday, 28 January 2022 at 01:00 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:
[1441] #iot,#iiot [1263] #javascript,#reactjs [1194] #women,#ehealth [1188] #cx,#women [1082] #iiot,#pytorch [1076] #python,#iot [1053] #datascientist,#digital [1053] #digital,#cx [1039] #finserv,#fashiontech [1035] #ces2023,#finserv Top Word Pairs in Tweet in G1:
[1040] #women,#ehealth [1034] #cx,#women [925] #datascientist,#digital [925] #digital,#cx [913] #finserv,#fashiontech [913] #fashiontech,#insurtech [909] #ces2023,#finserv [868] #ehealth,#data [868] #data,#ces2023 [530] chidambara09,#datascientist Top Word Pairs in Tweet in G2:
[46] #iot,#iiot [45] #javascript,#reactjs [35] #reactjs,#wordpress [33] fgraillot,great [31] #python,#iot [30] #iiot,#pytorch [28] #pytorch,#javascript [22] great,overview [22] #python,#ai [22] #ai,#iot Top Word Pairs in Tweet in G3:
[1301] #iot,#iiot [1122] #javascript,#reactjs [974] #iiot,#pytorch [961] #python,#iot [810] #reactjs,#wordpress [726] #robotics,#aiethics [668] #machinelearning,#ai [609] #pytorch,#javascript [598] #wordpress,#security [553] #aiethics,#machinelearning Top Word Pairs in Tweet in G4:
[9] safebrok,aspira [9] aspira,convertirse [9] convertirse,principales [9] principales,insurtech [9] insurtech,mercado [8] fintech,insurtech [6] insurtech,startup [5] mobility,insurtech [5] laka,secures [5] secures,10 Top Word Pairs in Tweet in G5:
[62] #insurtech,#fintech [59] #ai,bank [59] bank,future [59] future,#infographic [59] #infographic,#insurtech [59] #fintech,#banking [59] #banking,#finserv [59] #finserv,cc [59] cc,evankirstel [58] antgrasso,lindagrass0 Top Word Pairs in Tweet in G6:
[35] #fintech,#insurtech [15] #insurtech,#insurance [12] last,year [12] fgraillot,great [11] #europe,last [11] year,#fintech [10] #fintech,#i [10] spirosmargaris,ai [9] female,#entrepreneurs [9] #entrepreneurs,banked Top Word Pairs in Tweet in G7:
[76] rumpire,strikes [76] strikes,back [76] back,episode [76] part,insurance [76] insurance,mockumentary [76] mockumentary,detailing [76] detailing,ed's [76] ed's,journey [76] journey,self [75] episode,hubbinsure's Top Word Pairs in Tweet in G8:
[8] #insurtech,#insurance [6] based,lakahq [6] mobility,insurtech [6] #fintech,#insurtech [5] uk,based [5] lakahq,secures [5] secures,10 [5] 10,million [5] million,build [5] build,european Top Word Pairs in Tweet in G9:
[16] nourrir,réparer [16] réparer,planète [16] planète,sans [16] sans,avoir [16] avoir,capacité [16] capacité,prendre [16] prendre,risques [16] risques,sebastien_abis [16] sebastien_abis,directeur [16] directeur,club Top Word Pairs in Tweet in G10:
[15] bandita,#chambing [15] #chambing,encanta [15] encanta,startup [15] startup,colombiana [15] colombiana,sector [15] sector,insurtech [15] insurtech,seguros [15] seguros,busca [15] busca,fullstack [14] talentprospect,bandita Top Replied-To in Entire Graph:
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Top Replied-To in G6:
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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 G10: