The graph represents a network of 1,514 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, 04 February 2022 at 13:10 UTC.
The requested start date was Friday, 04 February 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 2-day, 21-hour, 31-minute period from Tuesday, 01 February 2022 at 02:59 UTC to Friday, 04 February 2022 at 00:30 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 : 1514
Unique Edges : 1971
Edges With Duplicates : 17037
Total Edges : 19008
Number of Edge Types : 5
Retweet : 6448
MentionsInRetweet : 8713
Mentions : 3200
Replies to : 118
Tweet : 529
Self-Loops : 1031
Reciprocated Vertex Pair Ratio : 0.0388174807197943
Reciprocated Edge Ratio : 0.0747339767384311
Connected Components : 215
Single-Vertex Connected Components : 150
Maximum Vertices in a Connected Component : 1137
Maximum Edges in a Connected Component : 18431
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 3.511446
Graph Density : 0.00176410344168243
Modularity : 0.173698
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 1,514 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, 04 February 2022 at 13:10 UTC.
The requested start date was Friday, 04 February 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 2-day, 21-hour, 31-minute period from Tuesday, 01 February 2022 at 02:59 UTC to Friday, 04 February 2022 at 00:30 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:
[2304] #ces2023,#finserv [2295] #cx,#women [2295] #women,#ehealth [2290] #finserv,#fashiontech [2269] #fashiontech,#insurtech [2250] #ehealth,#data [2250] #data,#ces2023 [2155] #iot,#iiot [2138] #digital,#cx [2124] #datascientist,#digital Top Word Pairs in Tweet in G1:
[205] #fintech,#insurtech [127] #cx,#women [127] #women,#ehealth [127] #ces2023,#finserv [127] #finserv,#fashiontech [126] #ehealth,#data [126] #data,#ces2023 [124] #fashiontech,#insurtech [123] #insurtech,#big [122] chidambara09,#datascientist Top Word Pairs in Tweet in G2:
[2136] #iot,#iiot [2002] #ces2023,#finserv [1995] #cx,#women [1995] #women,#ehealth [1991] #finserv,#fashiontech [1975] #fashiontech,#insurtech [1953] #ehealth,#data [1953] #data,#ces2023 [1861] #digital,#cx [1849] #datascientist,#digital Top Word Pairs in Tweet in G3:
[39] insurtech,startup [34] kenyan,insurtech [34] startup,lami [33] malawi,drc [31] lami,enters [31] enters,malawi [31] drc,acquiring [31] acquiring,bluewave [31] bluewave,eyes [31] eyes,rest Top Word Pairs in Tweet in G4:
[302] #machinelearning,#ai [280] #robotics,#aiethics [252] #aiethics,#machinelearning [184] sign,free [184] free,charge [168] #ai,#python [147] #fintech,#insurtech [143] #python,#datascience [143] #datascience,#bigdata [142] #100daysofcode,#robots Top Word Pairs in Tweet in G5:
[39] kenyan,insurtech [39] insurtech,startup [39] enters,malawi [39] malawi,drc [39] drc,acquiring [39] eyes,rest [39] rest,africa [38] startup,lami [38] lami,enters [38] acquiring,bluewave Top Word Pairs in Tweet in G6:
[34] #infographic,24 [34] 24,industries [34] industries,disrupted [34] disrupted,#ai [34] #ai,ingliguori [34] ingliguori,#artificialintelligence [31] #artificialintelligence,#iotpl [30] ingliguori,#infographic [26] #iotpl,# [19] #fintech,#insurtech Top Word Pairs in Tweet in G7:
[26] #fintech,#finserv [25] #finserv,#cryptos [25] #cryptos,#innovation [24] important,before [24] before,lose [24] lose,money [24] money,#crypto [24] #crypto,know [24] know,read [24] read,table Top Word Pairs in Tweet in G8:
[2] miss,ways [2] ways,transform [2] transform,insurance [2] insurance,customer [2] customer,experience [2] experience,itlupdates [2] itlupdates,#insurance [2] méditer,parle [2] parle,assez [2] assez,ces Top Word Pairs in Tweet in G9:
[17] dbdtokens,leveraging [17] leveraging,algorand [17] algorand,build [17] build,first [17] first,kind [17] kind,blockchain [17] blockchain,based [17] based,#insurtech [17] #insurtech,platform [16] algorand,dbdtokens Top Word Pairs in Tweet in G10:
[3] thanks,_diginsurance [2] today,foresight_ins [2] foresight_ins,making [2] making,headlines [2] headlines,one [2] one,top [2] top,#insurtech [2] #insurtech,funding [2] funding,rounds [2] rounds,announced Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G5:
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: