The graph represents a network of 1,799 Twitter users whose tweets in the requested range contained "predictive analytics", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Sunday, 12 June 2022 at 04:55 UTC.
The requested start date was Sunday, 12 June 2022 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 13-day, 22-hour, 31-minute period from Sunday, 29 May 2022 at 01:25 UTC to Saturday, 11 June 2022 at 23:56 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 : 1799
Unique Edges : 1365
Edges With Duplicates : 1929
Total Edges : 3294
Number of Edge Types : 5
Tweet : 746
Retweet : 773
MentionsInRetweet : 1073
Mentions : 613
Replies to : 89
Self-Loops : 779
Reciprocated Vertex Pair Ratio : 0.0314663310258024
Reciprocated Edge Ratio : 0.061012812690665
Connected Components : 655
Single-Vertex Connected Components : 387
Maximum Vertices in a Connected Component : 433
Maximum Edges in a Connected Component : 1465
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 4.243751
Graph Density : 0.000506708398745812
Modularity : 0.515708
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 1,799 Twitter users whose tweets in the requested range contained "predictive analytics", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Sunday, 12 June 2022 at 04:55 UTC.
The requested start date was Sunday, 12 June 2022 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 13-day, 22-hour, 31-minute period from Sunday, 29 May 2022 at 01:25 UTC to Saturday, 11 June 2022 at 23:56 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 : predictive analytics
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:
[952] predictive,analytics [198] top,list [196] list,hot [164] predictive,#analytics [158] machine,learning [113] analytics,top [111] hot,#technologies [108] #ai,predictive [105] ai,predictive [87] hot,technologies Top Word Pairs in Tweet in G1:
[315] predictive,analytics [30] machine,learning [27] data,predictive [26] data,analytics [26] use,predictive [24] ai,predictive [24] hot,technologies [23] analytics,top [23] top,list [22] list,hot Top Word Pairs in Tweet in G2:
[117] predictive,analytics [101] top,list [100] list,hot [71] analytics,top [58] predictive,#analytics [57] hot,#technologies [45] #ai,predictive [43] ai,predictive [43] hot,technologies [34] machine,learning Top Word Pairs in Tweet in G5:
[49] top,list [49] list,hot [49] hot,#technologies [49] #technologies,#banks [48] #ai,predictive [48] predictive,#analytics [48] #analytics,top [38] #fintech,#machinelearning [38] #banks,#fintech [37] khulood_almani,#ai Top Word Pairs in Tweet in G6:
[17] top,machine [17] machine,learning [17] learning,algorithms [17] algorithms,predictions [17] predictions,higher [17] higher,resolution [17] resolution,table [17] table,downloaded [16] ceo_aisoma,top [14] predictive,analytics Top Word Pairs in Tweet in G7:
[12] predictive,analytics [6] google's,chief [6] chief,measurement [6] measurement,strategist [6] strategist,neilhoyne [6] neilhoyne,joined [6] joined,pecan_ai's [6] pecan_ai's,ceo [6] ceo,co [6] co,founder Top Word Pairs in Tweet in G8:
[19] ai,predictive [18] predictive,#analytics [18] #analytics,marketing [18] marketing,need [18] need,know [18] know,mikekaput [18] mikekaput,mktgai [16] ipfconline1,ai [15] mktgai,#datascienceâ [3] mktgai,#datascience Top Word Pairs in Tweet in G9:
[14] predictive,analytics [9] embed,automate [9] automate,discriminatory [9] discriminatory,behavior [9] behavior,institution [7] institution,operations [6] analytics,embed [6] operations,danbauman77 [6] congress,scrutinize [6] scrutinize,higher Top Replied-To in Entire Graph:
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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 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: