The graph represents a network of 248 Twitter users whose recent tweets contained "#dataeconomy", 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 Sunday, 24 November 2019 at 18:25 UTC.
The tweets in the network were tweeted over the 9-day, 6-hour, 57-minute period from Friday, 15 November 2019 at 11:18 UTC to Sunday, 24 November 2019 at 18:16 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 : 248
Unique Edges : 390
Edges With Duplicates : 303
Total Edges : 693
Number of Edge Types : 4
Mentions : 410
Retweet : 186
Tweet : 88
Replies to : 9
Self-Loops : 88
Reciprocated Vertex Pair Ratio : 0,043778801843318
Reciprocated Edge Ratio : 0,0838852097130243
Connected Components : 33
Single-Vertex Connected Components : 11
Maximum Vertices in a Connected Component : 54
Maximum Edges in a Connected Component : 281
Maximum Geodesic Distance (Diameter) : 6
Average Geodesic Distance : 2,210543
Graph Density : 0,00739519394018545
Modularity : 0,574656
NodeXL Version : 1.0.1.421
Graph Gallery URL : https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=217190
Data Import : The graph represents a network of 248 Twitter users whose recent tweets contained "#dataeconomy", 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 Sunday, 24 November 2019 at 18:25 UTC.
The tweets in the network were tweeted over the 9-day, 6-hour, 57-minute period from Friday, 15 November 2019 at 11:18 UTC to Sunday, 24 November 2019 at 18:16 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 : #dataeconomy
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:
[50] data,economy [40] #dataeconomy,#dataeconomy2019 [37] #dataeconomy2019,#eu2019fi [36] 25,26 [35] data,centre [33] laura,vilkkonen [31] next,week [31] conference,helsinki [23] high,level [21] #blockchain,#dataeconomy Top Word Pairs in Tweet in G1:
[40] data,economy [40] #dataeconomy,#dataeconomy2019 [37] #dataeconomy2019,#eu2019fi [36] 25,26 [33] laura,vilkkonen [31] next,week [31] conference,helsinki [23] high,level [19] 26,11 [18] fair,people Top Word Pairs in Tweet in G2:
[33] data,centre [6] #dataeconomy,#google [5] data,centres [5] #dataeconomy,#aws [5] serverfarm,supports [5] supports,nvidia's [5] nvidia's,artificial [5] artificial,intelligence [5] intelligence,data [5] centre,play Top Word Pairs in Tweet in G3:
[8] jonathan,wolff [8] wolff,explaining [8] explaining,streamr [8] streamr,allows [8] allows,monetise [8] monetise,data [8] data,#diffusion2019 [8] #diffusion2019,watch [8] watch,full [8] full,presentation Top Word Pairs in Tweet in G4:
[12] silicon,valley [12] valley,giants [12] giants,#data [12] #data,#money [12] #money,#bigtech [12] #bigtech,taking [12] taking,low [12] low,profit [12] profit,retail [12] retail,#banking Top Word Pairs in Tweet in G5:
[7] data,exchange [5] insight,data [5] exchange,put [5] put,powerful [5] powerful,data [5] data,hands [5] hands,those [5] those,need [5] need,fast [5] fast,snowflakedb Top Word Pairs in Tweet in G6:
[9] #dataexchange,#dataeconomy [6] hall,p2 [5] p2,stand [5] stand,403 [4] #opendata,#dataexchange [4] day,smartcityexpo [4] data,circulation [3] véhicules,autonomes [3] dawexdata,met [3] met,disposition Top Word Pairs in Tweet in G7:
[15] data,ownership [15] ownership,platform [13] premiomarzotto,#axa [13] #tickettothefuture,#data [13] #data,driven [13] driven,#insurance [13] #iot,#blockchain [13] #blockchain,#dataeconomy [9] #dataeconomy,#dataownership [7] proud,winner Top Word Pairs in Tweet in G8:
[2] #datascience,#analytics [2] european,#dataeconomy [2] data,centre Top Word Pairs in Tweet in G9:
[6] transparency,transparency [6] #ihan,#dataeconomy [6] customer,experience [4] think,fair [4] fair,data [4] data,economy [4] economy,zero [4] zero,sum [4] sum,game [4] game,think Top Word Pairs in Tweet in G10:
[2] data,economic [2] economic,asset [2] asset,data [2] data,economy [2] economy,success [2] success,need [2] need,tp [2] tp,bring [2] bring,back [2] back,data Top Replied-To in Entire Graph:
Top Replied-To in G3:
Top Replied-To in G6:
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 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: