The graph represents a network of 6,408 Twitter users whose tweets in the requested range contained "diabetes", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 15 May 2019 at 15:11 UTC.
The requested start date was Monday, 13 May 2019 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 16-hour, 6-minute period from Sunday, 12 May 2019 at 07:55 UTC to Monday, 13 May 2019 at 00:01 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 : 6408
Unique Edges : 5871
Edges With Duplicates : 909
Total Edges : 6780
Number of Edge Types : 3
Tweet : 2486
Mentions : 3158
Replies to : 1136
Self-Loops : 2486
Reciprocated Vertex Pair Ratio : 0.0208851317752362
Reciprocated Edge Ratio : 0.0409157330735509
Connected Components : 2888
Single-Vertex Connected Components : 1576
Maximum Vertices in a Connected Component : 290
Maximum Edges in a Connected Component : 490
Maximum Geodesic Distance (Diameter) : 12
Average Geodesic Distance : 4.314283
Graph Density : 0.000100009606378167
Modularity : 0.731882
NodeXL Version : 1.0.1.412
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[299] type,2 [240] 2,diabetes [176] heart,disease [153] don,t [143] type,1 [142] blood,pressure [137] high,blood [120] diabetes,high [113] 1,diabetes [108] t,diabetes Top Word Pairs in Tweet in G1:
[97] type,2 [82] 2,diabetes [39] type,1 [32] over,40 [32] 40,states [32] states,allege [32] allege,nation's [32] nation's,largest [32] manufacturers,conspired [31] largest,generic Top Word Pairs in Tweet in G2:
[42] type,2 [42] 2,diabetes [25] diabetes,remission [24] put,type [21] deputy,leader [21] leader,uk [21] uk,labour [21] labour,party [21] party,tom [21] tom,watson Top Word Pairs in Tweet in G3:
[98] those,worried [98] worried,1 [98] 1,don [98] don,t [98] t,diabetes [98] diabetes,high [98] high,blood [98] blood,pressure [98] pressure,heart [98] heart,disease Top Word Pairs in Tweet in G4:
[10] 75,años [6] type,2 [6] 2,diabetes [6] tratamiento,#diabetes [5] explican,beneficio [5] sglt,2 [5] #pacientes,#diabetes [5] #diabetes,mayores [5] mayores,75 [5] años,3 Top Word Pairs in Tweet in G5:
[72] salah,dimatiin [72] dimatiin,buat [72] buat,nutupin [72] nutupin,fakta [72] fakta,husni [72] husni,kamil [72] kamil,malik [72] malik,meninggal [72] meninggal,karena [72] karena,mengidap Top Word Pairs in Tweet in G6:
[27] article,nih [27] nih,discusses [27] discusses,links [27] links,between [27] between,obesity [27] obesity,diabetes [27] diabetes,cardiovascular [27] cardiovascular,disease [26] r_m_huffman,article [8] type,2 Top Word Pairs in Tweet in G7:
[14] matters,mody [14] mody,diagnosed [14] diagnosed,close [14] close,diabetes [14] diabetes,diagnosis [14] diagnosis,delay [14] delay,means [14] means,good [14] good,control [14] control,less Top Word Pairs in Tweet in G8:
[15] type,2 [13] 2,#diabetes [10] #diabetes,mellitus [10] mellitus,associated [10] associated,doubled [10] doubled,risk [10] risk,severe [10] severe,liver [10] liver,disease [9] jwatch,type Top Word Pairs in Tweet in G9:
[3] democrats,working [3] working,protect [3] protect,patients [3] patients,preexisting [3] preexisting,conditions [3] conditions,cancer [3] gop,senatemajldr [3] senatemajldr,democrats [2] obesity,diabetes [2] cancer,diabetes Top Word Pairs in Tweet in G10:
[2] girth_brooks15,aoc [2] myrickharward,lovelearnrage [2] lovelearnrage,aoc [2] empower,yourself [2] yourself,here [2] here,become [2] become,independent [2] independent,rep [2] rep,amazing [2] amazing,product Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
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