The graph represents a network of 1,920 Twitter users whose recent tweets contained "#Bioinformatics", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 6,000 tweets. The network was obtained from Twitter on Sunday, 29 August 2021 at 01:48 UTC.
The tweets in the network were tweeted over the 8-day, 3-hour, 49-minute period from Friday, 20 August 2021 at 20:42 UTC to Sunday, 29 August 2021 at 00:32 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 : 1920
Unique Edges : 4297
Edges With Duplicates : 3656
Total Edges : 7953
Number of Edge Types : 5
Retweet : 4115
Replies to : 251
MentionsInRetweet : 2270
Mentions : 527
Tweet : 790
Self-Loops : 856
Reciprocated Vertex Pair Ratio : 0.0196867061812024
Reciprocated Edge Ratio : 0.0386132447581482
Connected Components : 50
Single-Vertex Connected Components : 19
Maximum Vertices in a Connected Component : 1806
Maximum Edges in a Connected Component : 7807
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 3.505354
Graph Density : 0.00130737580336981
Modularity : 0.419524
NodeXL Version : 1.0.1.445
Graph Gallery URL : https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=260935
Data Import : The graph represents a network of 1,920 Twitter users whose recent tweets contained "#Bioinformatics", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 6,000 tweets. The network was obtained from Twitter on Sunday, 29 August 2021 at 01:48 UTC.
The tweets in the network were tweeted over the 8-day, 3-hour, 49-minute period from Friday, 20 August 2021 at 20:42 UTC to Sunday, 29 August 2021 at 00:32 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 : #Bioinformatics
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:
[681] #100daysofcode,#womenwhocode [669] #datascience,#100daysofcode [638] #openscience,#datascience [613] #womenwhocode,#bigdata [588] #python,#coding [536] #bioinformatics,#openscience [514] #coding,#scicomm [482] #linux,#python [410] #serverless,#linux [402] #bigdata,#machinelearning Top Word Pairs in Tweet in G1:
[576] #100daysofcode,#womenwhocode [569] #datascience,#100daysofcode [549] #openscience,#datascience [519] #womenwhocode,#bigdata [498] #python,#coding [455] #bioinformatics,#openscience [436] #coding,#scicomm [411] #linux,#python [351] #serverless,#linux [343] #bigdata,#machinelearning Top Word Pairs in Tweet in G2:
[118] #bioit,#bioinformatics [82] #genomics,#bioinformatics [51] better,expert [49] #healthcare,#healthtech [49] #healthtech,#medical [47] #medical,#mri [47] #mri,#bioinformatics [45] #bioinformatics,comment [42] #health,#healthcare [41] positions,#genomics Top Word Pairs in Tweet in G3:
[119] #genomics,#bioinformatics [53] better,expert [51] #healthcare,#healthtech [51] #healthtech,#medical [49] #bioinformatics,#bioinformática [49] #medical,#mri [49] #mri,#bioinformatics [46] biology,#bioinformatics [45] single,cell [44] #health,#healthcare Top Word Pairs in Tweet in G4:
[30] pacbio,nanopore [27] join,3rd [27] 3rd,#hackathon [27] #hackathon,hgsc [27] hgsc,oct [27] oct,10 [27] 10,13th [27] 13th,virtual [27] virtual,register [27] register,work Top Word Pairs in Tweet in G5:
[59] #100daysofcode,#womenwhocode [56] #datascience,#100daysofcode [55] #python,#coding [53] #openscience,#datascience [51] #womenwhocode,#bigdata [47] #coding,#scicomm [45] #linux,#python [37] #bigdata,#machinelearning [37] #machinelearning,#serverless [37] #serverless,#linux Top Word Pairs in Tweet in G6:
[54] ph,position [54] position,computational [54] computational,biology [54] biology,bioinformatics [54] bioinformatics,related [54] related,field [54] recommendations,#phdposition [54] #phdposition,#bioinformatics [38] field,recommendations [38] #bioinformatics,#researchers Top Word Pairs in Tweet in G7:
[51] #genomics,#raredisease [26] #bioinformatics,#womeninstem [24] #immunology,#genomics [22] inborn,error [22] error,immunity [20] #bioinformatics,#snrtg [20] #openscience,#scicomm [17] #itrtg,#openscience [17] #openscience,#snrtg [15] #iot,#openscience Top Word Pairs in Tweet in G8:
[17] practical,guide [16] marie,claude [16] claude,blatter [16] blatter,philippe [16] philippe,le [16] le,mercier [16] terri,attwood [13] #outreach,resources [13] resources,explain [13] explain,researchers Top Word Pairs in Tweet in G9:
[27] #mygnuhealth,#gnuhealth [27] #gnuhealth,personal [27] personal,health [27] health,record [27] record,improvements [27] improvements,matplotlib [27] matplotlib,plotting [27] plotting,imports [27] imports,#phr [27] #phr,#mhealth Top Word Pairs in Tweet in G10:
[6] virtual,rad [6] rad,seq [6] seq,data [6] data,analysis [6] analysis,workshop [6] workshop,13 [6] 13,16 [6] 16,september [6] september,open [6] open,virtual 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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Top Tweeters in G10: