The graph represents a network of 4,833 Twitter users whose recent tweets contained "#BioTech", 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 Thursday, 16 January 2020 at 19:25 UTC.
The tweets in the network were tweeted over the 8-day, 3-hour, 0-minute period from Wednesday, 08 January 2020 at 15:33 UTC to Thursday, 16 January 2020 at 18:33 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 : 4833
Unique Edges : 7635
Edges With Duplicates : 5180
Total Edges : 12815
Number of Edge Types : 5
Retweet : 2679
Mentions : 2101
MentionsInRetweet : 4835
Tweet : 3053
Replies to : 147
Self-Loops : 3483
Reciprocated Vertex Pair Ratio : 0.0122177954847278
Reciprocated Edge Ratio : 0.0241406454998688
Connected Components : 944
Single-Vertex Connected Components : 492
Maximum Vertices in a Connected Component : 2653
Maximum Edges in a Connected Component : 9696
Maximum Geodesic Distance (Diameter) : 21
Average Geodesic Distance : 6.881003
Graph Density : 0.000326381266760119
Modularity : 0.567911
NodeXL Version : 1.0.1.423
Data Import : The graph represents a network of 4,833 Twitter users whose recent tweets contained "#BioTech", 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 Thursday, 16 January 2020 at 19:25 UTC.
The tweets in the network were tweeted over the 8-day, 3-hour, 0-minute period from Wednesday, 08 January 2020 at 15:33 UTC to Thursday, 16 January 2020 at 18:33 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 : #BioTech
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:
[3567] gt,gt [1097] gt,#strategy [1097] #strategy,#competitiveintelligence [1097] #competitiveintelligence,#marketing [668] cell,therapy [646] gene,cell [644] therapy,gt [641] gt,published [613] #lucidquest,#followthepatient [613] #followthepatient,#genetherapy Top Word Pairs in Tweet in G1:
[44] #pharma,#biotech [30] #biotech,#pharma [19] #biotech,#healthcare [17] learn,more [16] #biotech,#cancer [14] #vaccine,#smallcap [14] #smallcap,#biotech [12] #science,#biotech [11] san,francisco [11] #biotech,#science Top Word Pairs in Tweet in G2:
[93] #biotech,#pharma [79] #biospace,#lifesciences [79] #lifesciences,#biotech [38] healthcare,conference [28] jpmorgan,healthcare [28] #biotech,#healthcare [24] #jpm20,#biotech [22] #genomics,#genetics [22] #jpm2020,#jpm20 [21] vista,partners Top Word Pairs in Tweet in G3:
[396] gt,gt [128] #biotech,#fintech [93] chboursin,julez_norton [91] equations,changed [91] changed,world [91] world,wef [91] wef,#ai [91] #ai,#bigdata [91] #bigdata,#biotech [91] #fintech,#maths Top Word Pairs in Tweet in G4:
[2822] gt,gt [1093] gt,#strategy [1093] #strategy,#competitiveintelligence [1093] #competitiveintelligence,#marketing [656] cell,therapy [638] therapy,gt [637] gene,cell [635] gt,published [607] #lucidquest,#followthepatient [607] #followthepatient,#genetherapy Top Word Pairs in Tweet in G5:
[41] #bioengineering,#biotech [12] marché,2020 [12] l'echo,#biotech [12] journal,l'action [12] l'action,régionale [12] thesneaklife,#biotech [10] 2020,26 [10] marché,2017 [10] 2017,2026 [10] dernières,actualités Top Word Pairs in Tweet in G6:
[16] cell,gene [13] gene,therapy [10] #pharma,#biotech [9] upfront,plus [9] companies,co [9] co,commercialize [9] #biotech,#cgtmanufacturing [8] series,round [7] german,#biotech [7] #biotech,morphosys Top Word Pairs in Tweet in G7:
[69] agroécologistes,militants [51] plantes,#biotech [51] #biotech,service [51] service,#santé [51] #santé,végétal [51] végétal,environnement [51] par,catherine [51] catherine,regnault [51] regnault,roger [50] #biotech,#phytos Top Word Pairs in Tweet in G8:
[140] #science,#biotech [137] #smartlabequipment,#smartlaboratory [137] #smartlaboratory,#haas [137] #haas,#microbiologylab [137] #microbiologylab,#microbiology [137] #microbiology,#science [137] #biotech,# [137] #,startup [134] startup,#hardinscientific [29] #aatf,#prosperitythroughtechnology Top Word Pairs in Tweet in G9:
[48] #pharma,#biotech [21] #biotech,#igniton [21] #igniton,#grant [19] handmade,bacteriophage [19] bacteriophage,thats [19] thats,#scientists [19] #scientists,see [19] see,work [19] work,best [19] best,way Top Word Pairs in Tweet in G10:
[54] #biotech,#genomics [42] #crispr,#biotech [40] very,comprehensive [40] comprehensive,review [40] review,dna [40] dna,editing [40] editing,technology [40] technology,genetic [40] genetic,disorders [40] disorders,curative 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 G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
Top Tweeters in G2:
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Top Tweeters in G7:
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Top Tweeters in G9:
Top Tweeters in G10: