The graph represents a network of 1,429 Twitter users whose tweets in the requested range contained "personalizedmedicine", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 07 January 2022 at 03:46 UTC.
The requested start date was Friday, 07 January 2022 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 96-day, 9-hour, 43-minute period from Friday, 01 October 2021 at 08:37 UTC to Wednesday, 05 January 2022 at 18:21 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 : 1429
Unique Edges : 1172
Edges With Duplicates : 2518
Total Edges : 3690
Number of Edge Types : 5
Retweet : 1039
MentionsInRetweet : 1665
Tweet : 407
Mentions : 555
Replies to : 24
Self-Loops : 474
Reciprocated Vertex Pair Ratio : 0.0524282560706402
Reciprocated Edge Ratio : 0.0996329313057158
Connected Components : 243
Single-Vertex Connected Components : 105
Maximum Vertices in a Connected Component : 529
Maximum Edges in a Connected Component : 1909
Maximum Geodesic Distance (Diameter) : 17
Average Geodesic Distance : 6.206601
Graph Density : 0.000934523564499278
Modularity : 0.502799
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 1,429 Twitter users whose tweets in the requested range contained "personalizedmedicine", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 07 January 2022 at 03:46 UTC.
The requested start date was Friday, 07 January 2022 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 96-day, 9-hour, 43-minute period from Friday, 01 October 2021 at 08:37 UTC to Wednesday, 05 January 2022 at 18:21 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 : personalizedmedicine
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:
[123] ai,transforming [123] transforming,healthcare [123] healthcare,those [123] those,changes [123] changes,happening [123] happening,inside [121] drgauravchandra,ai [119] inside,microbiome [119] microbiome,level [113] level,tak Top Word Pairs in Tweet in G1:
[122] ai,transforming [122] transforming,healthcare [122] healthcare,those [122] those,changes [122] changes,happening [122] happening,inside [121] drgauravchandra,ai [118] inside,microbiome [118] microbiome,level [113] level,tak Top Word Pairs in Tweet in G2:
[43] î,î [33] #personalizedmedicine,call [20] visit,website [16] call,today [14] learn,more [12] today,find [11] call,visit [11] website,find [11] wondering,#personalizedmedicine [11] thinking,#personalizedmedicine Top Word Pairs in Tweet in G3:
[46] analyse,twistbioscience [46] twistbioscience,whole [46] whole,exome [46] exome,sequencing [46] sequencing,kit [46] kit,fully [46] fully,automated [46] automated,seamless [46] seamless,ngs [46] ngs,platform Top Word Pairs in Tweet in G4:
[27] digital,health [26] #healthcareai,#smarthit [24] impacts,biomedical [24] biomedical,hashtag [24] hashtag,based [24] based,twitter [24] twitter,campaign [24] campaign,#dhpsp [24] #dhpsp,utilization [24] utilization,promotion Top Word Pairs in Tweet in G5:
[25] digital,solutions [25] solutions,cellular [25] cellular,gene [25] gene,therapy [25] therapy,#cell [25] #cell,#gene [25] #gene,therapies [25] therapies,part [25] part,#personalizedmedicine [24] irmaraste,digital Top Word Pairs in Tweet in G6:
[10] #bioinformatics,#personalizedmedicine [9] drug,discovery [8] genetics,podcast [8] #bioengineering,#drugdesign [8] #drugdesign,#bioinformatics [8] #bioinformatics,researchers [8] researchers,developed [8] developed,machine [8] machine,learning [8] learning,based Top Word Pairs in Tweet in G7:
[29] science,health [28] #personalizedmedicine,#sfh2021 [27] data,science [18] #datascience,#ai [18] #ai,#bigdata [17] learn,more [17] #event,#personalizedmedicine [16] #bigdata,#healthcare [16] #healthcare,#event [12] health,2021 Top Word Pairs in Tweet in G8:
[7] tragically,uneven [7] advances,#personalizedmedicine [6] pandemic's,tragically [6] uneven,impact [6] latest,article [6] article,permedcoalition [6] permedcoalition,discuss [6] discuss,potential [6] potential,exciting [6] exciting,advances Top Word Pairs in Tweet in G9:
[10] bostongene,nec_corp [10] nec_corp,formed [10] formed,global [10] global,partnership [10] partnership,aimed [10] aimed,accelerate [10] accelerate,commercialization [10] commercialization,adoption [10] precision,medicine [9] bostongenecorp,bostongene Top Word Pairs in Tweet in G10:
[7] although,#artificialintelligence [7] #artificialintelligence,#augmentedintelligence [7] #augmentedintelligence,both [7] both,effective [7] effective,enhancing [7] enhancing,quality [7] quality,care [7] care,offer [6] septweets,although [6] offer,differ Top Replied-To in Entire Graph:
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Top Replied-To in G7:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G10: