The graph represents a network of 9,668 Twitter users whose tweets in the requested range contained "Pharma", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 20 November 2021 at 12:58 UTC.
The requested start date was Saturday, 20 November 2021 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 2-day, 1-hour, 44-minute period from Wednesday, 17 November 2021 at 09:29 UTC to Friday, 19 November 2021 at 11:13 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 : 9668
Unique Edges : 6294
Edges With Duplicates : 10071
Total Edges : 16365
Number of Edge Types : 5
Mentions : 3026
Retweet : 4131
MentionsInRetweet : 5407
Replies to : 1927
Tweet : 1874
Self-Loops : 1947
Reciprocated Vertex Pair Ratio : 0.0197167755991285
Reciprocated Edge Ratio : 0.038671082149343
Connected Components : 2105
Single-Vertex Connected Components : 755
Maximum Vertices in a Connected Component : 3589
Maximum Edges in a Connected Component : 7673
Maximum Geodesic Distance (Diameter) : 30
Average Geodesic Distance : 11.446934
Graph Density : 0.000100159900610906
Modularity : 0.594441
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 9,668 Twitter users whose tweets in the requested range contained "Pharma", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 20 November 2021 at 12:58 UTC.
The requested start date was Saturday, 20 November 2021 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 2-day, 1-hour, 44-minute period from Wednesday, 17 November 2021 at 09:29 UTC to Friday, 19 November 2021 at 11:13 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 : Pharma
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:
[2892] big,pharma [229] pharma,industry [200] indian,pharma [190] journaliste,scientifique [190] scientifique,auteur [190] auteur,big [190] pharma,démasqué [190] s'attaque,question [169] question,discriminations [163] démasqué,xavierbazin2 Top Word Pairs in Tweet in G1:
[225] big,pharma [73] namo,app [41] pm,modi [40] #jobs,#pharma [38] #pharma,#hiring [31] र,म [30] kidney,liver [28] global,pharma [28] pharma,summit [27] covid,delta Top Word Pairs in Tweet in G2:
[196] big,pharma [188] journaliste,scientifique [188] scientifique,auteur [188] auteur,big [188] pharma,démasqué [188] s'attaque,question [168] question,discriminations [161] démasqué,xavierbazin2 [161] xavierbazin2,s'attaque [139] france_soir,journaliste Top Word Pairs in Tweet in G3:
[109] know,vaccine [109] vaccine,passports [109] passports,being [109] being,taken [109] taken,rapidly [109] rapidly,around [109] around,world [109] world,benefit [109] benefit,powerful [109] powerful,sectors Top Word Pairs in Tweet in G4:
[83] big,pharma [59] die,onze [59] onze,regering [59] over,corona [59] corona,virus [59] virus,beleid [59] beleid,heeft [59] heeft,belangenverstrengeling [59] belangenverstrengeling,met [59] met,pharma Top Word Pairs in Tweet in G5:
[183] indian,pharma [173] pharma,industry [149] two,requests [149] requests,indian [148] narendramodi,two [31] pharma,sector [23] combination,high [23] high,quality [23] quality,quantity [23] quantity,affordable Top Word Pairs in Tweet in G6:
[199] big,pharma [146] paid,big [74] people,trust [73] trust,tories [73] tories,labour [73] labour,msm [73] msm,wef [73] wef,sage [73] sage,doctors [73] doctors,paid Top Word Pairs in Tweet in G7:
[126] big,pharma [89] governments,lie [89] lie,time [89] time,media [89] media,lies [89] lies,time [89] time,big [89] pharma,make [89] make,money [89] money,time Top Word Pairs in Tweet in G8:
[51] big,pharma [39] draseemmalhotra,bad [39] bad,pharma [39] pharma,usual [39] usual,dirty [39] dirty,tricks [24] media,big [23] 'perfect,storm' [23] storm',interests [23] interests,media Top Word Pairs in Tweet in G9:
[94] big,pharma [60] pharma,spent [60] spent,263 [60] 263,million [60] million,lobbying [58] corporate,democrats [43] davidsirota,news [42] news,big [42] lobbying,documents [42] documents,show Top Word Pairs in Tweet in G10:
[35] pharma_mankind,_adilhussain [21] _adilhussain,deepika [19] nahi,chalta [19] chalta,hai [19] hai,message [19] message,pharma_mankind [19] deepika,narayan [19] narayan,bhardwaj [19] bhardwaj,company [19] company,discuss Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G8:
Top Replied-To in G9:
Top Replied-To in G10:
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 G8:
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:
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Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: