The graph represents a network of 6,544 Twitter users whose recent tweets contained "Pharma", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/17/2023 5:00:36 PM. The network was obtained from Twitter on Saturday, 18 March 2023 at 12:11 UTC.
The tweets in the network were tweeted over the 1667-day, 3-hour, 37-minute period from Thursday, 23 August 2018 at 20:23 UTC to Saturday, 18 March 2023 at 00:00 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
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 : 6544
Unique Edges : 3434
Edges With Duplicates : 11352
Total Edges : 14786
Number of Edge Types : 9
Retweet : 3530
MentionsInRetweet : 4335
Replies to : 1633
MentionsInReplyTo : 3902
Tweet : 727
Quote : 183
Mentions : 296
MentionsInQuote : 136
MentionsInQuoteReply : 44
Self-Loops : 962
Reciprocated Vertex Pair Ratio : 0.0292063492063492
Reciprocated Edge Ratio : 0.0567550894509562
Connected Components : 769
Single-Vertex Connected Components : 165
Maximum Vertices in a Connected Component : 4056
Maximum Edges in a Connected Component : 10060
Maximum Geodesic Distance (Diameter) : 24
Average Geodesic Distance : 6.458697
Graph Density : 0.000189292239004188
Modularity : 0.533258
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 6,544 Twitter users whose recent tweets contained "Pharma", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/17/2023 5:00:36 PM. The network was obtained from Twitter on Saturday, 18 March 2023 at 12:11 UTC.
The tweets in the network were tweeted over the 1667-day, 3-hour, 37-minute period from Thursday, 23 August 2018 at 20:23 UTC to Saturday, 18 March 2023 at 00:00 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch2
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:
[2518] big,pharma [503] captured,big [496] hiding,fact [496] tube,hiding [496] ve,captured [496] fact,ve [495] mattletiss7,tube [291] ivermectin,trending [285] here's,thread [285] trending,shame Top Word Pairs in Tweet in G1:
[467] big,pharma [450] hiding,fact [450] captured,big [450] tube,hiding [450] ve,captured [450] fact,ve [449] mattletiss7,tube [16] health,edicts [16] public,health [15] concealing,info Top Word Pairs in Tweet in G2:
[152] big,pharma [47] abridgen,youtube [19] dominiquetaegon,abridgen [11] capture,steroids [11] jcvi,members [11] worse,uk [11] steroids,worse [11] uk,86 [11] agency,capture [11] budget,comes Top Word Pairs in Tweet in G3:
[256] thread,substack [256] trending,shame [256] participate,here's [256] ivermectin,trending [256] here's,thread [256] substack,documents [256] shame,participate [255] pierrekory,ivermectin [26] big,pharma [23] attacks,upon Top Word Pairs in Tweet in G4:
[98] finally,acknowledging [98] vaccine,injured [98] acknowledging,vaccine [98] vaccine,companies [98] giving,vaccine [98] injured,one's [98] apologizing,giving [98] one's,apologizing [98] experts,finally [97] marksteynonline,experts Top Word Pairs in Tweet in G5:
[179] twitter,files [177] release,covid [176] vaccine,truth [176] suppressed,headline [176] files,release [176] truth,being [176] covid,vaccine [176] paper,news [176] being,suppressed [176] headline,paper Top Word Pairs in Tweet in G6:
[153] big,pharma [111] cost,insulin [93] called,big [92] insulin,american [88] cut,cost [88] three,major [88] manufacturers,time [88] pharma,cut [88] american,three [88] major,manufacturers Top Word Pairs in Tweet in G7:
[115] big,pharma [30] pharma,against [29] against,claims [29] claims,participation [29] immunity,immunity [29] participation,roll [29] immunity,right [29] right,big [28] juneslater17,immunity [14] vigilantfox,robertkennedyjr Top Word Pairs in Tweet in G8:
[68] big,pharma [20] timcast,depopulation [20] illness,culture [20] pharma,mental [20] culture,normalizing [20] depopulation,dependance [20] mental,illness [20] lgbtq,exploiting [20] exploiting,children [20] normalizing,lgbtq Top Word Pairs in Tweet in G9:
[139] big,pharma [134] american,people [134] speaker,mccarthy [134] people,house [134] mccarthy,housegop [132] tonyhussein4,speaker [108] house,republicans [107] republicans,taken [107] choose,big [107] taken,total Top Word Pairs in Tweet in G10:
[67] big,pharma [7] pharma,mislead [7] paid,big [7] pharma,choice [7] くすりの仕事図鑑,gt [6] mislead,followers [6] covid,19 [5] social,media [5] influencers,paid [5] patient,influencers Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
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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:
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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:
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Top Tweeters in G9:
Top Tweeters in G10: