The graph represents a network of 6,947 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 12/30/2022 5:00:35 PM. The network was obtained from Twitter on Saturday, 31 December 2022 at 13:11 UTC.
The tweets in the network were tweeted over the 1785-day, 8-hour, 17-minute period from Friday, 09 February 2018 at 16:42 UTC to Saturday, 31 December 2022 at 01:00 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 : 6947
Unique Edges : 3690
Edges With Duplicates : 11706
Total Edges : 15396
Number of Edge Types : 9
Retweet : 3508
MentionsInRetweet : 4216
Tweet : 807
Replies to : 1752
MentionsInReplyTo : 4393
Quote : 173
Mentions : 259
MentionsInQuote : 207
MentionsInQuoteReply : 81
Self-Loops : 1059
Reciprocated Vertex Pair Ratio : 0.0290159278923324
Reciprocated Edge Ratio : 0.0563954883609311
Connected Components : 855
Single-Vertex Connected Components : 190
Maximum Vertices in a Connected Component : 3912
Maximum Edges in a Connected Component : 9730
Maximum Geodesic Distance (Diameter) : 19
Average Geodesic Distance : 6.379676
Graph Density : 0.000172711564516846
Modularity : 0.531642
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 6,947 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 12/30/2022 5:00:35 PM. The network was obtained from Twitter on Saturday, 31 December 2022 at 13:11 UTC.
The tweets in the network were tweeted over the 1785-day, 8-hour, 17-minute period from Friday, 09 February 2018 at 16:42 UTC to Saturday, 31 December 2022 at 01:00 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:
[2200] big,pharma [626] two,thirds [626] thirds,congress [626] house,representatives [625] congress,72 [625] representatives,members [625] 2020,more [625] 72,senators [625] more,two [625] cashed,campaign Top Word Pairs in Tweet in G1:
[550] two,thirds [550] thirds,congress [549] cashed,campaign [549] 72,senators [549] campaign,check [549] 2020,more [549] members,cashed [549] senators,302 [549] congress,72 [549] representatives,members Top Word Pairs in Tweet in G2:
[259] big,pharma [228] pharma,govt [227] agencies,equally [227] fraud,racketeering [227] govt,agencies [227] racketeering,collusion [227] equally,culpable [227] charges,fraud [227] explain,big [227] culpable,charges Top Word Pairs in Tweet in G3:
[81] big,pharma [10] elonmusk,pmarca [10] pharma,big [9] more,dangerous [8] receive,covid [8] bombshell,conclusions [8] malhotra,more [8] conclusions,leading [8] cardiologist,dr [8] dr,aseem Top Word Pairs in Tweet in G4:
[232] robert,kennedy [232] kennedy,jr [230] jr,media [230] extension,pharmaceutical [230] 75,advertising [230] backtolife_2023,robert [230] industry,75 [230] advertising,revenues [230] pharmaceutical,industry [230] media,extension Top Word Pairs in Tweet in G5:
[97] big,pharma [49] captured,big [48] system,captured [48] lot,money [48] vaccines,buys [48] awful,lot [48] health,system [48] making,awful [48] money,vaccines [48] pharma,making Top Word Pairs in Tweet in G6:
[80] big,pharma [9] big,chain [8] opioid,epidemic [8] pharma,companies [7] stop,bloody [7] tragedy,under [7] pharma,industriels [7] economic,ass [7] fooled,more [7] one,largest Top Word Pairs in Tweet in G7:
[183] big,pharma [115] pharma,doesn [115] need,dependent [115] doesn,healthy [115] healthy,need [114] gunthereagleman,big [28] funded,sickness [28] pharma,funded [28] don,expect [28] sickness,don Top Word Pairs in Tweet in G8:
[174] big,pharma [170] more,see [170] willing,kill [170] pharma,profit [170] people,big [170] time,willing [170] countless,people [170] kill,countless [170] profit,more [170] see,hague Top Word Pairs in Tweet in G9:
[71] big,pharma [18] ll,take [18] assessment,test [18] racebaiting,big [18] limitations,over [18] over,racebaiting [18] test,limitations [18] tests,assessment [18] inventor,tests [18] take,inventor Top Word Pairs in Tweet in G10:
[116] adverse,events [116] pfizer,lot [116] en6201,nearly [116] events,211 [116] lot,en6201 [116] nearly,4000 [116] reports,deaths [116] 211,reports [116] reports,adverse [116] deaths,cdc's Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: