The graph represents a network of 6,597 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 2/10/2023 5:00:35 PM. The network was obtained from Twitter on Saturday, 11 February 2023 at 13:11 UTC.
The tweets in the network were tweeted over the 1854-day, 5-hour, 31-minute period from Saturday, 13 January 2018 at 19:29 UTC to Saturday, 11 February 2023 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 : 6597
Unique Edges : 3515
Edges With Duplicates : 11099
Total Edges : 14614
Number of Edge Types : 9
Retweet : 3547
MentionsInRetweet : 4494
MentionsInReplyTo : 3641
Replies to : 1607
Quote : 184
Tweet : 719
Mentions : 244
MentionsInQuote : 128
MentionsInQuoteReply : 50
Self-Loops : 931
Reciprocated Vertex Pair Ratio : 0.022087593083428
Reciprocated Edge Ratio : 0.0432205482835268
Connected Components : 784
Single-Vertex Connected Components : 206
Maximum Vertices in a Connected Component : 4093
Maximum Edges in a Connected Component : 10086
Maximum Geodesic Distance (Diameter) : 22
Average Geodesic Distance : 7.235925
Graph Density : 0.00018610182900087
Modularity : 0.544799
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 6,597 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 2/10/2023 5:00:35 PM. The network was obtained from Twitter on Saturday, 11 February 2023 at 13:11 UTC.
The tweets in the network were tweeted over the 1854-day, 5-hour, 31-minute period from Saturday, 13 January 2018 at 19:29 UTC to Saturday, 11 February 2023 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:
[2781] big,pharma [862] people,hundreds [833] insulin,35 [830] 35,month [828] make,big [826] insulin,costs [824] pharma,charges [824] 10,vial [823] vial,make [823] costs,10 Top Word Pairs in Tweet in G1:
[925] big,pharma [810] insulin,costs [809] make,big [808] people,hundreds [808] 10,vial [808] pharma,charges [808] insulin,35 [808] 35,month [807] anymore,capped [807] vial,make Top Word Pairs in Tweet in G2:
[117] big,pharma [18] covid,vaccine [18] vaccine,injury [17] dr,peter [17] mccullough,covid [17] p_mcculloughmd,rumblevideo [17] peter,mccullough [17] pharma,p_mcculloughmd [17] coming,big [17] lawsuits,coming Top Word Pairs in Tweet in G3:
[157] ordre_pharma,carinewolfthal [137] national,pharmaciens [137] mme,présidente [137] pharmaciens,ordre_pharma [137] présidente,l'ordre [137] l'ordre,national [135] amine_umlil,mme [124] carinewolfthal,procureur [124] procureur,république [123] république,d' Top Word Pairs in Tweet in G4:
[128] bitchute,dr [74] jeffreyatucker,brownstoneinst [64] dr,judy [64] big,pharma [64] judy,mikovits [64] brook,bitchute [64] tenpenny,bitchute [64] shawn,brook [64] dr,shawn [64] co,d0wrovhqo2 Top Word Pairs in Tweet in G5:
[246] works,pharma [123] cdc,works [123] pharma,healthy [123] fda,works [123] healthy,ignore [123] pharma,fda [122] ignore,adv [122] jedediahbila,cdc [61] won,give [61] 18,scheduled Top Word Pairs in Tweet in G6:
[73] big,pharma [51] gt,gt [27] carnivore,diet [16] know,big [15] diet,gt [15] never,hear [15] pharma,hopes [15] hear,carnivore [15] hopes,never [15] gt,works Top Word Pairs in Tweet in G7:
[66] bird,flu [65] h5n1,human [65] prepare,potential [65] tedros,prepare [65] human,bird [65] terrorist,continues [65] flu,pandemic [65] potential,h5n1 [65] continues,push [65] pandemic,terrorist Top Word Pairs in Tweet in G8:
[44] big,pharma [8] draseemmalhotra,doubledownnews [8] draseemmalhotra,drjbhattacharya [8] drjbhattacharya,rwmalonemd [7] dineshdsouza,draseemmalhotra [5] rwmalonemd,big [5] pharma,shill [4] doing,commercials [4] pharma,nothing [4] bullshit,product Top Word Pairs in Tweet in G9:
[121] big,pharma [116] pfizer,dod [116] operation,wasn [116] really,ran [116] pharma,cover [116] pfizer,big [116] covid,operation [116] wasn,pfizer [116] laralogan,really [116] dod,pfizer Top Word Pairs in Tweet in G10:
[45] big,pharma [11] catturd2,gatewaypundit [8] conspirators,fly [8] personal,security [8] protected,armed [8] security,guards [8] fly,private [8] armed,personal [8] private,jets [8] backtolife_2023,conspirators 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 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:
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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:
Top Tweeters in G4:
Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: