The graph represents a network of 6,305 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 1/13/2023 5:00:34 PM. The network was obtained from Twitter on Saturday, 14 January 2023 at 13:10 UTC.
The tweets in the network were tweeted over the 1145-day, 8-hour, 19-minute period from Monday, 25 November 2019 at 16:41 UTC to Saturday, 14 January 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 : 6305
Unique Edges : 4408
Edges With Duplicates : 10951
Total Edges : 15359
Number of Edge Types : 9
Retweet : 3763
MentionsInRetweet : 5856
Replies to : 1448
MentionsInReplyTo : 3176
Tweet : 627
Quote : 160
MentionsInQuote : 93
Mentions : 201
MentionsInQuoteReply : 35
Self-Loops : 795
Reciprocated Vertex Pair Ratio : 0.0164044943820225
Reciprocated Edge Ratio : 0.0322794605350431
Connected Components : 621
Single-Vertex Connected Components : 118
Maximum Vertices in a Connected Component : 4313
Maximum Edges in a Connected Component : 11761
Maximum Geodesic Distance (Diameter) : 18
Average Geodesic Distance : 5.872845
Graph Density : 0.00022759110688882
Modularity : 0.557314
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 6,305 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 1/13/2023 5:00:34 PM. The network was obtained from Twitter on Saturday, 14 January 2023 at 13:10 UTC.
The tweets in the network were tweeted over the 1145-day, 8-hour, 19-minute period from Monday, 25 November 2019 at 16:41 UTC to Saturday, 14 January 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:
[2223] big,pharma [519] pharma,money [508] reveals,corrupt [508] business,practices [508] money,incentive [508] practices,big [508] 2022,chris [508] exec,reveals [508] cole,us_fda [508] us_fda,exec Top Word Pairs in Tweet in G1:
[508] big,pharma [491] us_fda,exec [491] business,practices [491] feb,2022 [491] practices,big [491] money,incentive [491] exec,reveals [491] chris,cole [491] corrupt,business [491] cole,us_fda Top Word Pairs in Tweet in G2:
[360] kathryn,edwards [360] pharma,shill [359] role,model [359] industry,corruption [359] edwards,role [359] vaccinology,pfizer [359] hired,pharma [359] goddess,vaccinology [359] pfizer,hired [359] dark,goddess Top Word Pairs in Tweet in G3:
[327] pharma,industry [319] industry,spot [319] industry,knocked [319] take,trusted [319] public,still [319] trusted,industry [319] knocked,tech [319] tech,take [319] still,clueless [319] yeh,public Top Word Pairs in Tweet in G4:
[332] upitt,pharma [331] lindsay,heck [330] lindsay,loved [330] student,lindsay [330] pharma,student [329] years,old [329] students,doing [329] 25,years [329] #diedsuddenly,25 [329] teaching,students Top Word Pairs in Tweet in G5:
[313] big,pharma [264] pink,michaelphelps [264] charlieputh,questlove [264] questlove,pink [254] pharma,gt [254] much,cost [254] yourself,big [254] sell,yourself [254] michaelphelps,much [254] cost,sell Top Word Pairs in Tweet in G6:
[105] big,pharma [29] year,old [27] lindsay,heck [27] pharma,student [27] lindsay,loved [27] upitt,pharma [27] student,lindsay [26] heart,attack [25] father,died [25] old,upitt Top Word Pairs in Tweet in G7:
[89] médias,mensongers [89] mince,complotistes [89] cela,sera [89] virer,tous [89] temps,virer [89] complotistes,avaient [89] sera,premie [89] avaient,encore [89] tous,médias [89] encore,raison Top Word Pairs in Tweet in G8:
[52] big,pharma [36] mrna,injections [36] description,mrna [36] admit,pharma's [36] thomas_binder,admit [36] best,minute [36] dr,thomas_binder [36] injections,dr [36] video,description [36] minute,video Top Word Pairs in Tweet in G9:
[49] big,pharma [15] covid,19 [11] 19,vaccine [10] removed,over [10] over,telling [10] truth,covid [10] vaccine,statements [10] bridgen,whip [10] telling,truth [10] whip,removed Top Word Pairs in Tweet in G10:
[68] big,pharma [64] truth,emerging [64] uk,doctors [64] call,government [64] government,investigation [64] c19,vaccines [64] government,mp [64] doctors,call [64] emerging,government [64] investigation,c19 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:
Top Mentioned in G3:
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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:
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Top Tweeters in G7:
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Top Tweeters in G9:
Top Tweeters in G10: