The graph represents a network of 8,715 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, 04 June 2022 at 12:18 UTC.
The requested start date was Saturday, 04 June 2022 at 00:01 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, 2-hour, 46-minute period from Wednesday, 01 June 2022 at 08:27 UTC to Friday, 03 June 2022 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 : 8715
Unique Edges : 4615
Edges With Duplicates : 10829
Total Edges : 15444
Number of Edge Types : 5
Retweet : 4816
MentionsInRetweet : 5505
Mentions : 2059
Tweet : 1789
Replies to : 1275
Self-Loops : 1824
Reciprocated Vertex Pair Ratio : 0.0169428642097452
Reciprocated Edge Ratio : 0.0333211723215372
Connected Components : 1673
Single-Vertex Connected Components : 667
Maximum Vertices in a Connected Component : 2351
Maximum Edges in a Connected Component : 4723
Maximum Geodesic Distance (Diameter) : 25
Average Geodesic Distance : 6.454662
Graph Density : 0.000108279275994433
Modularity : 0.55182
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 8,715 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, 04 June 2022 at 12:18 UTC.
The requested start date was Saturday, 04 June 2022 at 00:01 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, 2-hour, 46-minute period from Wednesday, 01 June 2022 at 08:27 UTC to Friday, 03 June 2022 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:
[1776] congress,action [1775] buys,congress [1711] big,pharma [892] insurance,companies [887] nra,buys [887] action,guns [887] guns,oil [887] oil,industry [887] industry,buys [887] action,climate Top Word Pairs in Tweet in G1:
[1758] congress,action [1757] buys,congress [878] nra,buys [878] action,guns [878] guns,oil [878] oil,industry [878] industry,buys [878] action,climate [878] climate,insurance [878] insurance,companies Top Word Pairs in Tweet in G2:
[110] big,pharma [33] pharma,company [24] fake,vaccine [23] vaccine,card [22] pharma,franchise [22] spanish,pharma [21] know,more [21] large,spanish [21] company,bought [21] bought,fake Top Word Pairs in Tweet in G3:
[337] coal,big [336] senator,kentucky [336] kentucky,16 [336] 16,years [336] years,old [336] old,54 [336] 54,bought [336] bought,paid [336] paid,nra [336] nra,coal Top Word Pairs in Tweet in G4:
[284] big,pharma [231] african,south [231] south,asian [231] asian,communities [231] communities,subjected [231] subjected,big [231] pharma,evil [231] evil,decades [231] decades,media [231] media,propagandists Top Word Pairs in Tweet in G5:
[240] parent,give [240] give,young [240] young,child [240] child,99 [240] 99,9999 [240] 9999,survival [240] survival,rate [240] rate,three [240] three,covid [240] covid,vaccine Top Word Pairs in Tweet in G6:
[15] big,pharma [9] pharma,company [8] gerarddelaney39,ceo [8] ceo,pharma [8] company,buy [8] buy,fake [8] fake,certificate [7] forrest_ursula,gerarddelaney39 [4] state,fake [4] fake,doctor Top Word Pairs in Tweet in G7:
[240] 大手製薬会社ceo,偽ワクチン接種で逮捕 [240] 偽ワクチン接種で逮捕,欧州製薬大手ファルママールのソウザ [240] 欧州製薬大手ファルママールのソウザ,ファロ社長は [240] ファロ社長は,生理食塩水 [240] 生理食塩水,接種済登録 [240] 接種済登録,に数千ドルを支払ったとして起訴された [240] に数千ドルを支払ったとして起訴された,この他 [240] この他,著名人2 [240] 著名人2,200名がリストアップされている [240] 200名がリストアップされている,彼らは Top Word Pairs in Tweet in G8:
[25] big,pharma [15] impfen,impfen [13] die,pharma [10] pharma,lobbyisten [8] immer,wieder [7] tag,mpk [7] pharma,lobbyist [7] c_lindner,_friedrichmerz [7] _friedrichmerz,cducsubt [7] cducsubt,immer Top Word Pairs in Tweet in G9:
[118] big,pharma [69] dare,big [69] pharma,first [68] timrunshismouth,dare [40] ridiculously,false [40] false,firearm [40] firearm,manufacturers [40] manufacturers,more [40] more,shielded [40] shielded,liability Top Word Pairs in Tweet in G10:
[102] pharma,companies [102] bought,fake [101] 200,prominent [101] prominent,spaniards [101] spaniards,including [101] including,leader [101] leader,one [101] one,country [101] country,largest [101] largest,pharma Top Replied-To in Entire Graph:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
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:
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: