The graph represents a network of 9,073 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, 09 April 2022 at 12:11 UTC.
The requested start date was Saturday, 09 April 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, 20-minute period from Tuesday, 05 April 2022 at 08:53 UTC to Thursday, 07 April 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 : 9073
Unique Edges : 6236
Edges With Duplicates : 9898
Total Edges : 16134
Number of Edge Types : 5
Replies to : 1769
Mentions : 3053
Retweet : 3958
MentionsInRetweet : 5289
Tweet : 2065
Self-Loops : 2110
Reciprocated Vertex Pair Ratio : 0.0230307076101469
Reciprocated Edge Ratio : 0.0450244698205546
Connected Components : 2049
Single-Vertex Connected Components : 823
Maximum Vertices in a Connected Component : 2599
Maximum Edges in a Connected Component : 6074
Maximum Geodesic Distance (Diameter) : 46
Average Geodesic Distance : 15.576333
Graph Density : 0.00011171147371963
Modularity : 0.593012
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 9,073 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, 09 April 2022 at 12:11 UTC.
The requested start date was Saturday, 09 April 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, 20-minute period from Tuesday, 05 April 2022 at 08:53 UTC to Thursday, 07 April 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:
[1921] big,pharma [697] ãƒ,ム[281] purdue,pharma [278] pharma,giant [277] sold,pharma [276] vaccine,centre [274] uk,vaccine [272] government,sold [247] ø,ù [232] centre,215m Top Word Pairs in Tweet in G1:
[164] î,î [154] big,pharma [101] ãƒ,ム[60] ø,ù [58] ù,ø [56] ø,ø [34] job,alert [34] apply,#pharmajobs [34] #pharmajobs,#jobsearch [34] #jobsearch,#pharma Top Word Pairs in Tweet in G2:
[74] die,pharma [72] deutschland,einziges [72] einziges,land [72] land,die [71] die,impfpflicht [70] impfpflicht,trotz [63] trotz,impfschã [52] impfschã,todesfã [51] todesfã,lle [50] lle,einige Top Word Pairs in Tweet in G3:
[316] big,pharma [172] pr,raoult [172] raoult,dã [172] dã,nonce [172] nonce,fraudes [172] fraudes,big [172] pharma,rentabilitã [172] rentabilitã,financiã [172] financiã,re [172] re,l'industrie Top Word Pairs in Tweet in G4:
[229] purdue,pharma [228] vance,blames [228] blames,mexicans [228] mexicans,mother's [228] mother's,drug [228] drug,addiction [228] addiction,except [228] except,addicted [228] addicted,oxycontin [228] oxycontin,produced Top Word Pairs in Tweet in G5:
[229] uk,vaccine [229] vaccine,centre [229] government,sold [229] sold,pharma [229] pharma,giant [226] centre,215m [226] 215m,government [225] danbloom1,uk [3] danbloom1,attractive [3] attractive,'us Top Word Pairs in Tweet in G6:
[131] #gesetzderschande,betrifft [131] betrifft,impfgegner [131] impfgegner,sonder [131] sonder,alle [131] alle,ermã [131] ermã,chtigt [131] chtigt,gesundheitsminister [130] deframing23,#gesetzderschande [125] gesundheitsminister,entscheiden [124] entscheiden,wasâ Top Word Pairs in Tweet in G7:
[147] big,pharma [114] payments,big [112] aussie,medicos [112] medicos,over [112] over,11 [112] 11,million [112] million,payments [112] pharma,past [112] past,year [112] year,many Top Word Pairs in Tweet in G8:
[114] big,pharma [95] raoult_didier,big [94] #sudradio,andrebercoff [94] andrebercoff,raoult_didier [94] pharma,l'industrie [94] l'industrie,plus [94] plus,corrompue [94] corrompue,monde [94] monde,banques [93] sudradio,#sudradio Top Word Pairs in Tweet in G9:
[127] 95,americans [127] americans,antibodies [127] antibodies,according [127] according,cdc [127] cdc,survival [127] survival,rate [127] rate,healthy [127] healthy,kids [127] kids,99 [127] 99,9999 Top Word Pairs in Tweet in G10:
[56] met,health [56] health,minister [56] minister,ethiopia [56] ethiopia,dr [56] dr,lia_tadesse [56] lia_tadesse,gavi [56] gavi,board [56] board,meeting [56] meeting,evian [56] evian,france 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 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:
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: