The graph represents a network of 8,757 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, 26 September 2020 at 12:59 UTC.
The requested start date was Saturday, 26 September 2020 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, 12-minute period from Wednesday, 23 September 2020 at 09:50 UTC to Friday, 25 September 2020 at 12:03 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 : 8757
Unique Edges : 6735
Edges With Duplicates : 9506
Total Edges : 16241
Number of Edge Types : 5
Retweet : 3551
MentionsInRetweet : 5305
Mentions : 3175
Tweet : 1966
Replies to : 2244
Self-Loops : 2024
Reciprocated Vertex Pair Ratio : 0.026084121291164
Reciprocated Edge Ratio : 0.0508420718144264
Connected Components : 1902
Single-Vertex Connected Components : 757
Maximum Vertices in a Connected Component : 3281
Maximum Edges in a Connected Component : 7575
Maximum Geodesic Distance (Diameter) : 31
Average Geodesic Distance : 11.293285
Graph Density : 0.000123128019805653
Modularity : 0.593918
NodeXL Version : 1.0.1.440
Data Import : The graph represents a network of 8,757 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, 26 September 2020 at 12:59 UTC.
The requested start date was Saturday, 26 September 2020 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, 12-minute period from Wednesday, 23 September 2020 at 09:50 UTC to Friday, 25 September 2020 at 12:03 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:
[1608] big,pharma [253] understanding,narendramodi [253] narendramodi,ji's [253] ji's,'make [253] 'make,india' [253] india',affordability [253] affordability,accessibility [253] accessibility,pandemic [252] chandrimaaitc,understanding [252] pandemic,ex Top Word Pairs in Tweet in G1:
[174] #jobs,#pharma [142] big,pharma [141] #pharma,#hiringnow [141] #hiringnow,#pharmiweb [38] covid,19 [33] #pharma,#hiring [29] sa,pharma [28] pharma,companies [28] abcam,#jobs [23] united,kingdom Top Word Pairs in Tweet in G2:
[134] big,pharma [34] clearly,dr [34] dr,#fauci [34] #fauci,being [34] being,challenged [34] challenged,tries [34] tries,smear [34] smear,#sweden [34] #sweden,tired [34] tired,old Top Word Pairs in Tweet in G3:
[134] big,pharma [38] achieve,world [38] world,government [38] government,necessary [38] necessary,remove [38] remove,minds [38] minds,men [38] men,individualism [38] individualism,loyalty [38] loyalty,family Top Word Pairs in Tweet in G4:
[253] understanding,narendramodi [253] narendramodi,ji's [253] ji's,'make [253] 'make,india' [253] india',affordability [253] affordability,accessibility [253] accessibility,pandemic [252] chandrimaaitc,understanding [252] pandemic,ex [2] increasing,costs Top Word Pairs in Tweet in G5:
[18] #worldpharmacistday2020,#pharmacist_transforming_global_health [17] #worldpharmacistday2020,pharma [14] pharma,clusters [14] bulk,drug [13] #gujarat,state [13] state,art [13] art,facilities [13] facilities,pharma [13] clusters,upcoming [13] upcoming,bulk Top Word Pairs in Tweet in G6:
[17] ordre_pharma,upso [17] upso,fspf_officiel [15] ocealab,ordre_pharma [9] aujourd,hui [8] par,gvallancien [8] gvallancien,olivierveran [7] #cham2020,ouverture [7] ouverture,l'édition [7] l'édition,2020 [7] 2020,#cham Top Word Pairs in Tweet in G7:
[161] joniernst,voted [161] voted,repeatedly [161] repeatedly,repeal [161] repeal,aca [161] aca,supports [161] supports,lawsuit [161] lawsuit,strip [161] strip,protections [161] protections,folks [160] greenfieldiowa,joniernst Top Word Pairs in Tweet in G8:
[14] #sunpharma,highest [14] highest,domestic [14] domestic,pharma [14] pharma,mkt [14] mkt,share [14] share,max [14] max,brands [14] brands,top [14] top,300 [14] 300,low Top Word Pairs in Tweet in G9:
[78] pharma's,campaign [78] campaign,pushing [78] pushing,vaccine [78] vaccine,mandate [78] mandate,bills [78] bills,50 [78] 50,states [78] states,form [78] form,lawfare [78] lawfare,using Top Word Pairs in Tweet in G10:
[58] becoming,clear [58] clear,government [58] government,scientific [58] scientific,advisers [58] advisers,conflict [58] conflict,interest [58] interest,funds [58] funds,research [58] research,big [57] oldcodger15,becoming Top Replied-To in Entire Graph:
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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: