The graph represents a network of 1,753 Twitter users whose tweets in the requested range contained "sackler", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Sunday, 16 June 2019 at 12:38 UTC.
The requested start date was Sunday, 16 June 2019 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 0-hour, 23-minute period from Sunday, 02 June 2019 at 00:02 UTC to Saturday, 15 June 2019 at 00:26 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 : 1753
Unique Edges : 1719
Edges With Duplicates : 181
Total Edges : 1900
Number of Edge Types : 3
Replies to : 193
Mentions : 1414
Tweet : 293
Self-Loops : 293
Reciprocated Vertex Pair Ratio : 0.00783289817232376
Reciprocated Edge Ratio : 0.0155440414507772
Connected Components : 367
Single-Vertex Connected Components : 152
Maximum Vertices in a Connected Component : 313
Maximum Edges in a Connected Component : 315
Maximum Geodesic Distance (Diameter) : 15
Average Geodesic Distance : 3.581806
Graph Density : 0.000502725920600562
Modularity : 0.828591
NodeXL Version : 1.0.1.413
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[330] sackler,family [330] opioid,epidemic [314] fueling,opioid [309] create,oxycontin [309] new,drug [308] 1,create [308] oxycontin,filthy [308] filthy,rich [308] rich,fueling [308] epidemic,2 Top Word Pairs in Tweet in G1:
[307] 1,create [307] create,oxycontin [307] oxycontin,filthy [307] filthy,rich [307] rich,fueling [307] fueling,opioid [307] opioid,epidemic [307] epidemic,2 [307] 2,develop [307] develop,new Top Word Pairs in Tweet in G2:
[56] ð,ð [49] sackler,family [21] purdue,pharma [21] ð,ñ [15] ñ,ð [13] david,sackler [12] richard,sackler [10] new,jersey [10] opioid,crisis [9] freer,sackler Top Word Pairs in Tweet in G3:
[130] 1st,century [65] gold,amulet [65] amulet,goddess [65] goddess,lat [65] lat,dates [65] dates,1st [65] century,bce [65] bce,mid [65] mid,1st [65] century,ce Top Word Pairs in Tweet in G4:
[56] purdue,pharma [38] sackler,family [22] lawsuits,against [22] against,purdue [22] pharma,named [22] named,members [22] s,controlling [22] controlling,sackler [22] family,come [22] come,under Top Word Pairs in Tweet in G5:
[38] richard,sackler [37] dr,richard [33] purdue,pharma [22] re,suing [22] suing,dr [22] sackler,purdue [22] pharma,role [22] role,#opioidcrisis [22] #opioidcrisis,devastating [22] devastating,communities Top Word Pairs in Tweet in G6:
[2] sackler,family Top Word Pairs in Tweet in G9:
[38] purdue,pharma [38] richard,sackler [37] #breaking,dc [37] dc,suing [37] suing,purdue [37] pharma,richard [37] sackler,misleading [37] misleading,patients [37] patients,doctors [37] doctors,communities Top Word Pairs in Tweet in G10:
[27] sackler,family [18] tel,aviv [18] aviv,university [18] university,refuses [18] refuses,reject [18] reject,donations [18] donations,sackler [18] family,embroiled [18] embroiled,opioids [18] opioids,crisis 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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