The graph represents a network of 15,891 Twitter users whose recent tweets contained "#PPEShortage", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Sunday, 22 March 2020 at 20:55 UTC.
The tweets in the network were tweeted over the 2-day, 21-hour, 5-minute period from Thursday, 19 March 2020 at 22:29 UTC to Sunday, 22 March 2020 at 19:34 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 : 15891
Unique Edges : 25444
Edges With Duplicates : 2712
Total Edges : 28156
Number of Edge Types : 5
Replies to : 2751
MentionsInRetweet : 10371
Retweet : 10009
Mentions : 3176
Tweet : 1849
Self-Loops : 1894
Reciprocated Vertex Pair Ratio : 0.00323082445853775
Reciprocated Edge Ratio : 0.00644083969465649
Connected Components : 1075
Single-Vertex Connected Components : 687
Maximum Vertices in a Connected Component : 13886
Maximum Edges in a Connected Component : 25956
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 4.624551
Graph Density : 9.96087292128855E-05
Modularity : 0.777751
NodeXL Version : 1.0.1.427
Data Import : The graph represents a network of 15,891 Twitter users whose recent tweets contained "#PPEShortage", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Sunday, 22 March 2020 at 20:55 UTC.
The tweets in the network were tweeted over the 2-day, 21-hour, 5-minute period from Thursday, 19 March 2020 at 22:29 UTC to Sunday, 22 March 2020 at 19:34 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 : TwitterSearch
Graph Term : #PPEShortage
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:
[2017] front,line [1859] health,workers [1838] national,stockpile [1835] strategic,national [1833] line,health [1826] ppe,front [1825] workers,never [1821] wait,strategic [1821] stockpile,ppe [1821] never,mentioned Top Word Pairs in Tweet in G1:
[167] healthcare,workers [117] #ppeshortage,potus [116] #ppeshortage,#ppe [115] mess,presidents [115] presidents,stood [115] stood,allowed [115] allowed,90 [115] 90,drugs [115] drugs,goods [115] goods,made Top Word Pairs in Tweet in G2:
[1523] wait,strategic [1523] strategic,national [1523] national,stockpile [1523] stockpile,ppe [1523] ppe,front [1523] front,line [1523] line,health [1523] health,workers [1523] workers,never [1523] never,mentioned Top Word Pairs in Tweet in G3:
[255] healthcare,workers [203] masks,gowns [200] need,masks [200] gowns,#ppeshortage [199] need,thoughts [199] thoughts,prayers [199] prayers,need [143] hospitals,rationing [119] #ppeshortage,#covid19 [115] #ppeshortage,trending Top Word Pairs in Tweet in G4:
[712] masks,#ppeshortage [670] respond,projected [670] projected,covid [670] covid,19 [670] 19,outbreak [670] outbreak,heard [670] heard,health [670] health,care [670] care,providers [670] providers,reusing Top Word Pairs in Tweet in G5:
[483] trump,administration [483] administration,itself [483] itself,knew [483] knew,long [483] long,advance [483] advance,there'd [483] there'd,#ppeshortage [483] #ppeshortage,read [483] read,#crimsoncontagion [483] #crimsoncontagion,report Top Word Pairs in Tweet in G6:
[378] #ppeshortage,#millionmaskmayday [271] face,shields [232] need,masks [228] please,share [225] central,point [225] patterns,information [225] desperate,need [223] point,patterns [223] information,support [223] share,medical Top Word Pairs in Tweet in G7:
[333] #ppeshortage,#ppeisnotoptional [323] spent,afternoon [323] afternoon,many [323] many,hopkinsmedicine [323] hopkinsmedicine,colleagues [323] colleagues,making [323] making,#ppe [323] #ppe,staff [323] staff,sharing [323] sharing,permission Top Word Pairs in Tweet in G8:
[336] #ppeshortage,#givemeppe [303] calling,people [303] make,help [303] help,solve [303] solve,2020 [303] 2020,n95 [303] n95,type [303] type,mask [303] mask,shortage [302] amazing,resource Top Word Pairs in Tweet in G9:
[46] #ppe,#ppeshortage [35] #ppeshortage,#ppe [32] #covid19,#ppeshortage [29] healthcare,workers [28] #covid_19,#ppeshortage [25] #ppeshortage,#covid_19 [25] #ppeshortage,#ppenow [23] #ppeshortage,#ppeisnotoptional [21] face,masks [19] #ppeshortage,#covid19 Top Word Pairs in Tweet in G10:
[436] sadly,week [436] week,two [436] two,behind [436] behind,#italy [436] #italy,#coronavirusoutbreak [436] #coronavirusoutbreak,warned [436] warned,expect [436] expect,explosion [436] explosion,#coronavirus [436] #coronavirus,cases Top Replied-To in Entire Graph:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: