The graph represents a network of 4,296 Twitter users whose recent tweets contained "Nuhr", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 5,000 tweets. The network was obtained from Twitter on Thursday, 12 March 2020 at 09:02 UTC.
The tweets in the network were tweeted over the 9-day, 5-hour, 2-minute period from Tuesday, 03 March 2020 at 03:50 UTC to Thursday, 12 March 2020 at 08:52 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.
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Author Description
Vertices : 4296
Unique Edges : 5265
Edges With Duplicates : 707
Total Edges : 5972
Number of Edge Types : 5
Retweet : 1994
Tweet : 858
Replies to : 1896
Mentions : 941
MentionsInRetweet : 283
Self-Loops : 876
Reciprocated Vertex Pair Ratio : 0.0112098138747885
Reciprocated Edge Ratio : 0.0221710939134072
Connected Components : 581
Single-Vertex Connected Components : 373
Maximum Vertices in a Connected Component : 3295
Maximum Edges in a Connected Component : 4907
Maximum Geodesic Distance (Diameter) : 17
Average Geodesic Distance : 4.726938
Graph Density : 0.000259114253072409
Modularity : 0.709558
NodeXL Version : 1.0.1.426
Data Import : The graph represents a network of 4,296 Twitter users whose recent tweets contained "Nuhr", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 5,000 tweets. The network was obtained from Twitter on Thursday, 12 March 2020 at 09:02 UTC.
The tweets in the network were tweeted over the 9-day, 5-hour, 2-minute period from Tuesday, 03 March 2020 at 03:50 UTC to Thursday, 12 March 2020 at 08:52 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 : Nuhr
Groups : The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.
Edge Color : Language
Edge Width : Edge Weight
Edge Alpha : Edge Weight
Vertex Color : Language by Count
Vertex Radius : In-Degree
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[1616] dieter,nuhr [352] #nuhr,echt [351] herr,nuhr [344] großartige,#gruber [344] #gruber,liest [344] liest,linksgrünradikalen [344] linksgrünradikalen,bessermenschen [344] bessermenschen,leviten [344] leviten,wirft [344] wirft,wahrnehmungsstörungen Top Word Pairs in Tweet in G1:
[249] dieter,nuhr [230] herr,nuhr [82] dieternuhr,herr [78] dieternuhr,nuhr [47] zahlen,deutschland [47] deutschland,angesehen [47] angesehen,besorgt [47] besorgt,derzeit [47] derzeit,dieternuhr [47] dieternuhr,klingt Top Word Pairs in Tweet in G2:
[152] dieter,nuhr [19] dieter,#nuhr [12] corona,tweet [10] herr,nuhr [8] xavier,naidoo [8] wütende,kommentare [7] einfach,fresse [7] einfach,auftreten [7] tweet,kabarettist [6] gerne,einfach Top Word Pairs in Tweet in G3:
[332] großartige,#gruber [332] #gruber,liest [332] liest,linksgrünradikalen [332] linksgrünradikalen,bessermenschen [332] bessermenschen,leviten [332] leviten,wirft [332] wirft,wahrnehmungsstörungen [332] wahrnehmungsstörungen,grund [332] grund,#nuhr [332] #nuhr,echt Top Word Pairs in Tweet in G4:
[199] dieter,nuhr [158] grund,sorge [158] sorge,kabarettabend [158] kabarettabend,dieter [158] nuhr,fühlt [158] fühlt,allermeisten [158] allermeisten,betroffenen [158] betroffenen,lediglich [158] lediglich,gewöhnliche [158] gewöhnliche,schwere Top Word Pairs in Tweet in G5:
[84] saudummen,tweet [83] #nuhr,gesehen [83] gesehen,pardon [83] pardon,saudummen [83] tweet,zugetraut [83] zugetraut,scheint [83] scheint,virus [83] virus,erfasst [83] erfasst,bürgerliche [83] bürgerliche,trotzköpfigkeit Top Word Pairs in Tweet in G6:
[62] dieter,#nuhr [49] veranstaltungen,absagen [49] expert,innen [48] absagen,#corona [48] #corona,panik [48] panik,geraten [48] geraten,dieter [48] #nuhr,auftritt [48] auftritt,wochenende [48] wochenende,besuchen Top Word Pairs in Tweet in G7:
[63] hört,nuhr [58] italien,todesrate [58] todesrate,südkorea [58] südkorea,nächste [58] nächste,woche [58] woche,kritisch [58] kritisch,#coronadeutschland [58] #coronadeutschland,hohe [58] hohe,todesrate [58] todesrate,überlastung Top Word Pairs in Tweet in G8:
[109] dieter,nuhr [72] nuhr,einfach [72] einfach,komplette [72] komplette,proto [72] proto,boomer [72] boomer,leben [72] leben,geschenkt [72] geschenkt,widerspruch [72] widerspruch,erfahren [72] erfahren,hält Top Word Pairs in Tweet in G9:
[76] dieter,nuhr [24] nuhr,triggert [24] triggert,bloß [24] bloß,blöd [24] blöd,rum [24] rum,schlicht [24] schlicht,guten [24] guten,witzen [24] witzen,viral [19] gehalten,wünschen Top Word Pairs in Tweet in G10:
[83] dieter,nuhr [35] monat,aussehen [35] aussehen,italien [35] italien,bekämen [35] bekämen,schwerkranke [35] schwerkranke,kinder [35] kinder,betten [35] betten,pflege [35] pflege,intensivstationen [35] intensivstationen,dieter Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
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Top Mentioned in G6:
Top Mentioned in G7:
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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:
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Top Tweeters in G10: