The graph represents a network of 9,385 Twitter users whose recent tweets contained "Lauterbach", 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 Monday, 13 March 2023 at 12:25 UTC.
The tweets in the network were tweeted over the 4-hour, 24-minute period from Monday, 13 March 2023 at 07:07 UTC to Monday, 13 March 2023 at 11:32 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 : 9385
Unique Edges : 23245
Edges With Duplicates : 16977
Total Edges : 40222
Number of Edge Types : 5
Retweet : 11426
Mentions : 10965
MentionsInRetweet : 7814
Replies to : 9193
Tweet : 824
Self-Loops : 878
Reciprocated Vertex Pair Ratio : 0.0121879803821097
Reciprocated Edge Ratio : 0.0240824444042669
Connected Components : 238
Single-Vertex Connected Components : 176
Maximum Vertices in a Connected Component : 8986
Maximum Edges in a Connected Component : 39792
Maximum Geodesic Distance (Diameter) : 12
Average Geodesic Distance : 3.059072
Graph Density : 0.000314015717704468
Modularity : 0.357364
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 9,385 Twitter users whose recent tweets contained "Lauterbach", 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 Monday, 13 March 2023 at 12:25 UTC.
The tweets in the network were tweeted over the 4-hour, 24-minute period from Monday, 13 March 2023 at 07:07 UTC to Monday, 13 March 2023 at 11:32 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 : Lauterbach
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 : In-Degree
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[1952] heutejournal,karl_lauterbach [1921] 10,000 [1149] karl,lauterbach [675] drpuerner,karl_lauterbach [655] haut,retten [573] exorbitante,gewinne [545] nebenwirkungsfreie,impfung [523] la,santé [522] schwere,nebenwirkungen [515] ministre,la Top Word Pairs in Tweet in G1:
[661] 10,000 [386] heutejournal,karl_lauterbach [329] karl,lauterbach [327] nebenwirkungsfreie,impfung [233] schwere,nebenwirkungen [191] völlig,normal [188] impfung,tweet [186] tweet,gelöscht [185] kopf,kragen [173] zahlen,#impfschäden Top Word Pairs in Tweet in G2:
[145] doc_ecmo,karl_lauterbach [94] 10,000 [74] heutejournal,karl_lauterbach [69] verhöhnung,volkes [56] exorbitante,gewinne [50] karl,lauterbach [49] karl_lauterbach,volk [48] drecks,aufzukommen [48] bigpharma,exorbitante [48] straße,saßen Top Word Pairs in Tweet in G3:
[1301] heutejournal,karl_lauterbach [169] karl_lauterbach,programm [167] appelliert,impfhersteller [167] impfhersteller,beteiligen [167] gewinne,exorbitant [166] unterstützung,geste [166] exorbitant,finanzielle [166] beteiligen,gewinne [166] weiterhin,appelliert [166] aufzulegen,weiterhin Top Word Pairs in Tweet in G4:
[464] 10,000 [198] #lauterbach,risiko [198] 250,credit [198] dunkelziffer,dosen [198] 000,dunkelziffer [198] spielt,#lauterbach [198] ministerium,000 [198] 000,spielt [198] herunter,ministerium [198] risiko,schwerer Top Word Pairs in Tweet in G5:
[575] drpuerner,karl_lauterbach [138] 10,000 [112] karl_lauterbach,klar [106] mehrere,tausend [106] haut,retten [104] impfung,enden [104] impfopfer,aufgrund [104] verantworten,impfung [104] retten,verantwortlich [104] amp,hinterbliebenen Top Word Pairs in Tweet in G6:
[507] la,santé [507] ministre,la [397] effets,secondaires [381] #lauterbach,#macron [381] #macron,#mckinsey [381] super,profits [381] #pfizerbiontech,#lauterbach [381] #pfizer,#pfizerbiontech [379] #mckinsey,quand [379] coûts,#pfizer Top Word Pairs in Tweet in G7:
[182] lauterbach,definitiv [182] verantwortung,bundesministerium [182] herrn,lauterbach [182] bundesministerium,tragen [181] #deshalbafd,#afd [181] #lauterbach,#lauterbachluegt [181] definitiv,verantwortung [181] erfinden,argumentation [181] untermauern,scheint [181] argumentation,untermauern Top Word Pairs in Tweet in G8:
[219] 10,000 [193] 100k,doses [156] karl_lauterbach,heutejournal [90] karl,lauterbach [88] serious,adverse [88] adverse,events [87] million,doses [87] reported,10 [87] total,of [87] states,serious Top Word Pairs in Tweet in G9:
[340] karl,lauterbach [305] haut,retten [301] biontech,exorbitante [301] schwer,geschädigt [300] geschädigt,biontech [300] exorbitante,gewinne [300] impfung,beerdigt [300] lauterbach,soeben [300] plottwist,haut [300] absolut,bestürzende Top Word Pairs in Tweet in G10:
[112] karl_lauterbach,marcobuschmann [46] lisapaus,karl_lauterbach [34] bundeskanzler,karl_lauterbach [31] kindertransition,reue [31] bmwk,hubertus_heil [31] irreversibel,geschädigt [31] jugendliche,irreversibel [31] geschädigt,lisapaus [31] deutschland,kinder [31] pionierin,medizinischen 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: