The graph represents a network of 12,592 Twitter users whose recent tweets contained "1238780849652465664", 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 Wednesday, 18 March 2020 at 09:04 UTC.
The tweets in the network were tweeted over the 3-day, 21-hour, 17-minute period from Saturday, 14 March 2020 at 10:55 UTC to Wednesday, 18 March 2020 at 08:13 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 : 12592
Unique Edges : 13472
Edges With Duplicates : 226
Total Edges : 13698
Number of Edge Types : 5
Retweet : 11774
Tweet : 702
MentionsInRetweet : 904
Mentions : 184
Replies to : 134
Self-Loops : 706
Reciprocated Vertex Pair Ratio : 0.000232270052647879
Reciprocated Edge Ratio : 0.000464432231596873
Connected Components : 503
Single-Vertex Connected Components : 407
Maximum Vertices in a Connected Component : 11903
Maximum Edges in a Connected Component : 13006
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 2.662142
Graph Density : 8.14843037982093E-05
Modularity : 0.440845
NodeXL Version : 1.0.1.427
Data Import : The graph represents a network of 12,592 Twitter users whose recent tweets contained "1238780849652465664", 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 Wednesday, 18 March 2020 at 09:04 UTC.
The tweets in the network were tweeted over the 3-day, 21-hour, 17-minute period from Saturday, 14 March 2020 at 10:55 UTC to Wednesday, 18 March 2020 at 08:13 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 : 1.23878084965246E+18
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:
[10681] fake,news [9579] massive,einschränkungen [9543] bitte,helfen [9511] öffentlichen,lebens [9504] einschränkungen,öffentlichen [9382] achtung,fake [9377] bundesministerium,gesundheit [9370] behauptet,rasch [9370] rasch,verbreitet [9370] gesundheit,bundesregierung Top Word Pairs in Tweet in G1:
[9127] fake,news [9110] massive,einschränkungen [9110] einschränkungen,öffentlichen [9110] öffentlichen,lebens [9109] achtung,fake [9109] news,behauptet [9109] behauptet,rasch [9109] rasch,verbreitet [9109] verbreitet,bundesministerium [9109] bundesministerium,gesundheit Top Word Pairs in Tweet in G2:
[763] fake,news [322] bundesregierung,dinge [322] dinge,fake [322] news,bezeichnet [322] bezeichnet,zutreffend [322] zutreffend,herausstellen [322] herausstellen,dürfte [322] dürfte,eingeforderte [322] eingeforderte,vertrauen [322] vertrauen,aussagen Top Word Pairs in Tweet in G3:
[69] fake,news [16] öffentlichen,lebens [15] einschränkungen,öffentlichen [13] absicht,mauer [13] massive,einschränkungen [13] achtung,fake [11] bundesministerium,gesundheit [11] age,well [10] behauptet,rasch [10] rasch,verbreitet Top Word Pairs in Tweet in G4:
[310] ドイツの保健省,厚生省 [310] 厚生省,適切な訳不明 [310] 適切な訳不明,も [310] も,イブプロフェンがコロナウイルス [310] イブプロフェンがコロナウイルス,covid [310] covid,19 [310] 19,の症状を悪化させるというのはフェイクニュースだと [5] achtung,fake [5] fake,news [5] news,behauptet Top Word Pairs in Tweet in G5:
[297] fake,news [117] beschwert,regierung [117] regierung,fake [117] news,vorgegangen [117] vorgegangen,fake [117] news,angekündigten [117] angekündigten,einschnitte [117] einschnitte,betreibt [117] betreibt,populismus [117] populismus,einschnitte Top Word Pairs in Tweet in G6:
[142] einschränkungen,öffentlichen [142] öffentlichen,lebens [107] bitte,helfen [104] bundesgesundheitsministerium,warnt [104] warnt,falschmeldungen [104] falschmeldungen,mögliche [104] mögliche,einschränkungen [104] lebens,#coronavirus [104] #coronavirus,#coronavirusde [69] helfen,falschnachricht Top Word Pairs in Tweet in G7:
[129] bitte,helfen [111] #nrw,deutschland [111] deutschland,betrifft [111] betrifft,bitte [111] helfen,fahrlässige [111] fahrlässige,verbreitung [111] verbreitung,derartigen [111] derartigen,falschnachrichten [111] falschnachrichten,stoppen [111] stoppen,#corona Top Word Pairs in Tweet in G8:
[170] fake,news [165] massive,einschränkungen [153] klar,moment [153] moment,einfach [153] einfach,politik [153] politik,supereindeutige [153] supereindeutige,ansage [153] ansage,fake [153] news,exakt [153] exakt,massive Top Word Pairs in Tweet in G9:
[91] offiziellen,quellen [87] derzeit,vermehrt [87] vermehrt,#fakenews [87] #fakenews,umlauf [87] umlauf,bitte [87] bitte,verbreitet [87] verbreitet,teilt [87] teilt,informationen [87] informationen,offiziellen [87] quellen,rki_de Top Word Pairs in Tweet in G10:
[85] derzeit,erreichen [85] erreichen,vermehrt [85] vermehrt,anfragen [85] anfragen,nachgewiesenen [85] nachgewiesenen,#fakenews [85] #fakenews,klare [85] klare,empfehlung [85] empfehlung,bitte [85] bitte,verbreiten [85] verbreiten,infos Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G5:
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 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: