The graph represents a network of 5,372 Twitter users whose recent tweets contained "cyber bullying", 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 Friday, 08 November 2019 at 13:52 UTC.
The tweets in the network were tweeted over the 2-day, 2-hour, 42-minute period from Wednesday, 06 November 2019 at 11:04 UTC to Friday, 08 November 2019 at 13:46 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 : 5372
Unique Edges : 5841
Edges With Duplicates : 555
Total Edges : 6396
Number of Edge Types : 4
Retweet : 3851
Tweet : 610
Replies to : 587
Mentions : 1348
Self-Loops : 617
Reciprocated Vertex Pair Ratio : 0.00564663023679417
Reciprocated Edge Ratio : 0.0112298496649158
Connected Components : 939
Single-Vertex Connected Components : 362
Maximum Vertices in a Connected Component : 2201
Maximum Edges in a Connected Component : 3176
Maximum Geodesic Distance (Diameter) : 18
Average Geodesic Distance : 4.063899
Graph Density : 0.000191349173528226
Modularity : 0.805979
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 5,372 Twitter users whose recent tweets contained "cyber bullying", 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 Friday, 08 November 2019 at 13:52 UTC.
The tweets in the network were tweeted over the 2-day, 2-hour, 42-minute period from Wednesday, 06 November 2019 at 11:04 UTC to Friday, 08 November 2019 at 13:46 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 : cyber bullying
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:
[5052] cyber,bullying [1349] against,cyber [1302] bullying,harassment [1231] fight,against [1226] #monbebe,fight [1226] harassment,defending [1226] defending,boys [1226] boys,suffered [1226] suffered,please [1226] please,taint Top Word Pairs in Tweet in G1:
[1145] cyber,bullying [1144] against,cyber [1143] #monbebe,fight [1143] fight,against [1143] bullying,harassment [1143] harassment,defending [1143] defending,boys [1143] boys,suffered [1143] suffered,please [1143] please,taint Top Word Pairs in Tweet in G2:
[561] cyber,bullying [238] officialmonstax,starshipent [177] stop,cyber [150] fighting,against [147] #몬엑_행복해지길_바래,#monstax7shineforever [144] defamation,cyber [143] sometimes,wonder [143] wonder,fighting [143] against,defamation [143] bullying,football Top Word Pairs in Tweet in G3:
[498] cyber,bullying [410] mental,health [377] funny,last [377] last,month [377] month,stan [377] stan,twt [377] twt,talking [377] talking,mental [377] health,important [377] important,blaming Top Word Pairs in Tweet in G4:
[363] cyber,bullying [25] stop,cyber [12] victim,cyber [11] social,media [9] samantha,markle [8] against,cyber [8] #cyberbullying,#cyberbully [7] bullying,cyber [7] mental,health [6] bullying,stop Top Word Pairs in Tweet in G5:
[283] cyber,bullying [218] normalizing,cyber [218] bullying,worst [218] worst,thing [218] thing,seen [218] seen,social [218] social,media [218] media,lately [218] lately,y'all [218] y'all,notice Top Word Pairs in Tweet in G6:
[226] spm,students [226] students,look [226] look,guys [226] guys,done [226] done,towards [226] towards,miss [226] miss,laura [226] laura,melissa [226] melissa,williams [226] williams,announced Top Word Pairs in Tweet in G7:
[257] cyber,bullying [125] ve,normalized [125] normalized,cyber [125] bullying,hence [125] hence,don [125] don,see [125] see,nothing [125] nothing,wrong [125] wrong,defend [79] social,media Top Word Pairs in Tweet in G8:
[174] cyber,bullying [172] hahahahahahahaha,fuck [172] fuck,cyber [172] bullying,hahahaha [172] hahahaha,nigga [172] nigga,walk [172] walk,away [172] away,screen [172] screen,nigga [172] nigga,close Top Word Pairs in Tweet in G9:
[52] cyber,bullying [51] people,stop [51] stop,tagging [51] tagging,arashi [51] arashi,freaking [51] freaking,highly [51] highly,inappropriate [51] inappropriate,cheap [51] cheap,thirsty [51] thirsty,cyber Top Word Pairs in Tweet in G10:
[31] cyber,bullying [7] half,sister [6] samantha,markle [6] flotus,the_bmc [6] bullying,polkcosheriff [5] whitehouse,flotus [4] bullying,campaign [4] anti,cyber [4] tonight,fox13news [4] fox13news,exclusive Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G7:
Top Replied-To in G9:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G2:
Top Mentioned in G5:
Top Mentioned in G7:
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: