The graph represents a network of 5,231 Twitter users whose tweets in the requested range contained "acog", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 31 July 2020 at 13:46 UTC.
The requested start date was Friday, 31 July 2020 at 00:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 11-day, 10-hour, 15-minute period from Sunday, 19 July 2020 at 13:32 UTC to Thursday, 30 July 2020 at 23:47 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 : 5231
Unique Edges : 4282
Edges With Duplicates : 7532
Total Edges : 11814
Number of Edge Types : 5
Retweet : 2687
MentionsInRetweet : 3901
Tweet : 1111
Mentions : 2768
Replies to : 1347
Self-Loops : 1123
Reciprocated Vertex Pair Ratio : 0.0341760299625468
Reciprocated Edge Ratio : 0.0660932548664554
Connected Components : 885
Single-Vertex Connected Components : 403
Maximum Vertices in a Connected Component : 1831
Maximum Edges in a Connected Component : 6110
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 4.261761
Graph Density : 0.000242231468305765
Modularity : 0.532725
NodeXL Version : 1.0.1.439
Data Import : The graph represents a network of 5,231 Twitter users whose tweets in the requested range contained "acog", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 31 July 2020 at 13:46 UTC.
The requested start date was Friday, 31 July 2020 at 00:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 11-day, 10-hour, 15-minute period from Sunday, 19 July 2020 at 13:32 UTC to Thursday, 30 July 2020 at 23:47 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 : GraphServerTwitterSearch
Graph Term : acog
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:
[438] take,acog [434] make,speed [432] acog,nerf [432] nerf,gun's [432] gun's,damage [432] damage,change [432] change,gun's [432] gun's,recoil [432] recoil,make [432] speed,dread Top Word Pairs in Tweet in G1:
[56] ameracadpeds,acog [47] acog,proud [41] acogaction,acog [38] proud,endorse [33] acog,mysmfm [29] public,health [27] endorse,resolution [27] resolution,declare [27] declare,racism [27] racism,public Top Word Pairs in Tweet in G2:
[427] take,acog [427] acog,nerf [427] nerf,gun's [427] gun's,damage [427] damage,change [427] change,gun's [427] gun's,recoil [427] recoil,make [427] make,speed [427] speed,dread Top Word Pairs in Tweet in G3:
[17] acogはいつまでも使えるものだと思っていた,だが違った [13] ak47には,acogサイトつけない方がカッコいいよね [10] みんなからの匿名質問を募集中,こんな質問に答えてるよ [10] #質問箱,#匿名質問募集中 [7] obstetricians,gynecologists [7] 主観的武器評価,fal [7] fal,唯一のセミオートａｒ [7] 唯一のセミオートａｒ,音とリロードモーションがカコイイ [7] 音とリロードモーションがカコイイ,ホロサイトを付けるとなんか強くなるらしい [7] ホロサイトを付けるとなんか強くなるらしい,ａｃｏｇ付けたくなる気持ちはわかるけど Top Word Pairs in Tweet in G4:
[335] cause,mortality [335] mortality,kids [335] kids,under [335] under,year [335] year,old [335] old,declined [335] declined,30 [335] 30,during [335] during,lockdown [335] lockdown,evidence Top Word Pairs in Tweet in G5:
[182] ag,barr [174] secazar,stevefda [142] acog,fda [133] appeal,acog [131] barr,secazar [127] fda,decision [115] abortion,lobby [104] urge,ag [101] mail,without [91] stevefda,appeal Top Word Pairs in Tweet in G6:
[266] physician,took [266] took,hippocratic [266] hippocratic,oath [266] oath,harm [266] harm,dangerous [266] dangerous,decision [266] decision,allow [266] allow,access [266] access,abortion [266] abortion,drugs Top Word Pairs in Tweet in G7:
[17] bosg,acog [13] acog,back [8] fabianhallsten,bikinibodhi [8] ash,acog [7] jager,acog [6] rainbow6game,add [6] add,acog [6] needs,acog [6] give,acog [6] badguycry,smokyyr6 Top Word Pairs in Tweet in G8:
[10] please,halo [10] halo,look [10] look,good [8] call,duty [8] good,please [8] gt,gt [6] duty,modern [6] modern,warfare [6] halo,infinite [4] infinite,box Top Word Pairs in Tweet in G9:
[107] リーク,新acog [106] r6_hungry,リーク [3] black__right,目が悪いのでacogしかつかえません Top Word Pairs in Tweet in G10:
[7] dia_planinauta,stream [6] stream,começando [6] começando,live [6] live,em [6] em,clima [6] clima,alto [6] alto,astral [6] astral,acog_geek4ever [6] acog_geek4ever,não [6] não,consegue Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
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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:
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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 G5:
Top Tweeters in G6:
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Top Tweeters in G9:
Top Tweeters in G10: