The graph represents a network of 1,148 Twitter users whose recent tweets were included in a list (Tweet ID List3) of 801 tweet IDs, or who were replied to or mentioned in those tweets. 799 out of 801 tweets were collected. The network was obtained from Twitter on Saturday, 21 May 2022 at 01:43 UTC.
The tweets in the network were tweeted over the 2-day, 10-hour, 57-minute period from Tuesday, 03 May 2022 at 22:46 UTC to Friday, 06 May 2022 at 09:44 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 : 1148
Unique Edges : 1525
Edges With Duplicates : 47
Total Edges : 1572
Number of Edge Types : 5
Retweet : 1402
MentionsInRetweet : 22
Replies to : 42
Tweet : 96
Mentions : 10
Self-Loops : 100
Reciprocated Vertex Pair Ratio : 0.000684462696783025
Reciprocated Edge Ratio : 0.00136798905608755
Connected Components : 35
Single-Vertex Connected Components : 25
Maximum Vertices in a Connected Component : 1056
Maximum Edges in a Connected Component : 1479
Maximum Geodesic Distance (Diameter) : 9
Average Geodesic Distance : 3.632451
Graph Density : 0.00111030441478907
Modularity : 0.65541
NodeXL Version : 1.0.1.507
Graph Gallery URL : https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=284288
Data Import : The graph represents a network of 1,148 Twitter users whose recent tweets were included in a list (Tweet ID List3) of 801 tweet IDs, or who were replied to or mentioned in those tweets. 799 out of 801 tweets were collected. The network was obtained from Twitter on Saturday, 21 May 2022 at 01:43 UTC.
The tweets in the network were tweeted over the 2-day, 10-hour, 57-minute period from Tuesday, 03 May 2022 at 22:46 UTC to Friday, 06 May 2022 at 09:44 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 : TwitterIDList
Graph Term : Tweet ID List3
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:
[571] 복지관에,기부한 [569] 딸이,대학 [568] 활용해,기업으로부터 [568] 기부한,것으로 [568] 것으로,의심되는 [567] 스펙을,쌓기 [567] 쌓기,위해 [565] 찬스,를 [565] 엄마,찬스 [564] 를,활용해 Top Word Pairs in Tweet in G1:
[241] 활용해,기업으로부터 [241] 위해,엄마 [241] 쌓기,위해 [241] 기부한,것으로 [241] 후보자와,배우자 [241] 장관,후보자의 [241] 한,후보자와 [241] 한동훈,법무부 [241] 의심되는,정황이 [241] 모두,서울대 Top Word Pairs in Tweet in G2:
[167] 의심되는,정황이 [167] 복지관에,기부한 [167] 정황이,나왔다 [167] 쌓기,위해 [167] 스펙을,쌓기 [167] 것으로,의심되는 [167] 엄마,찬스 [167] 대학,진학에 [167] 위해,엄마 [167] 기부한,것으로 Top Word Pairs in Tweet in G3:
[312] 진,씨 [179] 속보,한동훈 [170] 한동훈,법무부 [170] 법무부,장관 [159] 노트북,50대 [156] 배우자,진 [156] 하고,압색 [156] 기업으로,부터 [156] 대학,진학 [156] 미국,복수국적자 Top Word Pairs in Tweet in G4:
[49] 한동훈,딸 [34] 한동훈,딸도 [30] 다하다가,동양대 [30] 한동훈,이새기는 [30] 조국장관님,가족에게 [30] 위조라는,말도 [30] 누명을,씌우기 [30] 꼬셔서,정경심교수님에게 [30] 말도,안돼는걸로 [30] 비리로,입학시킨거네 Top Word Pairs in Tweet in G5:
[103] 한동훈,딸이 [103] 딸이,해외 [103] 한동훈,딸에게 [103] 50대를,직접 [103] 어떤,멍청한 [103] 도와준,일종의 [103] 주고,복지기관에 [103] 명문대,입학을 [103] 가능한,일이 [103] 기부를,하려고 Top Word Pairs in Tweet in G6:
[66] 가르치더냐,수치스런 [66] 의원,전세금 [66] 결혼하여,악업을 [66] 올렸다,니들은 [66] 비난,하고 [66] 기사로,비난 [66] 일억원,올린것 [66] 수치스런,인간 [66] 그런,ㄴ과 [66] 손가락에,피흘리며 Top Word Pairs in Tweet in G7:
[69] 한동훈,딸도 [66] 정작,기부 [66] 딸도,'부모 [66] 메일,보내서 [66] 보내서,기부 [66] 찬스'로,대학진학용 [66] 엄마빠,대학 [66] 대학진학용,'기부 [66] 받은,회사는 [66] 없고,엄마빠 Top Word Pairs in Tweet in G8:
[53] 한동훈,딸도 [45] 단독,한동훈 [36] 한동훈,딸 [23] 로,대학진학용 [21] 딸이,대학 [21] 엄마,찬스 [21] 딸,중학교 [21] 찬스,를 [20] 활용해,기업으로부터 [20] 기부한,것으로 Top Word Pairs in Tweet in G9:
[41] 썼네,ㅋㅋ [41] 4년을,구형 [41] 봉사표창장으로,4년을 [41] 엄마찬스,썼네 [41] 지,딸은 [41] 노트북50개,기부해서 [41] 구형,수사한 [41] 기부해서,대학진학시키려고 [41] 딸은,노트북50개 [41] 한동훈이,이새끼는 Top Word Pairs in Tweet in G10:
[36] 봉사가서,디바이스없는 [36] 기사썼는데,딸 [36] 기부한꺼까지,미담행ㅋㅋㅋ [36] 까려고,기사썼는데 [36] 한동훈,까려고 [36] 존나ㅋㅋㅋ한계레,한동훈 [36] 딸,봉사가서 [36] 디바이스없는,애들 [36] 애들,기부한꺼까지 [7] 네이버,뉴스 Top Replied-To in Entire Graph:
Top Replied-To in G1:
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 Mentioned in Entire Graph:
Top Mentioned in G4:
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: