The graph represents a network of 2,729 Twitter users whose recent tweets contained "#economicmobility", 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, 22 January 2020 at 21:25 UTC.
The tweets in the network were tweeted over the 7-day, 5-hour, 58-minute period from Wednesday, 15 January 2020 at 14:51 UTC to Wednesday, 22 January 2020 at 20:49 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 : 2729
Unique Edges : 2699
Edges With Duplicates : 55
Total Edges : 2754
Number of Edge Types : 5
Mentions : 2626
MentionsInRetweet : 76
Tweet : 28
Replies to : 19
Retweet : 5
Self-Loops : 28
Reciprocated Vertex Pair Ratio : 0
Reciprocated Edge Ratio : 0
Connected Components : 43
Single-Vertex Connected Components : 20
Maximum Vertices in a Connected Component : 2632
Maximum Edges in a Connected Component : 2662
Maximum Geodesic Distance (Diameter) : 4
Average Geodesic Distance : 2.010567
Graph Density : 0.000362673532569158
Modularity : 0.082544
NodeXL Version : 1.0.1.423
Data Import : The graph represents a network of 2,729 Twitter users whose recent tweets contained "#economicmobility", 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, 22 January 2020 at 21:25 UTC.
The tweets in the network were tweeted over the 7-day, 5-hour, 58-minute period from Wednesday, 15 January 2020 at 14:51 UTC to Wednesday, 22 January 2020 at 20:49 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 : #economicmobility
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:
[2638] re,harnessing [2638] make,positive [2638] positive,impact [2637] harnessing,#powerto [2637] #powerto,make [2635] tackling,#economicmobility [2635] impact,world [2634] #economicmobility,re [2629] keeping,informed [2629] informed,#wef20 Top Word Pairs in Tweet in G1:
[2618] re,harnessing [2618] harnessing,#powerto [2618] make,positive [2618] positive,impact [2618] impact,world [2618] keeping,informed [2618] informed,#wef20 [2617] #powerto,make [2617] bofa_news,keeping [2616] thanks,bofa_news Top Word Pairs in Tweet in G2:
[7] #powerto,make [6] tackling,#economicmobility [6] #economicmobility,re [6] re,harnessing [6] harnessing,#powerto [6] make,positive [6] positive,impact [5] impact,world [2] high,school [2] great,list Top Word Pairs in Tweet in G3:
[2] tomgerend,marckcmetro [2] marckcmetro,support [2] support,#zerofaretransit [2] #zerofaretransit,#economicmobility [2] #economicmobility,#economicdevelopment [2] #economicdevelopment,strategies [2] strategies,locate [2] locate,jobs [2] jobs,education [2] education,healthcare Top Word Pairs in Tweet in G5:
[2] tackling,#economicmobility [2] #economicmobility,re [2] re,harnessing [2] harnessing,#powerto [2] #powerto,make [2] make,positive [2] positive,impact [2] impact,world [2] world,thanks [2] thanks,bofa_news Top Word Pairs in Tweet in G7:
[2] important,conversations [2] conversations,#economicmobility [2] #economicmobility,#racialwealthgap [2] #racialwealthgap,philadelphia [2] philadelphia,history [2] history,impacts [2] impacts,inclusive [2] inclusive,growth [2] growth,great [2] great,presenting Top Word Pairs in Tweet in G9:
[3] interested,work [3] work,cities [3] cities,doing [3] doing,country [3] country,increase [3] increase,#economicmobility [3] #economicmobility,residents [3] residents,check [3] check,b_i_tweets' [3] b_i_tweets',recent Top Word Pairs in Tweet in G10:
[3] tackling,workforce [3] workforce,challenges [3] challenges,working [3] working,remove [3] remove,barriers [3] barriers,#economicmobility [3] #economicmobility,hope [3] hope,join [3] join,#childcare Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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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:
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Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: