networkeffects, Twitter, 10/13/2021 4:53:18 PM, 264432


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networkeffects Twitter NodeXL SNA Map and Report for Wednesday, 13 October 2021 at 16:49 UTC
networkeffects Twitter NodeXL SNA Map and Report for Wednesday, 13 October 2021 at 16:49 UTC
From:
marc_smith
Uploaded on:
October 13, 2021
Short Description:
networkeffects via NodeXL https://bit.ly/3p0tXTU
@jamescurrier
@azeem
@b2btrust
@realnoob1
@pitzop
@aubit_and_me
@darpanalabs
@schmults
@g2link
@loudnewsnet

Top hashtags:
#networkeffects
#collectiveintelligence
#blockchain
#facebook
#regtech
#nfx
#egm
#supercharger

Description:
Description
The graph represents a network of 18 Twitter users whose recent tweets contained "networkeffects", 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, 13 October 2021 at 16:49 UTC.

The tweets in the network were tweeted over the 6-day, 22-hour, 52-minute period from Wednesday, 06 October 2021 at 15:10 UTC to Wednesday, 13 October 2021 at 14:02 UTC.

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


Overall Graph Metrics
Vertices : 18
Unique Edges : 20
Edges With Duplicates : 6
Total Edges : 26
Number of Edge Types : 5
Mentions : 5
Tweet : 13
Retweet : 3
MentionsInRetweet : 4
Replies to : 1
Self-Loops : 13
Reciprocated Vertex Pair Ratio : 0.3
Reciprocated Edge Ratio : 0.461538461538462
Connected Components : 12
Single-Vertex Connected Components : 9
Maximum Vertices in a Connected Component : 5
Maximum Edges in a Connected Component : 11
Maximum Geodesic Distance (Diameter) : 2
Average Geodesic Distance : 0.666667
Graph Density : 0.042483660130719
Modularity : 0.447485
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 18 Twitter users whose recent tweets contained "networkeffects", 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, 13 October 2021 at 16:49 UTC.

The tweets in the network were tweeted over the 6-day, 22-hour, 52-minute period from Wednesday, 06 October 2021 at 15:10 UTC to Wednesday, 13 October 2021 at 14:02 UTC.

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 : networkeffects
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 Influencers: Top 10 Vertices, Ranked by Betweenness Centrality
Top URLs
Top URLs in Tweet in Entire Graph:
[3] https://overcast.fm/+HiEZPC1Tk
[2] https://uilo.com/why-honeybooks-model/
[2] https://b2btrust.medium.com/disrupting-b2b-information-free-the-data-4b563a467148?utm_campaign=Get%20to%20Know%20Trust%20Exchange&utm_content=182223008&utm_medium=social&utm_source=twitter&hss_channel=tw-770623919313317888
[2] https://www.nfx.com/post/enterprise-gateway-marketplaces/?utm_campaign=Get%20to%20Know%20Trust%20Exchange&utm_content=182222983&utm_medium=social&utm_source=twitter&hss_channel=tw-770623919313317888
[1] https://podcasts.apple.com/us/podcast/how-network-effects-rule-the-world-with-james-currier/id1172218725?i=1000537729278
[1] https://time.com/5947561/pinterest-gender-discrimination-racism/?utm_source=twitter&utm_medium=social&utm_campaign=social-share-article&utm_term=tech
[1] https://twitter.com/azeem/status/1445758808064622593
[1] https://www.linkedin.com/slink?code=gdsbxc7D

Top URLs in Tweet in G1:
[2] https://b2btrust.medium.com/disrupting-b2b-information-free-the-data-4b563a467148?utm_campaign=Get%20to%20Know%20Trust%20Exchange&utm_content=182223008&utm_medium=social&utm_source=twitter&hss_channel=tw-770623919313317888
[2] https://www.nfx.com/post/enterprise-gateway-marketplaces/?utm_campaign=Get%20to%20Know%20Trust%20Exchange&utm_content=182222983&utm_medium=social&utm_source=twitter&hss_channel=tw-770623919313317888
[2] https://uilo.com/why-honeybooks-model/
[1] https://www.linkedin.com/slink?code=gdsbxc7D
[1] https://twitter.com/azeem/status/1445758808064622593
[1] https://time.com/5947561/pinterest-gender-discrimination-racism/?utm_source=twitter&utm_medium=social&utm_campaign=social-share-article&utm_term=tech

Top URLs in Tweet in G2:
[3] https://overcast.fm/+HiEZPC1Tk
[1] https://podcasts.apple.com/us/podcast/how-network-effects-rule-the-world-with-james-currier/id1172218725?i=1000537729278

Top Domains
Top Hashtags
Top Hashtags in Tweet in Entire Graph:
[17] networkeffects
[3] collectiveintelligence
[2] blockchain
[2] facebook
[2] regtech
[2] nfx
[2] egm
[2] supercharger
[2] freewaygains
[2] freewaysupercharged



Top Hashtags in Tweet in G1:
[10] networkeffects
[2] regtech
[2] nfx
[2] egm
[1] blockchain
[1] biotech
[1] gamingindustry
[1] spacetech
[1] exponentialview
[1] tokeneconomy

Top Hashtags in Tweet in G2:
[4] networkeffects
[3] collectiveintelligence
[1] blockchain
[1] google
[1] facebook

Top Hashtags in Tweet in G3:
[2] networkeffects
[2] supercharger
[2] freewaygains
[2] freewaysupercharged

Top Hashtags in Tweet in G4:
[1] networkeffects

Top Words
Top Word Pairs
Top Word Pairs in Tweet in Entire Graph:
[4] 165,27
[3] #networkeffects,yield
[3] yield,energy
[3] energy,adaptation
[3] adaptation,resulting
[3] resulting,competitive
[3] competitive,advantage
[3] advantage,possibly
[3] possibly,#collectiveintelligence
[3] #collectiveintelligence,worth

Top Word Pairs in Tweet in G1:
[2] charging,submit
[2] submit,data
[2] data,disincentive
[2] disincentive,accuracy
[2] accuracy,keeps
[2] keeps,largest
[2] largest,population
[2] population,companies
[2] companies,small
[2] small,businesses

Top Word Pairs in Tweet in G2:
[3] #networkeffects,yield
[3] yield,energy
[3] energy,adaptation
[3] adaptation,resulting
[3] resulting,competitive
[3] competitive,advantage
[3] advantage,possibly
[3] possibly,#collectiveintelligence
[3] #collectiveintelligence,worth
[3] worth,listening

Top Word Pairs in Tweet in G3:
[4] 165,27
[2] 27,earned
[2] earned,additional
[2] additional,165
[2] 27,#networkeffects
[2] #networkeffects,alone
[2] alone,share
[2] share,fees
[2] fees,people
[2] people,buying

Top Replied-To
Top Replied-To in Entire Graph:
@prestonpysh

Top Replied-To in G4:
@prestonpysh

Top Mentioned
Top Tweeters
Top Tweeters in Entire Graph:
@jennifersertl
@darpanalabs
@loudnewsnet
@azeem
@prestonpysh
@pitzop
@realnoob1
@exponentialview
@g2link
@capriciouscant

Top Tweeters in G1:
@jennifersertl
@darpanalabs
@loudnewsnet
@pitzop
@g2link
@emrahcavli
@b2btrust
@danunda
@akat1000

Top Tweeters in G2:
@azeem
@exponentialview
@jamescurrier
@ggiacomelli
@schmults

Top Tweeters in G3:
@realnoob1
@aubit_and_me

Top Tweeters in G4:
@prestonpysh
@capriciouscant


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