The graph represents a network of 6,295 Twitter users whose tweets in the requested range contained "#CDC", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 21 October 2020 at 09:53 UTC.
The requested start date was Wednesday, 21 October 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 7-day, 0-hour, 46-minute period from Tuesday, 13 October 2020 at 23:14 UTC to Wednesday, 21 October 2020 at 00:00 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 : 6295
Unique Edges : 3095
Edges With Duplicates : 9889
Total Edges : 12984
Number of Edge Types : 5
Tweet : 2943
Retweet : 3804
MentionsInRetweet : 4263
Replies to : 608
Mentions : 1366
Self-Loops : 3072
Reciprocated Vertex Pair Ratio : 0.00568787771062922
Reciprocated Edge Ratio : 0.0113114174620007
Connected Components : 1372
Single-Vertex Connected Components : 851
Maximum Vertices in a Connected Component : 2690
Maximum Edges in a Connected Component : 6869
Maximum Geodesic Distance (Diameter) : 19
Average Geodesic Distance : 6.227627
Graph Density : 0.000142804032131664
Modularity : 0.46433
NodeXL Version : 1.0.1.441
Data Import : The graph represents a network of 6,295 Twitter users whose tweets in the requested range contained "#CDC", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 21 October 2020 at 09:53 UTC.
The requested start date was Wednesday, 21 October 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 7-day, 0-hour, 46-minute period from Tuesday, 13 October 2020 at 23:14 UTC to Wednesday, 21 October 2020 at 00:00 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 : #CDC
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:
[958] read,more [502] covid,19 [443] more,#cdc [418] #coronavirus,#covid19 [417] #cdc,#coronavirus [376] johnrich,#cdc [376] oh,really [375] #cdc,outside [375] outside,dinners [375] dinners,thanksgiving Top Word Pairs in Tweet in G1:
[202] oh,mao [202] mao,god [202] god,#omg [202] #omg,#ohmaogod [128] #東方不敗,#dongfangbubai [128] #dongfangbubai,#cdc [124] #cdc,#commidescochons [96] covid,19 [61] #cdc,#cdc7words [61] #cdc7words,#bannedwords Top Word Pairs in Tweet in G2:
[376] johnrich,#cdc [375] #cdc,outside [375] outside,dinners [375] dinners,thanksgiving [375] thanksgiving,year [375] year,oh [375] oh,really [375] really,take [374] take,opportunity [3] wth,#cdc Top Word Pairs in Tweet in G3:
[44] realdonaldtrump,#cdc [43] #coronavirus,realdonaldtrump [42] cdc,currently [42] currently,recommend [42] recommend,use [42] use,facemasks [42] facemasks,help [42] help,prevent [42] prevent,novel [42] novel,#coronavirus Top Word Pairs in Tweet in G4:
[61] lotusoak2,#cdc [61] #coronavirus,#covid19 [60] #rent,#landlord [60] #landlord,#landlords [60] #landlords,#apartmentliving [60] #apartmentliving,#reviewyourlandlordsafestan [60] #reviewyourlandlordsafestan,#coronavirus [60] #covid19,#rentrelief [56] doctors,getting [56] getting,fed Top Word Pairs in Tweet in G5:
[161] data,#cdc [161] #cdc,revealed [161] revealed,startling [161] startling,reality [161] reality,effectiveness [161] effectiveness,mask [161] mask,mandates [161] mandates,#covid19 [161] #covid19,mitigation [160] highwiretalk,data Top Word Pairs in Tweet in G6:
[61] cdcgov,dr [60] #cdc,study [58] despite,#cdc [58] study,finds [58] finds,overwhelming [58] overwhelming,majority [58] majority,people [58] people,getting [58] getting,#coronavirus [58] #coronavirus,wore Top Word Pairs in Tweet in G7:
[10] puts,politicals [10] try,control [10] control,info [10] white,house [9] inside,fall [9] politicals,#cdc [9] #cdc,try [8] house,puts [7] fall,#cdc [7] info,ap Top Word Pairs in Tweet in G8:
[93] #breaking,#breakingnews [83] aoecoin,#breaking [36] #cdc,caught [36] caught,red [36] red,handed [35] criminal,#cdc [32] #breakingnews,#cdc [32] aoecoin,criminal [30] handed,blatant [30] blatant,fraud Top Word Pairs in Tweet in G9:
[122] #vaccines,#cdc [122] #cdc,finally [122] finally,admitting [122] admitting,#corruption [122] #corruption,#a [122] #a,vaccines [121] freedpeacock10,#vaccines [2] #cdc,stating [2] stating,overwhelming [2] overwhelming,majority Top Word Pairs in Tweet in G10:
[236] dr,fauci [118] fauci,working [118] working,government [118] government,1984 [118] 1984,dr [118] fauci,worked [118] worked,several [118] several,presidents [118] presidents,both [118] both,political Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: