The graph represents a network of 66 Twitter users whose tweets in the requested range contained "#HealthXPh", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 21 November 2019 at 02:58 UTC.
The requested start date was Tuesday, 19 November 2019 at 01:01 UTC and the maximum number of days (going backward) was 6.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 5-day, 4-hour, 39-minute period from Wednesday, 13 November 2019 at 14:21 UTC to Monday, 18 November 2019 at 19:01 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 : 66
Unique Edges : 121
Edges With Duplicates : 162
Total Edges : 283
Number of Edge Types : 3
Mentions : 152
Tweet : 64
Replies to : 67
Self-Loops : 64
Reciprocated Vertex Pair Ratio : 0.129032258064516
Reciprocated Edge Ratio : 0.228571428571429
Connected Components : 7
Single-Vertex Connected Components : 2
Maximum Vertices in a Connected Component : 42
Maximum Edges in a Connected Component : 216
Maximum Geodesic Distance (Diameter) : 5
Average Geodesic Distance : 2.503024
Graph Density : 0.0326340326340326
Modularity : 0.381501
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 66 Twitter users whose tweets in the requested range contained "#HealthXPh", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 21 November 2019 at 02:58 UTC.
The requested start date was Tuesday, 19 November 2019 at 01:01 UTC and the maximum number of days (going backward) was 6.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 5-day, 4-hour, 39-minute period from Wednesday, 13 November 2019 at 14:21 UTC to Monday, 18 November 2019 at 19:01 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 : #HealthXPh
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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[9] hepatorenal,syndrome [9] syndrome,thecurbsiders [9] thecurbsiders,twhittier_rush [9] twhittier_rush,veleznephhepato [9] veleznephhepato,kidney_boy [9] kidney_boy,#infographic [9] #infographic,nephroguy [9] stephmiaco,#healthxph [8] edgarvlermamd,hepatorenal [8] nephroguy,#healt Top Word Pairs in Tweet in G1:
[9] stephmiaco,#healthxph [7] proper,etiquette [7] healthcare,workers [7] endocrine_witch,stephmiaco [6] m,very [6] very,interested [6] interested,pushing [6] pushing,conversation [6] conversation,towards [6] towards,proper Top Word Pairs in Tweet in G2:
[9] hepatorenal,syndrome [9] syndrome,thecurbsiders [9] thecurbsiders,twhittier_rush [9] twhittier_rush,veleznephhepato [9] veleznephhepato,kidney_boy [9] kidney_boy,#infographic [9] #infographic,nephroguy [8] edgarvlermamd,hepatorenal [8] nephroguy,#healt Top Word Pairs in Tweet in G3:
[2] #healthxph,featuring [2] telemedicine,facilitates [2] facilitates,diagnosis [2] diagnosis,parasites [2] parasites,fungi [2] fungi,causing [2] causing,human [2] human,diseases [2] diseases,difficult [2] difficult,identify Top Word Pairs in Tweet in G4:
[5] dahil,ba [3] clinic,ask [3] ask,different [3] different,way [3] way,bakit [3] bakit,po [3] po,ngayon [3] ngayon,nyo [3] nyo,dinala [3] dinala,minus Top Word Pairs in Tweet in G5:
[4] #hcsmph2019,#healthxph [3] #healthxph,titasunshineph [2] empathy,necessary [2] necessary,bridge [2] bridge,divide [2] divide,know [2] know,empathy [2] empathy,naturally [2] naturally,selective [2] selective,e Top Word Pairs in Tweet in G6:
[3] know,#mentalhealth [3] #mentalhealth,#mentalhealthph [3] #mentalhealthph,#mentalhealthawareness [3] #mentalhealthawareness,#mentalhealthmatters [3] #mentalhealthmatters,#health [2] bonita74170936,know [2] #health,#healthx [2] #fitness,#fitnessmotivation Top Word Pairs in Tweet in G7:
[2] saturday,#twitterchat [2] #twitterchat,list [2] list,#edchateu [2] #edchateu,7am [2] 7am,#satchat [2] #satchat,7 [2] 7,30am [2] 30am,#healthxph [2] #healthxph,9am [2] 9am,#edugladiators Top Word Pairs in Tweet in G8:
[2] #health,#healthtech Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G4:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
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: