The graph represents a network of 4,879 Twitter users whose tweets in the requested range contained "smartcity OR smartcities", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 29 July 2022 at 00:25 UTC.
The requested start date was Friday, 29 July 2022 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 5-day, 13-hour, 47-minute period from Friday, 22 July 2022 at 13:04 UTC to Thursday, 28 July 2022 at 02:52 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 : 4879
Unique Edges : 6302
Edges With Duplicates : 15097
Total Edges : 21399
Number of Edge Types : 5
Retweet : 4556
MentionsInRetweet : 6880
Tweet : 1249
Mentions : 8107
Replies to : 607
Self-Loops : 1909
Reciprocated Vertex Pair Ratio : 0.0242148672940679
Reciprocated Edge Ratio : 0.0472847408631014
Connected Components : 622
Single-Vertex Connected Components : 304
Maximum Vertices in a Connected Component : 3247
Maximum Edges in a Connected Component : 18814
Maximum Geodesic Distance (Diameter) : 17
Average Geodesic Distance : 5.554556
Graph Density : 0.000406978859704563
Modularity : 0.408751
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 4,879 Twitter users whose tweets in the requested range contained "smartcity OR smartcities", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 29 July 2022 at 00:25 UTC.
The requested start date was Friday, 29 July 2022 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 5-day, 13-hour, 47-minute period from Friday, 22 July 2022 at 13:04 UTC to Thursday, 28 July 2022 at 02:52 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 : smartcity OR smartcities
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:
[1486] #healthtech,#datascientist [1484] #cx,#women [1482] #digitalhealth,#cx [1480] #women,#ehealth [1480] #ehealth,#finserv [1452] #web3,#digitalhealth [1448] #datascientist,#web3 [1399] #finserv,#cloud [1390] #cloud,#insurtech [1216] #iot,#iiot Top Word Pairs in Tweet in G1:
[1460] #healthtech,#datascientist [1458] #cx,#women [1456] #digitalhealth,#cx [1454] #women,#ehealth [1454] #ehealth,#finserv [1427] #web3,#digitalhealth [1423] #datascientist,#web3 [1375] #finserv,#cloud [1367] #cloud,#insurtech [1187] #iot,#iiot Top Word Pairs in Tweet in G2:
[193] vizag_smartcity,coc_gvmc [167] andhrapradeshcm,cdma_municipal [139] swachhbharat,swachhaandhra [119] gvmc_visakha,vizag_smartcity [106] swachhaandhra,andhrapradeshcm [90] swachhbharatgov,swachsurvekshan [82] coc_gvmc,swachhbharatgov [77] swachsurvekshan,swachhbharatgov [77] swachsurvekshan,swachhbharat [70] swachhbharatgov,swachhbharat Top Word Pairs in Tweet in G3:
[42] smart,city [25] smart,cities [17] #smartcity,#homecomposting [16] #dharwadforest,#smartcity [15] #dcoffice,#dharwadforest [14] #dharwad,#dcoffice [12] #hubli,#dharwad [11] #mayorhublidharwad,#hubli [10] #mycleanindia,#mayorhublidharwad [10] #cleancitydreamcity,#swachhbharatmissionurban Top Word Pairs in Tweet in G4:
[24] क,ट [19] #digitaljk,#digitalmela [19] #digitalmela,visit [19] visit,share [19] share,ideas [19] ideas,mygovjandk [19] mygovjandk,itd_gojk [19] itd_gojk,jandkegovagency [17] diprjk,infjammu [17] digital,mela Top Word Pairs in Tweet in G5:
[24] ध,यक [19] cmohry,mlkhattar [19] #smartcity,फर [19] फर,द [19] द,ब [19] ब,द [18] dc_gurugram,officialgmda [18] officialgmda,aapharyana [18] aapharyana,aap4gurgaon [17] vikas,ke Top Word Pairs in Tweet in G6:
[20] upgovt,cmofficeup [17] nagarvikasup,dmkanpur [15] र,क [15] chiefsecyup,commissionerknp [13] क,स [11] dmkanpur,upgovt [10] क,क [10] cmofficeup,secretary_mohua [10] secretary_mohua,chiefsecyup [10] commissionerknp,smartcities_hua Top Word Pairs in Tweet in G7:
[17] #nicdc,#smartcity [16] nicdc01,#nicdc [13] #smartcity,#pmgatishakti [13] #pmgatishakti,single [13] single,window [13] window,system [13] system,place [13] place,dholeraofficial [13] dholeraofficial,streamline [13] streamline,g2b Top Word Pairs in Tweet in G8:
[14] guten,morgen [14] morgen,#tanglenauten [14] #tanglenauten,neue [14] neue,woche [14] woche,neue [14] neue,#news [14] #news,wünschen [14] wünschen,viel [14] viel,spaß [14] spaß,neuen Top Word Pairs in Tweet in G9:
[41] #kccaonair,nbstv [36] kccaug,#kccaonair [23] nice,catching [23] catching,kccaed [23] kccaed,nbstv [23] nbstv,#nbsmorningbreeze [22] simonkaggwanjal,nice [22] #nbsmorningbreeze,smashing [22] smashing,green [22] green,hello Top Word Pairs in Tweet in G10:
[11] cities,adapt [11] adapt,extreme [11] extreme,heat [9] heat,ft [9] ft,#climatechange [9] #climatechange,#resilience [9] #resilience,#environment [9] #urbanplanning,#urbangovernance [8] urbanbigdata,cities [8] #environment,#smar Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
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 Replied-To in G10:
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 Mentioned in G8:
Top Mentioned in G9:
Top Mentioned in G10:
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:
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Top Tweeters in G9:
Top Tweeters in G10: