The graph represents a network of 6,381 Twitter users whose tweets in the requested range contained "opendata", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 21 September 2020 at 19:28 UTC.
The requested start date was Monday, 21 September 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 9-day, 13-hour, 59-minute period from Friday, 11 September 2020 at 10:01 UTC to Monday, 21 September 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 : 6381
Unique Edges : 5103
Edges With Duplicates : 12770
Total Edges : 17873
Number of Edge Types : 5
Retweet : 5204
MentionsInRetweet : 7506
Replies to : 393
Mentions : 3482
Tweet : 1288
Self-Loops : 1376
Reciprocated Vertex Pair Ratio : 0.0331292368248415
Reciprocated Edge Ratio : 0.0641337707693936
Connected Components : 570
Single-Vertex Connected Components : 168
Maximum Vertices in a Connected Component : 4159
Maximum Edges in a Connected Component : 13698
Maximum Geodesic Distance (Diameter) : 18
Average Geodesic Distance : 6.220382
Graph Density : 0.000232100686845106
Modularity : 0.493535
NodeXL Version : 1.0.1.440
Data Import : The graph represents a network of 6,381 Twitter users whose tweets in the requested range contained "opendata", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 21 September 2020 at 19:28 UTC.
The requested start date was Monday, 21 September 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 9-day, 13-hour, 59-minute period from Friday, 11 September 2020 at 10:01 UTC to Monday, 21 September 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 : opendata
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 URLs in Tweet in Entire Graph:
[196] http://www.city.matsuyama.ehime.jp/smph/shisei/opendata/metadata/shikihaiku.html [175] https://fcub.fluidware.it/stations [85] https://brasil.io/ [63] https://carto.graou.info [35] https://nextstrain.org/ncov [34] https://numfocus.org/your-support [33] https://www.meetup.com/pro/pydata/ [30] https://medium.com/@cq94/mission-données-et-codes-sources-dd684c4b8410 [29] https://framaforms.org/appel-a-participation-l-barometre-citoyen-du-covid-19-au-benin-1599847511 [25] https://www.datasciencecentral.com/profiles/blogs/iot-s-purview-on-current-environmental-conditions Top URLs in Tweet in G1:
[9] https://scic.ec.europa.eu/ew/register/dgscic/EU_Datathon_2020_Online_15_October_2020/e/lk/g/16870/k/ [7] https://www.youtube.com/channel/UCWRxmFRYBSQyUe6GFOOrxFA [6] https://digital-dryads.eu/ [6] https://eu01web.zoom.us/meeting/register/u5IqcOmhrDstH9VEjaV6GxgHa0O7zgI95HKk [5] https://op.europa.eu/en/eudatathon [5] https://ted.europa.eu/udl?uri=TED:NOTICE:362158-2020:TEXT:EN:HTML&src=0&WT.mc_id=Twitter [4] https://www.flickr.com/short_urls.gne?photoset=aHsmQa5Pah [4] https://worldview.earthdata.nasa.gov/?v=-156.70662560810365,22.209815306837413,-89.20662560810364,55.78403405683741&t=2020-09-10-T05:54:27Z&l=VIIRS_SNPP_Thermal_Anomalies_375m_Night(hidden),VIIRS_SNPP_Thermal_Anomalies_375m_Day(hidden),MODIS_Aqua_Thermal_Anomalies_All,MODIS_Terra_Thermal_Anomalies_All,Reference_Labels,Reference_Features,Coastlines,VIIRS_SNPP_CorrectedReflectance_TrueColor,MODIS_Aqua_CorrectedReflectance_TrueColor,MODIS_Terra_CorrectedReflectance_TrueColor [3] https://ec.europa.eu/digital-single-market/en/open-data [3] https://www.europeandataportal.eu/en/using-data/using-data-checklist Top URLs in Tweet in G2:
[11] https://codata.org/2020-international-symposium-on-covid-19-at-academia-sinica-taipei-on-5-6-october/ [6] https://www.youtube.com/watch?v=p8vyRH2DFwg&feature=youtu.be [6] https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/wastewater-surveillance.html [6] https://theconversation.com/medical-research-is-broken-heres-how-we-can-fix-it-145281?utm_medium=Social&utm_source=Twitter#Echobox=1599500796consider [5] https://www.meetup.com/pro/pydata/ [4] https://www.inaturalist.org/blog/40699-50-million-observations-on-inaturalist/ [4] https://numfocus.org/your-support [4] https://www.worldscientific.com/worldscibooks/10.1142/11794?cookieSet=1 [4] https://codata.org/introduction-to-fair-data-stewardship/ [3] https://www.iochem-bd.org Top URLs in Tweet in G3:
[175] https://fcub.fluidware.it/stations [63] https://carto.graou.info [30] https://medium.com/@cq94/mission-données-et-codes-sources-dd684c4b8410 [11] https://opendata-reunion.edf.fr/pages/cartographie_des_reseaux_electriques/ [10] https://git.fluidware.it/milanoscaloromana/pm/blob/master/README.md [5] https://www.lagazettedescommunes.com/695697/la-vague-des-communs-arrive/ [4] https://blog.insee.fr/la-diffusion-en-acces-libre-et-gratuit-des-donnees-lexemple-des-donnees-dentreprise-du-repertoire-sirene/ [3] https://numfocus.org/your-support [3] https://fnh.ma/article/alaune/open-banking-le-monopole-de-la-data-echappe-aux-banques [3] https://www.fmsh.fr/fr/recherche/30976 Top URLs in Tweet in G4:
[1] https://blogs.worldbank.org/opendata/new-child-and-youth-mortality-estimates-show-dramatic-reductions-progress-threatened Top URLs in Tweet in G5:
[27] https://numfocus.org/your-support [26] https://www.meetup.com/pro/pydata/ [25] https://www.datasciencecentral.com/profiles/blogs/iot-s-purview-on-current-environmental-conditions [20] https://engage.bah.com/Article/Redirect/a492db5b-0716-47fb-9efb-0dc825c08157?uc=16822&g=01d951a6-30a5-4ea8-8f41-421b782035ed&f=132880 [8] https://www.mygreatlearning.com/blog/sources-for-analytics-and-machine-learning-datasets/ [7] http://tinitaly.pi.ingv.it/Download_Area2.html [6] https://www.45drives.com/contact/public-webinar/ [6] https://blog.google/technology/health/making-data-useful-public-health/ [5] https://www.45drives.com/community/articles/CEPH-webinar-QA/ [4] http://aliprandi.blogspot.com/2020/09/software-licensing-data-governance-libro-nuovo.html Top URLs in Tweet in G6:
[11] https://blogs.worldbank.org/opendata/hidden-potential-mobile-phone-data-insights-covid-19-gambia [10] https://blogs.worldbank.org/opendata/hidden-potential-mobile-phone-data-insights-covid-19-gambia?cid=SHR_BlogSiteShare_EN_EXT [9] https://blogs.worldbank.org/opendata/new-child-and-youth-mortality-estimates-show-dramatic-reductions-progress-threatened?cid=dec_tt_data_en_ext [7] https://blogs.worldbank.org/opendata/online-learning-open-data-english-and-spanish?CID=WBW_AL_BlogNotification_EN_EXT?cid=SHR_BlogSiteShare_EN_EXT [4] https://blogs.worldbank.org/opendata/understanding-global-debt-relieving-covid-19-impact-most-vulnerable?cid=ECR_TT_worldbank_EN_EXT [4] https://blogs.worldbank.org/opendata/high-frequency-monitoring-covid-19-impacts-first-results-malawi [3] https://blogs.worldbank.org/opendata/coping-pandemic-crisis-what-do-national-statistical-offices-need-most [3] https://blogs.worldbank.org/opendata/exploring-links-between-democracy-and-womens-economic-empowerment?cid=dec_tt_data_en_ext [3] https://blogs.worldbank.org/es/opendata/aprendizaje-en-linea-sobre-datos-abiertos-en-ingles-y-en-espanol?cid=ECR_E_NewsletterWeekly_ES_EXT&deliveryName=DM78502?cid=SHR_BlogSiteShare_ES_EXT [2] http://wrld.bg/m7Ye50BsTeS Top URLs in Tweet in G7:
[196] http://www.city.matsuyama.ehime.jp/smph/shisei/opendata/metadata/shikihaiku.html Top URLs in Tweet in G8:
[7] https://twinybots.ch/ [5] https://blogs.worldbank.org/opendata/online-learning-open-data-english-and-spanish?CID=WBW_AL_BlogNotification_EN_EXT?cid=SHR_BlogSiteShare_EN_EXT [4] https://worldview.earthdata.nasa.gov/?v=-156.70662560810365,22.209815306837413,-89.20662560810364,55.78403405683741&t=2020-09-10-T05:54:27Z&l=VIIRS_SNPP_Thermal_Anomalies_375m_Night(hidden),VIIRS_SNPP_Thermal_Anomalies_375m_Day(hidden),MODIS_Aqua_Thermal_Anomalies_All,MODIS_Terra_Thermal_Anomalies_All,Reference_Labels,Reference_Features,Coastlines,VIIRS_SNPP_CorrectedReflectance_TrueColor,MODIS_Aqua_CorrectedReflectance_TrueColor,MODIS_Terra_CorrectedReflectance_TrueColor [2] https://opendata.cbs.nl/statline/#/CBS/nl/dataset/83913NED/line?ts=1571651405371 [2] https://www.youtube.com/watch?v=doR9KIAF7rI&feature=youtu.be [2] https://blogs.worldbank.org/opendata/new-child-and-youth-mortality-estimates-show-dramatic-reductions-progress-threatened?cid=dec_tt_data_en_ext [2] https://blogs.worldbank.org/opendata/updated-estimates-impact-covid-19-global-poverty [2] https://blogs.worldbank.org/opendata/new-child-and-youth-mortality-estimates-show-dramatic-reductions-progress-threatened?cid=afr_tt_nigeria_en_ext [2] https://blogs.worldbank.org/opendata/new-child-and-youth-mortality-estimates-show-dramatic-reductions-progress-threatened [2] https://opendataday.org/ Top URLs in Tweet in G9:
[10] https://opendata-ajuntament.barcelona.cat/ca/world-data-viz-challenge-bcn-kobe-2020 [7] https://opendata-ajuntament.barcelona.cat/data/ca/dataset [6] https://opendata-ajuntament.barcelona.cat/ca/aplicacions [5] https://opendata-ajuntament.barcelona.cat/en/world-data-viz-challenge-bcn-kobe-2020 [3] https://opendata-ajuntament.barcelona.cat/ca/centres-participants-2021 [2] https://opendata-ajuntament.barcelona.cat/ca/repte-jurat-2021 [2] https://opendata-ajuntament.barcelona.cat/data/ca/dataset?sort=fecha_publicacion+desc&q=carta+arqueol%C3%B2gica&res_format=GeoJSON [2] https://opendata-ajuntament.barcelona.cat/data/ca/dataset?q=clima+mensuals&sort=fecha_publicacion+desc [2] https://engage.bah.com/Article/Redirect/a492db5b-0716-47fb-9efb-0dc825c08157?uc=16822&g=01d951a6-30a5-4ea8-8f41-421b782035ed&f=132880 [2] https://www.lagazettedescommunes.com/687344/mieux-que-des-smart-cities-des-villes-numeriques-ouvertes-et-humaines/ Top URLs in Tweet in G10:
[35] https://nextstrain.org/ncov [6] https://brasil.io/ [3] https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=235266 [2] https://nextstrain.org/ncov/south-america [1] https://engage.bah.com/Article/Redirect/a492db5b-0716-47fb-9efb-0dc825c08157?uc=16822&g=01d951a6-30a5-4ea8-8f41-421b782035ed&f=132880 [1] https://nextstrain.org/ncov/africa [1] https://blogs.worldbank.org/opendata/high-frequency-monitoring-covid-19-impacts-first-results-malawi [1] https://www.linkedin.com/slink?code=gYdc-Qq Top Domains
Top Word Pairs in Tweet in Entire Graph:
[440] sep,2020 [310] child,mortality [310] mortality,data [310] data,remains [310] remains,one [310] one,largest [310] largest,global [310] global,problems [310] problems,world [310] world,continued Top Word Pairs in Tweet in G1:
[433] sep,2020 [291] 2020,#copernicus [246] #copernicus,#sentinel [221] #california,#usa [152] #sentinel,full [140] pierre_markuse,#sqfcomplex [138] 13,sep [131] smoke,plumes [116] full,size [115] #usa,13 Top Word Pairs in Tweet in G2:
[80] #opendata,#openscience [57] #openscience,#opendata [40] covid,19 [31] iochem,bd [25] avis,parution [25] parution,#données [25] #données,#opendata [25] #openscience,hors [25] hors,série [25] série,faire Top Word Pairs in Tweet in G3:
[261] μg,m3 [261] m3,pm10 [185] 09,2020 [158] #opendata,#opensource [156] #airquality,poor [156] poor,pm1 [155] #fcub,#fuoricomeunbalcone [155] #fuoricomeunbalcone,#opendata [155] #opensource,#openstandard [149] 59,#fcub Top Word Pairs in Tweet in G4:
[310] child,mortality [310] mortality,data [310] data,remains [310] remains,one [310] one,largest [310] largest,global [310] global,problems [310] problems,world [310] world,continued [310] continued,make Top Word Pairs in Tweet in G5:
[82] #datascience,#ai [69] top,sources [69] sources,#analytics [69] #analytics,#machinelearning [69] #machinelearning,datasets [69] datasets,google [69] google,gov [69] gov,kaggle [69] kaggle,amazon [69] amazon,uci Top Word Pairs in Tweet in G6:
[61] child,youth [56] youth,mortality [52] debt,service [50] find,means [49] check,interactive [49] interactive,dashboard [49] dashboard,see [49] see,upcoming [49] upcoming,monthly [49] monthly,debt Top Word Pairs in Tweet in G7:
[196] 正岡子規の俳句を季節別にオープンデータとしてcsv形式で提供してる松山市,マジでイカレ過ぎててloveしかねえよ [195] raise_4096,正岡子規の俳句を季節別にオープンデータとしてcsv形式で提供してる松山市 Top Word Pairs in Tweet in G8:
[46] inwoners,met [46] met,leeftijd [27] open,data [18] #będzin,#grodziec [18] 09,2020r [18] stacja,badawcza [18] imgw,pib [18] #opendata,bekijk [15] leeftijd,65 [15] 65,ouder Top Word Pairs in Tweet in G9:
[23] dades,obertes [21] open,data [15] covid,19 [13] barcelona,dades [13] follow,tomorrow [13] tomorrow,#dataforpolicy2020 [13] #dataforpolicy2020,emibaldacci's [13] emibaldacci's,data [13] data,governance [13] governance,policy Top Word Pairs in Tweet in G10:
[98] thanks,#opendata [98] #opendata,sharing [87] nextstrain,thanks [36] #covid19,#sarscov2 [35] sharing,gisaid [35] gisaid,we've [23] we've,updated [23] #sarscov2,sequences [19] sharing,irsicaixa [19] irsicaixa,seqcovid Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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