Visualizing Internet Measurements of Covid-19 Work-from-Home. Stutz, E., Pradkin, Y., Song, X., & Heidemann, J. In Proceedings of the National Symposium for NSF REU Research in Data Science, Systems, and Security (REU 2021 Symposium), pages 5633–5638, Virtual Workshop, December, 2021. IEEE. ![Visualizing Internet Measurements of Covid-19 Work-from-Home [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex The Covid-19 pandemic disrupted the world as businesses and schools shifted to work-from-home (WFH), and comprehensive maps have helped visualize how those policies changed over time and in different places. We recently developed algorithms that infer the onset of WFH based on changes in observed Internet usage. Measurements of WFH are important to evaluate how effectively policies are implemented and followed, or to confirm policies in countries with less transparent journalism. This paper describes a web-based visualization system for measurements of Covid-19-induced WFH\@. We build on a web-based world map, showing a geographic grid of observations about WFH\@. We extend typical map interaction (zoom and pan, plus animation over time) with two new forms of pop-up information that allow users to drill-down to investigate our underlying data. We use sparklines to show changes over the first 6 months of 2020 for a given location, supporting identification and navigation to hot spots. Alternatively, users can report particular networks (Internet Service Providers) that show WFH on a given day. We show that these tools help us relate our observations to news reports of Covid-19-induced changes and, in some cases, lockdowns due to other causes. Our visualization is publicly available at ˘rlhttps://covid.ant.isi.edu, as is our underlying data.
@InProceedings{Stutz21a,
author = "Erica Stutz and Yuri Pradkin and Xiao Song and John Heidemann",
title = "Visualizing {Internet} Measurements of
{Covid-19} Work-from-Home",
booktitle = "Proceedings of the " # "National Symposium for NSF REU Research in Data Science, Systems, and Security (REU 2021 Symposium)",
year = 2021,
sortdate = "2021-12-15",
project = "ant, minceq, eieio, reu, isireu",
jsubject = "topology_modeling",
pages = "5633--5638",
month = dec,
address = "Virtual Workshop",
publisher = "IEEE",
jlocation = "johnh: pafile",
keywords = "covid-19, work-from-home, visualization, trinocular",
doi = "https://doi.org/10.1109/BigData52589.2021.9671311",
url = "https://ant.isi.edu/%7ejohnh/PAPERS/Stutz21a.html",
pdfurl = "https://ant.isi.edu/%7ejohnh/PAPERS/Stutz21a.pdf",
conferenceurl = "https://bigdataieee.org/BigData2021/SpecialSymposium.html",
abstract = "The Covid-19 pandemic disrupted the world as businesses and schools
shifted to work-from-home (WFH), and comprehensive maps have helped
visualize how those policies changed over time and in different
places. We recently developed algorithms that infer the onset of WFH
based on changes in observed Internet usage. Measurements of WFH are
important to evaluate how effectively policies are implemented and
followed, or to confirm policies in countries with less transparent
journalism. This paper describes a web-based visualization system for
measurements of Covid-19-induced WFH\@. We build on a web-based world
map, showing a geographic grid of observations about WFH\@. We extend
typical map interaction (zoom and pan, plus animation over time) with
two new forms of pop-up information that allow users to drill-down to
investigate our underlying data. We use sparklines to show changes
over the first 6 months of 2020 for a given location, supporting
identification and navigation to hot spots. Alternatively, users can
report particular networks (Internet Service Providers) that show WFH
on a given day. We show that these tools help us relate our
observations to news reports of Covid-19-induced changes and, in some
cases, lockdowns due to other causes. Our visualization is publicly
available at \url{https://covid.ant.isi.edu}, as is our underlying
data."
,}
Downloads: 0
{"_id":"jDpcBsasojQdiKSAF","bibbaseid":"stutz-pradkin-song-heidemann-visualizinginternetmeasurementsofcovid19workfromhome-2021","author_short":["Stutz, E.","Pradkin, Y.","Song, X.","Heidemann, J."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Erica"],"propositions":[],"lastnames":["Stutz"],"suffixes":[]},{"firstnames":["Yuri"],"propositions":[],"lastnames":["Pradkin"],"suffixes":[]},{"firstnames":["Xiao"],"propositions":[],"lastnames":["Song"],"suffixes":[]},{"firstnames":["John"],"propositions":[],"lastnames":["Heidemann"],"suffixes":[]}],"title":"Visualizing Internet Measurements of Covid-19 Work-from-Home","booktitle":"Proceedings of the National Symposium for NSF REU Research in Data Science, Systems, and Security (REU 2021 Symposium)","year":"2021","sortdate":"2021-12-15","project":"ant, minceq, eieio, reu, isireu","jsubject":"topology_modeling","pages":"5633–5638","month":"December","address":"Virtual Workshop","publisher":"IEEE","jlocation":"johnh: pafile","keywords":"covid-19, work-from-home, visualization, trinocular","doi":"https://doi.org/10.1109/BigData52589.2021.9671311","url":"https://ant.isi.edu/%7ejohnh/PAPERS/Stutz21a.html","pdfurl":"https://ant.isi.edu/%7ejohnh/PAPERS/Stutz21a.pdf","conferenceurl":"https://bigdataieee.org/BigData2021/SpecialSymposium.html","abstract":"The Covid-19 pandemic disrupted the world as businesses and schools shifted to work-from-home (WFH), and comprehensive maps have helped visualize how those policies changed over time and in different places. We recently developed algorithms that infer the onset of WFH based on changes in observed Internet usage. Measurements of WFH are important to evaluate how effectively policies are implemented and followed, or to confirm policies in countries with less transparent journalism. This paper describes a web-based visualization system for measurements of Covid-19-induced WFH\\@. We build on a web-based world map, showing a geographic grid of observations about WFH\\@. We extend typical map interaction (zoom and pan, plus animation over time) with two new forms of pop-up information that allow users to drill-down to investigate our underlying data. We use sparklines to show changes over the first 6 months of 2020 for a given location, supporting identification and navigation to hot spots. Alternatively, users can report particular networks (Internet Service Providers) that show WFH on a given day. We show that these tools help us relate our observations to news reports of Covid-19-induced changes and, in some cases, lockdowns due to other causes. Our visualization is publicly available at ˘rlhttps://covid.ant.isi.edu, as is our underlying data.","bibtex":"@InProceedings{Stutz21a,\n author = \"Erica Stutz and Yuri Pradkin and Xiao Song and John Heidemann\",\n title = \"Visualizing {Internet} Measurements of\n {Covid-19} Work-from-Home\",\n booktitle = \"Proceedings of the \" # \"National Symposium for NSF REU Research in Data Science, Systems, and Security (REU 2021 Symposium)\",\n year = 2021,\n\tsortdate = \t\"2021-12-15\", \n\tproject = \"ant, minceq, eieio, reu, isireu\",\n\tjsubject = \"topology_modeling\",\n pages = \"5633--5638\",\n month = dec,\n address = \"Virtual Workshop\",\n publisher = \"IEEE\",\n jlocation = \"johnh: pafile\",\n keywords = \"covid-19, work-from-home, visualization, trinocular\",\n doi = \"https://doi.org/10.1109/BigData52589.2021.9671311\",\n\turl =\t\t\"https://ant.isi.edu/%7ejohnh/PAPERS/Stutz21a.html\",\n\tpdfurl =\t\"https://ant.isi.edu/%7ejohnh/PAPERS/Stutz21a.pdf\",\n\tconferenceurl = \"https://bigdataieee.org/BigData2021/SpecialSymposium.html\",\n\tabstract = \"The Covid-19 pandemic disrupted the world as businesses and schools\nshifted to work-from-home (WFH), and comprehensive maps have helped\nvisualize how those policies changed over time and in different\nplaces. We recently developed algorithms that infer the onset of WFH\nbased on changes in observed Internet usage. Measurements of WFH are\nimportant to evaluate how effectively policies are implemented and\nfollowed, or to confirm policies in countries with less transparent\njournalism. This paper describes a web-based visualization system for\nmeasurements of Covid-19-induced WFH\\@. We build on a web-based world\nmap, showing a geographic grid of observations about WFH\\@. We extend\ntypical map interaction (zoom and pan, plus animation over time) with\ntwo new forms of pop-up information that allow users to drill-down to\ninvestigate our underlying data. We use sparklines to show changes\nover the first 6 months of 2020 for a given location, supporting\nidentification and navigation to hot spots. Alternatively, users can\nreport particular networks (Internet Service Providers) that show WFH\non a given day. We show that these tools help us relate our\nobservations to news reports of Covid-19-induced changes and, in some\ncases, lockdowns due to other causes. Our visualization is publicly\navailable at \\url{https://covid.ant.isi.edu}, as is our underlying\ndata.\"\n,}\n\n\n","author_short":["Stutz, E.","Pradkin, Y.","Song, X.","Heidemann, J."],"bibbaseid":"stutz-pradkin-song-heidemann-visualizinginternetmeasurementsofcovid19workfromhome-2021","role":"author","urls":{"Paper":"https://ant.isi.edu/%7ejohnh/PAPERS/Stutz21a.html"},"keyword":["covid-19","work-from-home","visualization","trinocular"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://bibbase.org/f/dHevizJoWEhWowz8q/johnh-2023-2.bib","dataSources":["YLyu3mj3xsBeoqiHK","fLZcDgNSoSuatv6aX","fxEParwu2ZfurScPY","7nuQvtHTqKrLmgu99"],"keywords":["covid-19","work-from-home","visualization","trinocular"],"search_terms":["visualizing","internet","measurements","covid","work","home","stutz","pradkin","song","heidemann"],"title":"Visualizing Internet Measurements of Covid-19 Work-from-Home","year":2021}