Shown here is a globe visualization of world-wide Google searches, categorized by one of 21 languages. The visualization is created with WebGL toolkit and bundled data from Chrome Experiments.
I have annotated the data with geographical information from MaxMind, to include city, region, and country for each search location. The closest city was determined by finding the entry in the MaxMind data set (2.8M cities) with the smallest haversine distance to the coordinates of the search term. Note that latitude and longitude were provided to 3 decimal places in the original data file but are available to 7 decimal places in the MaxMind set.
The annotated data file includes new fields
rank
(1-indexed rank of magnitude of search data point)
cumulative_value
(fractional total of all search terms with equal or smaller magnitude)
language_name
(name of the search language)
city
(closest city to latitude/longitude of search data point)
region
(region of closest city)
country
(country of closest city)
city_latitude, city_longitude
(coordinates of closest city)
Thanks to Evan Applegate from UC Davis for requesting an explanation of the additional fields. They were not obvious.
View all languages or individual data for the following languages: Arabic Belgian Chinese Dutch English Finnish French German Indonesian Italian Japanese Korean Norwegian Polish Portuguese Romanian Russian Spanish Swedish Thai Turkish
View top 5%, 10%, 15% of data.
View top 10 20 50 100 search locations.
View search density.
Showing volume of searches in Belgian.
The color legend was created based on the color scheme used in the original webgl-globe code.
There are 11 locations in the US with searches in Spanish: Dillard, Douglas, Flint Hill, Floyds Knobs, Great Falls, Orrs Island, Redwood Estates, Simpsonville, Spanish Fork, Spanish Fort, and Washington. Conspicuously, Los Angeles is missing.
The northern-most town in Mexico with a Spanish search is Mexicali (Baja Californa, lat 32.65 long -115.47).
The Chinese takeover (but not takeout) has been largely overestimated. Only two towns in the US participate in Chinese language searches: Williamsport and Evensville.
With the exception of Albouystown (Demerara-Mahaica, Guyana) and Paramaribo (Suriname), South America shows no English searches.
Asia shows interesting patterns. Namely, no English searches are seen from China. No doubt, political firewalls are the cause. By country, India leads with 82 searches, followed by Malaysia (64) and Pakistan (11). The full list is India (82), Malaysia (64), Pakistan (11), United (5), Bangladesh (4), Sri (3), Philippines (3), Nepal (3), Korea (3), Japan (2), Iran (2), Singapore (1), Papua (1), Myanmar (1), Maldives (1), Cambodia (1), Brunei (1), Bhutan (1), Afghanistan (1).
There are 25 locations with English language searches at latitude ≥ 60°. There are 15 cities in Alaska with searches (Anchorage, Barrow, Bethel, Cordova, Delta Junction, Eagle River, Fairbanks, Kenai, Nome, North Pole, Palmer, Seward, Soldotna, Valdez, Wasilla), of which Barrow is furthest north (lat 71.29°). The other 10 cities are mostly in Canada: Lerwick (Shetland Islands, United Kingdom, lat 60.160°), Whitehorse (Yukon Territory, Canada, lat 60.720°), Jarstad (Sogn og Fjordane, Norway, lat 61.360°), Fort Providence (Northwest Territories, Canada, lat 61.380°), Yellowknife (Northwest Territories, Canada, lat 62.450°), Frobisher Bay (Nunavut, Canada, lat 63.750°), Keflavík Gullbringusysla Iceland lat 64.010°), Inuvik (Northwest Territories, Canada, lat 68.340°), Gjoa Haven (Nunavut, Canada, lat 68.630°), Igloolik (Nunavut, Canada, lat 69.380°).
New Zealand and Australia dominate search loations in the far south. The southermost English search is from Invercargill (Southland, New Zealand, lat -46.4° — compare this to the northmost search from Barrow in Alaska at lat 71.29°). In Australia, the southermost search is from Davenport (Tasmania, Australia, lat -41.17°). In South Africa, the southermost search is from Hermanus (Western Cape, South Africa, lat -34.42°).
What is the most remote search location? Here, I define distance between locations by the haversine distance.
I tabulate three types of remote locations, by language, by finding
Cities, by language, most distant from their closest city.
The most remote search location of alll is Papeete, whose closest search data point is 2,287 km away — Fusi in American Samoa. Also interesting is the Belgian-speakinng Westerschelling in the Netherlands, which has the smallest maximum distance to its nearest city, by language. It is 25 km from Harlingen, Netherlands.
Cities, by language, most distant from their closest city, in which people speak (i.e. search) in the same language.
English searches are the most spread out on the globe. Of all search languuages, Mahe in Seychelles is furthest from its same-language nearest loccation of all other languages. It is 1,347 from Hamar in Somalia, in which English searches are found.
Cities, by language, most distant from their closest city, which is foreign (i.e. searching in a different language).
About 10% of all searches come from the top 10 locations.
I am surprised to see Miami here (bored retirees?) as well as Istanbul — I don't have a theory for that one.
38% of all searches come from the top 100 locations (out of 22,826), with English dominating (33/100) followed by Spanish (11/100).
The full breakdown for the top 100 locations by language is English (33), Spanish (11), German (8), Japanese (6), Dutch (6), Portuguese (5), French (5), Turkish (4), Italian (4), Chinese (4), Russian (3), Arabic (3), Polish (2), Thai (1), Swedish (1), Romanian (1), Korean (1), Indonesian (1), Finnish (1).
By country, the top 100 locations fall in United States (11), Germany (6), India (6), Japan (6), Brazil (5), United Kingdom (5), Italy (4), Turkey (4), Australia (3), France (3), Mexico (3), Russian Federation (3), Canada (2), China (2), Colombia (2), Poland (2), Saudi Arabia (2), Spain (2), Vietnam (2), Algeria (1), Argentina (1), Austria (1), Chile (1), Egypt (1), Finland (1), Greece (1), Hong Kong (1), Hungary (1), Indonesia (1), Ireland (1), Israel (1), Korea (1), Malaysia (1), Peru (1), Philippines (1), Romania (1), Serbia (1), Singapore (1), Sweden (1), Switzerland (1), Taiwan (1), Thailand (1), Tunisia (1), Ukraine (1), United Arab Emirates (1), Venezuela (1)
The top 100 locations are
Nature uses only the longest threads to weave her patterns, so that each small piece of her fabric reveals the organization of the entire tapestry. – Richard Feynman
Following up on our Neural network primer column, this month we explore a different kind of network architecture: a convolutional network.
The convolutional network replaces the hidden layer of a fully connected network (FCN) with one or more filters (a kind of neuron that looks at the input within a narrow window).
Even through convolutional networks have far fewer neurons that an FCN, they can perform substantially better for certain kinds of problems, such as sequence motif detection.
Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Convolutional neural networks. Nature Methods 20:.
Derry, A., Krzywinski, M. & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.
Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.
Nature is often hidden, sometimes overcome, seldom extinguished. —Francis Bacon
In the first of a series of columns about neural networks, we introduce them with an intuitive approach that draws from our discussion about logistic regression.
Simple neural networks are just a chain of linear regressions. And, although neural network models can get very complicated, their essence can be understood in terms of relatively basic principles.
We show how neural network components (neurons) can be arranged in the network and discuss the ideas of hidden layers. Using a simple data set we show how even a 3-neuron neural network can already model relatively complicated data patterns.
Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.
Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.
Our cover on the 11 January 2023 Cell Genomics issue depicts the process of determining the parent-of-origin using differential methylation of alleles at imprinted regions (iDMRs) is imagined as a circuit.
Designed in collaboration with with Carlos Urzua.
Akbari, V. et al. Parent-of-origin detection and chromosome-scale haplotyping using long-read DNA methylation sequencing and Strand-seq (2023) Cell Genomics 3(1).
Browse my gallery of cover designs.
My cover design on the 6 January 2023 Science Advances issue depicts DNA sequencing read translation in high-dimensional space. The image showss 672 bases of sequencing barcodes generated by three different single-cell RNA sequencing platforms were encoded as oriented triangles on the faces of three 7-dimensional cubes.
More details about the design.
Kijima, Y. et al. A universal sequencing read interpreter (2023) Science Advances 9.
Browse my gallery of cover designs.
If you sit on the sofa for your entire life, you’re running a higher risk of getting heart disease and cancer. —Alex Honnold, American rock climber
In a follow-up to our Survival analysis — time-to-event data and censoring article, we look at how regression can be used to account for additional risk factors in survival analysis.
We explore accelerated failure time regression (AFTR) and the Cox Proportional Hazards model (Cox PH).
Dey, T., Lipsitz, S.R., Cooper, Z., Trinh, Q., Krzywinski, M & Altman, N. (2022) Points of significance: Regression modeling of time-to-event data with censoring. Nature Methods 19:1513–1515.
My 5-dimensional animation sets the visual stage for Max Cooper's Ascent from the album Unspoken Words. I have previously collaborated with Max on telling a story about infinity for his Yearning for the Infinite album.
I provide a walkthrough the video, describe the animation system I created to generate the frames, and show you all the keyframes
The video recently premiered on YouTube.
Renders of the full scene are available as NFTs.