[Release]

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[Release]

Oliver Keyes-4
Hey all!

We've released a highly-aggregated dataset of readership data -
specifically, data about where, geographically, traffic to each of our
projects (and all of our projects) comes from. The data can be found
at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
put together an exploration tool for it at
https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/

Hope it's useful to people!

--
Oliver Keyes
Research Analyst
Wikimedia Foundation

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Re: [Analytics] [Release]

Pine W

Very nice. Do you think that you could pick out a few of your favorite graphs and add them to this week's Recent Research report in a gallery?

Thanks!
Pine

Hey all!

We've released a highly-aggregated dataset of readership data -
specifically, data about where, geographically, traffic to each of our
projects (and all of our projects) comes from. The data can be found
at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
put together an exploration tool for it at
https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/

Hope it's useful to people!

--
Oliver Keyes
Research Analyst
Wikimedia Foundation

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Re: [Analytics] [Release]

Oliver Keyes-4
Totally! I'm also going to get together with some NEU hackers tomorrow
and work on actually visualising the data on *drumroll* maps, which'd
probably be more interesting eye candy than infinite bar plots :)

On 25 February 2015 at 16:19, Pine W <[hidden email]> wrote:

> Very nice. Do you think that you could pick out a few of your favorite
> graphs and add them to this week's Recent Research report in a gallery?
>
> Thanks!
> Pine
>
> Hey all!
>
> We've released a highly-aggregated dataset of readership data -
> specifically, data about where, geographically, traffic to each of our
> projects (and all of our projects) comes from. The data can be found
> at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
> put together an exploration tool for it at
> https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/
>
> Hope it's useful to people!
>
> --
> Oliver Keyes
> Research Analyst
> Wikimedia Foundation
>
> _______________________________________________
> Analytics mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/analytics
>
> _______________________________________________
> Analytics mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/analytics
>



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Oliver Keyes
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Re: [Analytics] [Release]

Pine W

Excellent!

Pine

On Feb 25, 2015 1:26 PM, "Oliver Keyes" <[hidden email]> wrote:
Totally! I'm also going to get together with some NEU hackers tomorrow
and work on actually visualising the data on *drumroll* maps, which'd
probably be more interesting eye candy than infinite bar plots :)

On 25 February 2015 at 16:19, Pine W <[hidden email]> wrote:
> Very nice. Do you think that you could pick out a few of your favorite
> graphs and add them to this week's Recent Research report in a gallery?
>
> Thanks!
> Pine
>
> Hey all!
>
> We've released a highly-aggregated dataset of readership data -
> specifically, data about where, geographically, traffic to each of our
> projects (and all of our projects) comes from. The data can be found
> at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
> put together an exploration tool for it at
> https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/
>
> Hope it's useful to people!
>
> --
> Oliver Keyes
> Research Analyst
> Wikimedia Foundation
>
> _______________________________________________
> Analytics mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/analytics
>
> _______________________________________________
> Analytics mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/analytics
>



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Re: [Release]

Andrew Lih
In reply to this post by Oliver Keyes-4
Great job.

Who knew Esperanto was big in Japan and China at #2 and #3?



On Wed, Feb 25, 2015 at 4:06 PM, Oliver Keyes <[hidden email]> wrote:
Hey all!

We've released a highly-aggregated dataset of readership data -
specifically, data about where, geographically, traffic to each of our
projects (and all of our projects) comes from. The data can be found
at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
put together an exploration tool for it at
https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/

Hope it's useful to people!

--
Oliver Keyes
Research Analyst
Wikimedia Foundation

_______________________________________________
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https://lists.wikimedia.org/mailman/listinfo/wiki-research-l


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Re: [Release]

Oliver Keyes-4
The one major caveat, I think, is that the danger of proportionate
data is that it makes small projects very vulnerable to artificial
traffic spikes. I'd go out on a limb and say that some of the massive
bumps in popularity we see in particular combinations are likely due
to either undetected automata or simply a project having so little
traffic that a small number of people can sway the results
outlandishly.

On 25 February 2015 at 16:32, Andrew Lih <[hidden email]> wrote:

> Great job.
>
> Who knew Esperanto was big in Japan and China at #2 and #3?
>
>
>
> On Wed, Feb 25, 2015 at 4:06 PM, Oliver Keyes <[hidden email]> wrote:
>>
>> Hey all!
>>
>> We've released a highly-aggregated dataset of readership data -
>> specifically, data about where, geographically, traffic to each of our
>> projects (and all of our projects) comes from. The data can be found
>> at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
>> put together an exploration tool for it at
>> https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/
>>
>> Hope it's useful to people!
>>
>> --
>> Oliver Keyes
>> Research Analyst
>> Wikimedia Foundation
>>
>> _______________________________________________
>> Wiki-research-l mailing list
>> [hidden email]
>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>
>
>
> _______________________________________________
> Wiki-research-l mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>



--
Oliver Keyes
Research Analyst
Wikimedia Foundation

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Re: [Analytics] [Release]

Oliver Keyes-4
Yours is looking at just December, while mine is looking at the entire
year, for starters. Also, what's the apps/mobile web inclusion for
that report?

On 25 February 2015 at 17:34, Erik Zachte <[hidden email]> wrote:

> I am surprised that the new data, with crawlers excluded, show more wp:en traffic from US (43%) than the old data (36.4% for 2014), which contained much crawler traffic, presumably most of that from US.
>
> Compare https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/ and
> http://stats.wikimedia.org/wikimedia/squids/SquidReportPageViewsPerLanguageBreakdown.htm
>
> Any thoughts?
>
> Erik
>
> -----Original Message-----
> From: [hidden email] [mailto:[hidden email]] On Behalf Of Oliver Keyes
> Sent: Wednesday, February 25, 2015 22:37
> To: Research into Wikimedia content and communities
> Cc: A mailing list for the Analytics Team at WMF and everybody who has an interest in Wikipedia and analytics.
> Subject: Re: [Analytics] [Wiki-research-l] [Release]
>
> The one major caveat, I think, is that the danger of proportionate data is that it makes small projects very vulnerable to artificial traffic spikes. I'd go out on a limb and say that some of the massive bumps in popularity we see in particular combinations are likely due to either undetected automata or simply a project having so little traffic that a small number of people can sway the results outlandishly.
>
> On 25 February 2015 at 16:32, Andrew Lih <[hidden email]> wrote:
>> Great job.
>>
>> Who knew Esperanto was big in Japan and China at #2 and #3?
>>
>>
>>
>> On Wed, Feb 25, 2015 at 4:06 PM, Oliver Keyes <[hidden email]> wrote:
>>>
>>> Hey all!
>>>
>>> We've released a highly-aggregated dataset of readership data -
>>> specifically, data about where, geographically, traffic to each of
>>> our projects (and all of our projects) comes from. The data can be
>>> found at http://dx.doi.org/10.6084/m9.figshare.1317408 -
>>> additionally, I've put together an exploration tool for it at
>>> https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/
>>>
>>> Hope it's useful to people!
>>>
>>> --
>>> Oliver Keyes
>>> Research Analyst
>>> Wikimedia Foundation
>>>
>>> _______________________________________________
>>> Wiki-research-l mailing list
>>> [hidden email]
>>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>
>>
>>
>> _______________________________________________
>> Wiki-research-l mailing list
>> [hidden email]
>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>
>
>
>
> --
> Oliver Keyes
> Research Analyst
> Wikimedia Foundation
>
> _______________________________________________
> Analytics mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/analytics
>
>
> _______________________________________________
> Analytics mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/analytics



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Re: [Release]

Giovanni Luca Ciampaglia-3
In reply to this post by Oliver Keyes-4
This is really, really cool, great job guys!

G


Giovanni Luca Ciampaglia

✎ 919 E 10th ∙ Bloomington 47408 IN ∙ USA
http://www.glciampaglia.com/
✆ +1 812 855-7261
[hidden email]

2015-02-25 16:06 GMT-05:00 Oliver Keyes <[hidden email]>:
Hey all!

We've released a highly-aggregated dataset of readership data -
specifically, data about where, geographically, traffic to each of our
projects (and all of our projects) comes from. The data can be found
at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
put together an exploration tool for it at
https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/

Hope it's useful to people!

--
Oliver Keyes
Research Analyst
Wikimedia Foundation

_______________________________________________
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Re: [Analytics] [Release]

Federico Leva (Nemo)
In reply to this post by Oliver Keyes-4
Erik Zachte, 25/02/2015 23:34:
> Compare https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/  and
> http://stats.wikimedia.org/wikimedia/squids/SquidReportPageViewsPerLanguageBreakdown.htm

Ironholds' looks more vulnerable to bots, it's easier to see in small
wikis (though, kudos! many more small wikis are included than in
wikistats). For instance, 20 more percentage points for USA on Breton
and Bavarian Wikipedias, 30 on Welsh, 40 on Alemannic, almost 50 on
Kurdish. For Chinese bots they look similar, though in some cases I'm
not sure what's going on: for instance als.wiki also sees CH and RO emerge.

Will the new pageviews definition use the same bot filtering method?

Nemo

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Re: [Analytics] [Release]

Han-Teng Liao (OII)-2
Great work!

One way for further analysis of such kind of geolinguistic aggregate is to do some data normalization, or geographic normalization, as demonstrated by my previous work:  http://www.opensym.org/os2014-files/proceedings/p611.pdf


Currently, it has Population (LP), Internet users (IPop), Economy Size (PPPGDP), etc. estimation based on "even distribution" across percentage share of language population per country based on the Unicode CLDR 25 Territory-Language Information. 

A simple linear regression can reveal, say, which geo-linguistic, geographic, or linguistic category has less-than-expected or more-than-expected proportional of viewing traffic, with the expected values being generated according to the sizes of population, Internet population, economy. 

I hope this great work by Nemo can be extended to cover

(1) time-series report and data release

(2) edits aggregate


Altogether the tools and datasets will be a major milestone to monitor the language/project development across Wikimedia projects. Congrats!

Best,
han-teng liao

2015-02-26 8:31 GMT+01:00 Federico Leva (Nemo) <[hidden email]>:
Erik Zachte, 25/02/2015 23:34:
Compare https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/  and
http://stats.wikimedia.org/wikimedia/squids/SquidReportPageViewsPerLanguageBreakdown.htm

Ironholds' looks more vulnerable to bots, it's easier to see in small wikis (though, kudos! many more small wikis are included than in wikistats). For instance, 20 more percentage points for USA on Breton and Bavarian Wikipedias, 30 on Welsh, 40 on Alemannic, almost 50 on Kurdish. For Chinese bots they look similar, though in some cases I'm not sure what's going on: for instance als.wiki also sees CH and RO emerge.

Will the new pageviews definition use the same bot filtering method?

Nemo


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Re: [Release]

fn
In reply to this post by Oliver Keyes-4
Hi Oliver,


Interesting dataset! I am curious about why the Danish Wikipedia is so
highly acccessed from Sweden. Could it be an error, e.g., with Telia
IP-numbers?

In Python:

 >>> import pandas as pd
 >>> df =
pd.read_csv('http://files.figshare.com/1923822/language_pageviews_per_country.tsv',
sep='\t')
 >>> df.ix[df.project == 'da.wikipedia.org', ['country',
'pageviews_percentage']].set_index('country')
pageviews_percentage
country
Austria                            1
China                              1
Denmark                           61
Estonia                            1
France                             1
Germany                            2
Netherlands                        2
Norway                             1
Sweden                            18
United Kingdom                     3
United States                      3
Other                              5


MaxMind has some numbers on their own accuracy:

https://www.maxmind.com/en/geoip2-city-database-accuracy

For Denmark 85% is "Correctly Resolved", for Sweden only 68%. I wonder
if this really could bias the result so much.

If the numbers are correct why would the Swedish read the Danish
Wikipedia so much? Bots? It does not apply the other way around: Only 2%
of the traffic to Swedish Wikipedia comes from Denmark.



best regards
Finn



On 02/25/2015 10:06 PM, Oliver Keyes wrote:

> Hey all!
>
> We've released a highly-aggregated dataset of readership data -
> specifically, data about where, geographically, traffic to each of our
> projects (and all of our projects) comes from. The data can be found
> at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
> put together an exploration tool for it at
> https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/
>
> Hope it's useful to people!
>


--
Finn Årup Nielsen
http://people.compute.dtu.dk/faan/

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Re: [Release]

Han-Teng Liao (OII)-2
Hello Finn, 
   I do not have a specific answer to your question. However, it might be worthwhile to add Finnish in to the comparison as according to the CLDR 26 T-L information http://www.unicode.org/cldr/charts/26/supplemental/territory_language_information.html 

   You have some sizable Finnish language speakers in Sweden: 
 
Swedish {O} sv 95.0% 99.0%
Finnish {OR} fi 2.2%

    So if the similar query is executed on Finnish language, and the results also show some "undue" proportion of visits from Sweden, then what you observed as anomaly is the that unique. We probably need many iterations of comparative outcomes and normalization of data (Sweden does have higher population).  Also, it might be handy to have some statistics on immigration or residence, it is EU. I will not be surprised that for example the  visits from Oxford to Wikipedia website have sizable German language requests. 

    I am still a bit bothered by the number "1" in the current dataset. It does not feel right since the numbers of 1.4% and 0.6% is a notable difference in this regard. Perhaps we need some high precision "universal percentage" number for each territory-language pair. It would be also great to do another set of aggregation: i.e. given a territory, which language versions of Wikipedia are accessed....

Best,
han-teng liao

2015-03-02 13:54 GMT+01:00 Finn Årup Nielsen <[hidden email]>:
Hi Oliver,


Interesting dataset! I am curious about why the Danish Wikipedia is so highly acccessed from Sweden. Could it be an error, e.g., with Telia IP-numbers?

In Python:

>>> import pandas as pd
>>> df = pd.read_csv('http://files.figshare.com/1923822/language_pageviews_per_country.tsv', sep='\t')
>>> df.ix[df.project == 'da.wikipedia.org', ['country', 'pageviews_percentage']].set_index('country') pageviews_percentage
country
Austria                            1
China                              1
Denmark                           61
Estonia                            1
France                             1
Germany                            2
Netherlands                        2
Norway                             1
Sweden                            18
United Kingdom                     3
United States                      3
Other                              5


MaxMind has some numbers on their own accuracy:

https://www.maxmind.com/en/geoip2-city-database-accuracy

For Denmark 85% is "Correctly Resolved", for Sweden only 68%. I wonder if this really could bias the result so much.

If the numbers are correct why would the Swedish read the Danish Wikipedia so much? Bots? It does not apply the other way around: Only 2% of the traffic to Swedish Wikipedia comes from Denmark.



best regards
Finn



On 02/25/2015 10:06 PM, Oliver Keyes wrote:
Hey all!

We've released a highly-aggregated dataset of readership data -
specifically, data about where, geographically, traffic to each of our
projects (and all of our projects) comes from. The data can be found
at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
put together an exploration tool for it at
https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/

Hope it's useful to people!



--
Finn Årup Nielsen
http://people.compute.dtu.dk/faan/


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Re: [Release]

Oliver Keyes-4
Indeed! Orienting it that way (pivoting on language rather than
project) is something several people have asked for; I plan to spend a
chunk of my spare time (that is, recreational time) trying to make it
work. Should be fairly trivial.

On 2 March 2015 at 09:55, h <[hidden email]> wrote:

> Hello Finn,
>    I do not have a specific answer to your question. However, it might be
> worthwhile to add Finnish in to the comparison as according to the CLDR 26
> T-L information
> http://www.unicode.org/cldr/charts/26/supplemental/territory_language_information.html
>
>    You have some sizable Finnish language speakers in Sweden:
>
> Swedish {O} sv 95.0% 99.0%
> Finnish {OR} fi 2.2%
>
>     So if the similar query is executed on Finnish language, and the results
> also show some "undue" proportion of visits from Sweden, then what you
> observed as anomaly is the that unique. We probably need many iterations of
> comparative outcomes and normalization of data (Sweden does have higher
> population).  Also, it might be handy to have some statistics on immigration
> or residence, it is EU. I will not be surprised that for example the  visits
> from Oxford to Wikipedia website have sizable German language requests.
>
>     I am still a bit bothered by the number "1" in the current dataset. It
> does not feel right since the numbers of 1.4% and 0.6% is a notable
> difference in this regard. Perhaps we need some high precision "universal
> percentage" number for each territory-language pair. It would be also great
> to do another set of aggregation: i.e. given a territory, which language
> versions of Wikipedia are accessed....
>
> Best,
> han-teng liao
>
> 2015-03-02 13:54 GMT+01:00 Finn Årup Nielsen <[hidden email]>:
>>
>> Hi Oliver,
>>
>>
>> Interesting dataset! I am curious about why the Danish Wikipedia is so
>> highly acccessed from Sweden. Could it be an error, e.g., with Telia
>> IP-numbers?
>>
>> In Python:
>>
>> >>> import pandas as pd
>> >>> df =
>> >>> pd.read_csv('http://files.figshare.com/1923822/language_pageviews_per_country.tsv',
>> >>> sep='\t')
>> >>> df.ix[df.project == 'da.wikipedia.org', ['country',
>> >>> 'pageviews_percentage']].set_index('country') pageviews_percentage
>> country
>> Austria                            1
>> China                              1
>> Denmark                           61
>> Estonia                            1
>> France                             1
>> Germany                            2
>> Netherlands                        2
>> Norway                             1
>> Sweden                            18
>> United Kingdom                     3
>> United States                      3
>> Other                              5
>>
>>
>> MaxMind has some numbers on their own accuracy:
>>
>> https://www.maxmind.com/en/geoip2-city-database-accuracy
>>
>> For Denmark 85% is "Correctly Resolved", for Sweden only 68%. I wonder if
>> this really could bias the result so much.
>>
>> If the numbers are correct why would the Swedish read the Danish Wikipedia
>> so much? Bots? It does not apply the other way around: Only 2% of the
>> traffic to Swedish Wikipedia comes from Denmark.
>>
>>
>>
>> best regards
>> Finn
>>
>>
>>
>> On 02/25/2015 10:06 PM, Oliver Keyes wrote:
>>>
>>> Hey all!
>>>
>>> We've released a highly-aggregated dataset of readership data -
>>> specifically, data about where, geographically, traffic to each of our
>>> projects (and all of our projects) comes from. The data can be found
>>> at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
>>> put together an exploration tool for it at
>>> https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/
>>>
>>> Hope it's useful to people!
>>>
>>
>>
>> --
>> Finn Årup Nielsen
>> http://people.compute.dtu.dk/faan/
>>
>>
>> _______________________________________________
>> Wiki-research-l mailing list
>> [hidden email]
>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>
>
>
> _______________________________________________
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> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>



--
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Research Analyst
Wikimedia Foundation

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Re: [Release]

Oliver Keyes-4
Update: the original Shiny instance went down due to server load soon
after release. It's now up again at http://datavis.wmflabs.org/where/
on a dedicated Labs machine, where we hope to put...many more
visualisations. It also now has mapping, largely thanks to Sarah
Laplante (http://sarahlaplante.com/), and soon it will hopefully be
/non-hideous/ mapping (the current mass of blue and grey is because my
aesthetic tastes are...I don't actually have any aesthetic tastes)

On 2 March 2015 at 22:36, Oliver Keyes <[hidden email]> wrote:

> Indeed! Orienting it that way (pivoting on language rather than
> project) is something several people have asked for; I plan to spend a
> chunk of my spare time (that is, recreational time) trying to make it
> work. Should be fairly trivial.
>
> On 2 March 2015 at 09:55, h <[hidden email]> wrote:
>> Hello Finn,
>>    I do not have a specific answer to your question. However, it might be
>> worthwhile to add Finnish in to the comparison as according to the CLDR 26
>> T-L information
>> http://www.unicode.org/cldr/charts/26/supplemental/territory_language_information.html
>>
>>    You have some sizable Finnish language speakers in Sweden:
>>
>> Swedish {O} sv 95.0% 99.0%
>> Finnish {OR} fi 2.2%
>>
>>     So if the similar query is executed on Finnish language, and the results
>> also show some "undue" proportion of visits from Sweden, then what you
>> observed as anomaly is the that unique. We probably need many iterations of
>> comparative outcomes and normalization of data (Sweden does have higher
>> population).  Also, it might be handy to have some statistics on immigration
>> or residence, it is EU. I will not be surprised that for example the  visits
>> from Oxford to Wikipedia website have sizable German language requests.
>>
>>     I am still a bit bothered by the number "1" in the current dataset. It
>> does not feel right since the numbers of 1.4% and 0.6% is a notable
>> difference in this regard. Perhaps we need some high precision "universal
>> percentage" number for each territory-language pair. It would be also great
>> to do another set of aggregation: i.e. given a territory, which language
>> versions of Wikipedia are accessed....
>>
>> Best,
>> han-teng liao
>>
>> 2015-03-02 13:54 GMT+01:00 Finn Årup Nielsen <[hidden email]>:
>>>
>>> Hi Oliver,
>>>
>>>
>>> Interesting dataset! I am curious about why the Danish Wikipedia is so
>>> highly acccessed from Sweden. Could it be an error, e.g., with Telia
>>> IP-numbers?
>>>
>>> In Python:
>>>
>>> >>> import pandas as pd
>>> >>> df =
>>> >>> pd.read_csv('http://files.figshare.com/1923822/language_pageviews_per_country.tsv',
>>> >>> sep='\t')
>>> >>> df.ix[df.project == 'da.wikipedia.org', ['country',
>>> >>> 'pageviews_percentage']].set_index('country') pageviews_percentage
>>> country
>>> Austria                            1
>>> China                              1
>>> Denmark                           61
>>> Estonia                            1
>>> France                             1
>>> Germany                            2
>>> Netherlands                        2
>>> Norway                             1
>>> Sweden                            18
>>> United Kingdom                     3
>>> United States                      3
>>> Other                              5
>>>
>>>
>>> MaxMind has some numbers on their own accuracy:
>>>
>>> https://www.maxmind.com/en/geoip2-city-database-accuracy
>>>
>>> For Denmark 85% is "Correctly Resolved", for Sweden only 68%. I wonder if
>>> this really could bias the result so much.
>>>
>>> If the numbers are correct why would the Swedish read the Danish Wikipedia
>>> so much? Bots? It does not apply the other way around: Only 2% of the
>>> traffic to Swedish Wikipedia comes from Denmark.
>>>
>>>
>>>
>>> best regards
>>> Finn
>>>
>>>
>>>
>>> On 02/25/2015 10:06 PM, Oliver Keyes wrote:
>>>>
>>>> Hey all!
>>>>
>>>> We've released a highly-aggregated dataset of readership data -
>>>> specifically, data about where, geographically, traffic to each of our
>>>> projects (and all of our projects) comes from. The data can be found
>>>> at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
>>>> put together an exploration tool for it at
>>>> https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/
>>>>
>>>> Hope it's useful to people!
>>>>
>>>
>>>
>>> --
>>> Finn Årup Nielsen
>>> http://people.compute.dtu.dk/faan/
>>>
>>>
>>> _______________________________________________
>>> Wiki-research-l mailing list
>>> [hidden email]
>>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>
>>
>>
>> _______________________________________________
>> Wiki-research-l mailing list
>> [hidden email]
>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>
>
>
>
> --
> Oliver Keyes
> Research Analyst
> Wikimedia Foundation



--
Oliver Keyes
Research Analyst
Wikimedia Foundation

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Re: [Release]

Dario Taraborelli-3
yay, shiny! The map is a pretty compelling way to show how dominant traffic from the US is, even for very minor languages (say bi.wikipedia.org), I wonder how many requests from US-based bots/automata we’re still failing to detect.

> On Mar 3, 2015, at 9:29 PM, Oliver Keyes <[hidden email]> wrote:
>
> Update: the original Shiny instance went down due to server load soon
> after release. It's now up again at http://datavis.wmflabs.org/where/
> on a dedicated Labs machine, where we hope to put...many more
> visualisations. It also now has mapping, largely thanks to Sarah
> Laplante (http://sarahlaplante.com/), and soon it will hopefully be
> /non-hideous/ mapping (the current mass of blue and grey is because my
> aesthetic tastes are...I don't actually have any aesthetic tastes)
>
> On 2 March 2015 at 22:36, Oliver Keyes <[hidden email]> wrote:
>> Indeed! Orienting it that way (pivoting on language rather than
>> project) is something several people have asked for; I plan to spend a
>> chunk of my spare time (that is, recreational time) trying to make it
>> work. Should be fairly trivial.
>>
>> On 2 March 2015 at 09:55, h <[hidden email]> wrote:
>>> Hello Finn,
>>>   I do not have a specific answer to your question. However, it might be
>>> worthwhile to add Finnish in to the comparison as according to the CLDR 26
>>> T-L information
>>> http://www.unicode.org/cldr/charts/26/supplemental/territory_language_information.html
>>>
>>>   You have some sizable Finnish language speakers in Sweden:
>>>
>>> Swedish {O} sv 95.0% 99.0%
>>> Finnish {OR} fi 2.2%
>>>
>>>    So if the similar query is executed on Finnish language, and the results
>>> also show some "undue" proportion of visits from Sweden, then what you
>>> observed as anomaly is the that unique. We probably need many iterations of
>>> comparative outcomes and normalization of data (Sweden does have higher
>>> population).  Also, it might be handy to have some statistics on immigration
>>> or residence, it is EU. I will not be surprised that for example the  visits
>>> from Oxford to Wikipedia website have sizable German language requests.
>>>
>>>    I am still a bit bothered by the number "1" in the current dataset. It
>>> does not feel right since the numbers of 1.4% and 0.6% is a notable
>>> difference in this regard. Perhaps we need some high precision "universal
>>> percentage" number for each territory-language pair. It would be also great
>>> to do another set of aggregation: i.e. given a territory, which language
>>> versions of Wikipedia are accessed....
>>>
>>> Best,
>>> han-teng liao
>>>
>>> 2015-03-02 13:54 GMT+01:00 Finn Årup Nielsen <[hidden email]>:
>>>>
>>>> Hi Oliver,
>>>>
>>>>
>>>> Interesting dataset! I am curious about why the Danish Wikipedia is so
>>>> highly acccessed from Sweden. Could it be an error, e.g., with Telia
>>>> IP-numbers?
>>>>
>>>> In Python:
>>>>
>>>>>>> import pandas as pd
>>>>>>> df =
>>>>>>> pd.read_csv('http://files.figshare.com/1923822/language_pageviews_per_country.tsv',
>>>>>>> sep='\t')
>>>>>>> df.ix[df.project == 'da.wikipedia.org', ['country',
>>>>>>> 'pageviews_percentage']].set_index('country') pageviews_percentage
>>>> country
>>>> Austria                            1
>>>> China                              1
>>>> Denmark                           61
>>>> Estonia                            1
>>>> France                             1
>>>> Germany                            2
>>>> Netherlands                        2
>>>> Norway                             1
>>>> Sweden                            18
>>>> United Kingdom                     3
>>>> United States                      3
>>>> Other                              5
>>>>
>>>>
>>>> MaxMind has some numbers on their own accuracy:
>>>>
>>>> https://www.maxmind.com/en/geoip2-city-database-accuracy
>>>>
>>>> For Denmark 85% is "Correctly Resolved", for Sweden only 68%. I wonder if
>>>> this really could bias the result so much.
>>>>
>>>> If the numbers are correct why would the Swedish read the Danish Wikipedia
>>>> so much? Bots? It does not apply the other way around: Only 2% of the
>>>> traffic to Swedish Wikipedia comes from Denmark.
>>>>
>>>>
>>>>
>>>> best regards
>>>> Finn
>>>>
>>>>
>>>>
>>>> On 02/25/2015 10:06 PM, Oliver Keyes wrote:
>>>>>
>>>>> Hey all!
>>>>>
>>>>> We've released a highly-aggregated dataset of readership data -
>>>>> specifically, data about where, geographically, traffic to each of our
>>>>> projects (and all of our projects) comes from. The data can be found
>>>>> at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
>>>>> put together an exploration tool for it at
>>>>> https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/
>>>>>
>>>>> Hope it's useful to people!
>>>>>
>>>>
>>>>
>>>> --
>>>> Finn Årup Nielsen
>>>> http://people.compute.dtu.dk/faan/
>>>>
>>>>
>>>> _______________________________________________
>>>> Wiki-research-l mailing list
>>>> [hidden email]
>>>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>>
>>>
>>>
>>> _______________________________________________
>>> Wiki-research-l mailing list
>>> [hidden email]
>>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>>
>>
>>
>>
>> --
>> Oliver Keyes
>> Research Analyst
>> Wikimedia Foundation
>
>
>
> --
> Oliver Keyes
> Research Analyst
> Wikimedia Foundation
>
> _______________________________________________
> Wiki-research-l mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l


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Re: [Release]

Oliver Keyes-5
'Lots, but that's not currently anyone's job'

On Wednesday, 4 March 2015, Dario Taraborelli <[hidden email]> wrote:
yay, shiny! The map is a pretty compelling way to show how dominant traffic from the US is, even for very minor languages (say bi.wikipedia.org), I wonder how many requests from US-based bots/automata we’re still failing to detect.

> On Mar 3, 2015, at 9:29 PM, Oliver Keyes <<a href="javascript:;" onclick="_e(event, &#39;cvml&#39;, &#39;okeyes@wikimedia.org&#39;)">okeyes@...> wrote:
>
> Update: the original Shiny instance went down due to server load soon
> after release. It's now up again at http://datavis.wmflabs.org/where/
> on a dedicated Labs machine, where we hope to put...many more
> visualisations. It also now has mapping, largely thanks to Sarah
> Laplante (http://sarahlaplante.com/), and soon it will hopefully be
> /non-hideous/ mapping (the current mass of blue and grey is because my
> aesthetic tastes are...I don't actually have any aesthetic tastes)
>
> On 2 March 2015 at 22:36, Oliver Keyes <<a href="javascript:;" onclick="_e(event, &#39;cvml&#39;, &#39;okeyes@wikimedia.org&#39;)">okeyes@...> wrote:
>> Indeed! Orienting it that way (pivoting on language rather than
>> project) is something several people have asked for; I plan to spend a
>> chunk of my spare time (that is, recreational time) trying to make it
>> work. Should be fairly trivial.
>>
>> On 2 March 2015 at 09:55, h <<a href="javascript:;" onclick="_e(event, &#39;cvml&#39;, &#39;hanteng@gmail.com&#39;)">hanteng@...> wrote:
>>> Hello Finn,
>>>   I do not have a specific answer to your question. However, it might be
>>> worthwhile to add Finnish in to the comparison as according to the CLDR 26
>>> T-L information
>>> http://www.unicode.org/cldr/charts/26/supplemental/territory_language_information.html
>>>
>>>   You have some sizable Finnish language speakers in Sweden:
>>>
>>> Swedish {O} sv 95.0% 99.0%
>>> Finnish {OR} fi 2.2%
>>>
>>>    So if the similar query is executed on Finnish language, and the results
>>> also show some "undue" proportion of visits from Sweden, then what you
>>> observed as anomaly is the that unique. We probably need many iterations of
>>> comparative outcomes and normalization of data (Sweden does have higher
>>> population).  Also, it might be handy to have some statistics on immigration
>>> or residence, it is EU. I will not be surprised that for example the  visits
>>> from Oxford to Wikipedia website have sizable German language requests.
>>>
>>>    I am still a bit bothered by the number "1" in the current dataset. It
>>> does not feel right since the numbers of 1.4% and 0.6% is a notable
>>> difference in this regard. Perhaps we need some high precision "universal
>>> percentage" number for each territory-language pair. It would be also great
>>> to do another set of aggregation: i.e. given a territory, which language
>>> versions of Wikipedia are accessed....
>>>
>>> Best,
>>> han-teng liao
>>>
>>> 2015-03-02 13:54 GMT+01:00 Finn Årup Nielsen <<a href="javascript:;" onclick="_e(event, &#39;cvml&#39;, &#39;fn@imm.dtu.dk&#39;)">fn@...>:
>>>>
>>>> Hi Oliver,
>>>>
>>>>
>>>> Interesting dataset! I am curious about why the Danish Wikipedia is so
>>>> highly acccessed from Sweden. Could it be an error, e.g., with Telia
>>>> IP-numbers?
>>>>
>>>> In Python:
>>>>
>>>>>>> import pandas as pd
>>>>>>> df =
>>>>>>> pd.read_csv('http://files.figshare.com/1923822/language_pageviews_per_country.tsv',
>>>>>>> sep='\t')
>>>>>>> df.ix[df.project == 'da.wikipedia.org', ['country',
>>>>>>> 'pageviews_percentage']].set_index('country') pageviews_percentage
>>>> country
>>>> Austria                            1
>>>> China                              1
>>>> Denmark                           61
>>>> Estonia                            1
>>>> France                             1
>>>> Germany                            2
>>>> Netherlands                        2
>>>> Norway                             1
>>>> Sweden                            18
>>>> United Kingdom                     3
>>>> United States                      3
>>>> Other                              5
>>>>
>>>>
>>>> MaxMind has some numbers on their own accuracy:
>>>>
>>>> https://www.maxmind.com/en/geoip2-city-database-accuracy
>>>>
>>>> For Denmark 85% is "Correctly Resolved", for Sweden only 68%. I wonder if
>>>> this really could bias the result so much.
>>>>
>>>> If the numbers are correct why would the Swedish read the Danish Wikipedia
>>>> so much? Bots? It does not apply the other way around: Only 2% of the
>>>> traffic to Swedish Wikipedia comes from Denmark.
>>>>
>>>>
>>>>
>>>> best regards
>>>> Finn
>>>>
>>>>
>>>>
>>>> On 02/25/2015 10:06 PM, Oliver Keyes wrote:
>>>>>
>>>>> Hey all!
>>>>>
>>>>> We've released a highly-aggregated dataset of readership data -
>>>>> specifically, data about where, geographically, traffic to each of our
>>>>> projects (and all of our projects) comes from. The data can be found
>>>>> at http://dx.doi.org/10.6084/m9.figshare.1317408 - additionally, I've
>>>>> put together an exploration tool for it at
>>>>> https://ironholds.shinyapps.io/WhereInTheWorldIsWikipedia/
>>>>>
>>>>> Hope it's useful to people!
>>>>>
>>>>
>>>>
>>>> --
>>>> Finn Årup Nielsen
>>>> http://people.compute.dtu.dk/faan/
>>>>
>>>>
>>>> _______________________________________________
>>>> Wiki-research-l mailing list
>>>> <a href="javascript:;" onclick="_e(event, &#39;cvml&#39;, &#39;Wiki-research-l@lists.wikimedia.org&#39;)">Wiki-research-l@...
>>>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>>
>>>
>>>
>>> _______________________________________________
>>> Wiki-research-l mailing list
>>> <a href="javascript:;" onclick="_e(event, &#39;cvml&#39;, &#39;Wiki-research-l@lists.wikimedia.org&#39;)">Wiki-research-l@...
>>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>>
>>
>>
>>
>> --
>> Oliver Keyes
>> Research Analyst
>> Wikimedia Foundation
>
>
>
> --
> Oliver Keyes
> Research Analyst
> Wikimedia Foundation
>
> _______________________________________________
> Wiki-research-l mailing list
> <a href="javascript:;" onclick="_e(event, &#39;cvml&#39;, &#39;Wiki-research-l@lists.wikimedia.org&#39;)">Wiki-research-l@...
> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l


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Re: [Release]

Cristian Consonni
In reply to this post by Dario Taraborelli-3
2015-03-04 8:44 GMT+01:00 Dario Taraborelli <[hidden email]>:
> yay, shiny! The map is a pretty compelling way to show how dominant traffic from the US is, even for very minor languages (say bi.wikipedia.org), I wonder how many requests from US-based bots/automata we’re still failing to detect.

Still, the question could be: are we fulfilling the mission?
(hint: probably not)

Cristian

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Re: [Release]

Oliver Keyes-4
That is the question, and I agree with your conclusion. I'm hoping to
do more research into this; getting buyin internally has been tough,
but I'm confident of making progress on that front over the next few
weeks and months.

On 4 March 2015 at 04:13, Cristian Consonni <[hidden email]> wrote:

> 2015-03-04 8:44 GMT+01:00 Dario Taraborelli <[hidden email]>:
>> yay, shiny! The map is a pretty compelling way to show how dominant traffic from the US is, even for very minor languages (say bi.wikipedia.org), I wonder how many requests from US-based bots/automata we’re still failing to detect.
>
> Still, the question could be: are we fulfilling the mission?
> (hint: probably not)
>
> Cristian
>
> _______________________________________________
> Wiki-research-l mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l



--
Oliver Keyes
Research Analyst
Wikimedia Foundation

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Re: [Release]

Pine W
I'm not sure how much influence I have, but I would be happy to make whispers in appropriate places to try to get more support, if that's helpful.

Perhaps you could show your work at the next Research and Data showcase? I for one would be interested in seeing a presentation.

Pine

This is an Encyclopedia
One gateway to the wide garden of knowledge, where lies
The deep rock of our past, in which we must delve
The well of our future,
The clear water we must leave untainted for those who come after us,
The fertile earth, in which truth may grow in bright places, tended by many hands,
And the broad fall of sunshine, warming our first steps toward knowing how much we do not know.
Catherine Munro



On Wed, Mar 4, 2015 at 1:25 AM, Oliver Keyes <[hidden email]> wrote:
That is the question, and I agree with your conclusion. I'm hoping to
do more research into this; getting buyin internally has been tough,
but I'm confident of making progress on that front over the next few
weeks and months.

On 4 March 2015 at 04:13, Cristian Consonni <[hidden email]> wrote:
> 2015-03-04 8:44 GMT+01:00 Dario Taraborelli <[hidden email]>:
>> yay, shiny! The map is a pretty compelling way to show how dominant traffic from the US is, even for very minor languages (say bi.wikipedia.org), I wonder how many requests from US-based bots/automata we’re still failing to detect.
>
> Still, the question could be: are we fulfilling the mission?
> (hint: probably not)
>
> Cristian
>
> _______________________________________________
> Wiki-research-l mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l



--
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Research Analyst
Wikimedia Foundation

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Re: [Release]

Oliver Keyes-4
On 4 March 2015 at 04:28, Pine W <[hidden email]> wrote:
> I'm not sure how much influence I have, but I would be happy to make
> whispers in appropriate places to try to get more support, if that's
> helpful.
>

I think I'm probably good, but thank you.

> Perhaps you could show your work at the next Research and Data showcase? I
> for one would be interested in seeing a presentation.

That's in 3 weeks; I'm not convinced that a piece of substantive,
useful research about global reach could be done in that time period
even if I could drop everything I currently have (which I can't). This
problem is too big and too important to be scheduled around meetings;
things should work the other way around.

Scott Hale and I have been working on a paper looking at global reach
and how it tracks with internet access growth, in the context of
editing, particularly looking at the mobile web. That, we should be
done with by then; presenting it could be highly useful (Scott? ;p)

>
> Pine
>
> This is an Encyclopedia
> One gateway to the wide garden of knowledge, where lies
> The deep rock of our past, in which we must delve
> The well of our future,
> The clear water we must leave untainted for those who come after us,
> The fertile earth, in which truth may grow in bright places, tended by many
> hands,
> And the broad fall of sunshine, warming our first steps toward knowing how
> much we do not know.
> —Catherine Munro
>
>
>
> On Wed, Mar 4, 2015 at 1:25 AM, Oliver Keyes <[hidden email]> wrote:
>>
>> That is the question, and I agree with your conclusion. I'm hoping to
>> do more research into this; getting buyin internally has been tough,
>> but I'm confident of making progress on that front over the next few
>> weeks and months.
>>
>> On 4 March 2015 at 04:13, Cristian Consonni <[hidden email]>
>> wrote:
>> > 2015-03-04 8:44 GMT+01:00 Dario Taraborelli
>> > <[hidden email]>:
>> >> yay, shiny! The map is a pretty compelling way to show how dominant
>> >> traffic from the US is, even for very minor languages (say
>> >> bi.wikipedia.org), I wonder how many requests from US-based bots/automata
>> >> we’re still failing to detect.
>> >
>> > Still, the question could be: are we fulfilling the mission?
>> > (hint: probably not)
>> >
>> > Cristian
>> >
>> > _______________________________________________
>> > Wiki-research-l mailing list
>> > [hidden email]
>> > https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>>
>>
>>
>> --
>> Oliver Keyes
>> Research Analyst
>> Wikimedia Foundation
>>
>> _______________________________________________
>> Wiki-research-l mailing list
>> [hidden email]
>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>
>
>
> _______________________________________________
> Wiki-research-l mailing list
> [hidden email]
> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
>



--
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Research Analyst
Wikimedia Foundation

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12