Dave, thanks for sharing this, the referral data is particularly fascinating. I mentioned during the quarterly review that I'd love to get a better sense of (1) the proportion of requests in the mobile request logs lacking a referral, (2) the possible causes of this gap and (3) to what extent these missing entries introduce a bias in the referral ranking. The 3rd most popular query (according to your dumps) is ビッグダディ (japanese for "Big Daddy"), which presumably refers to this guy: http://metro.co.uk/2013/03/20/giant-japanese-spider-crab-big-daddy-arrives-… What's interesting is that there's no such entry on the japanese Wikipedia and I am baffled that people may have landed on the website via a search engine query for a non-existing article. Do you have an explanation for this or am I misinterpreting what you mean by search query? Dario On Apr 24, 2013, at 8:40 PM, David Schoonover <dsc(a)wikimedia.org> wrote: Hiya all, As promised earlier today in the Analytics weekly showcase, I've got a few interesting bits of data to share from playing with the new Mobile Site Sessions dataset. # Visits to Mobile Site, 4/21/2013 - Total Visits: 51,624,103 - Unique Visitors: 37,736,120 - Total Pageviews: 104,972,033 - Avg Pageviews per Session: 2.0334 - Max Pageviews in one Session: 141,882 ## Standard Site - Visits: 51,603,221 - Unique Visitors: 37,723,188 - Pageviews: 104,910,382 - Avg Pageviews per Session: 2.033 ## Alpha Site - Visits: 986 - Unique Visitors: 822 - Pageviews: 7,087 - Avg Pageviews per Session: 7.188 ## Beta Site - Visits: 19,896 - Unique Visitors: 16,235 - Pageviews: 54,564 - Avg Pageviews per Session: 2.742 ## Notes - A session (or "visit") is defined as all activity with less than 30 minutes between each hit. Intuitively speaking, a session ends when the user hasn't done anything in 30m. - As we do not set visitor_id cookies for all users, the "unique visitors" metric was calculated using hash(ip_address + users_agent) as visitor_id. - This job looked at all requests to the mobile site on 4/21/2013, which is 75.17 GB of request logs. - The job took ~17 minutes to process the day into 15.3 GB of sessions. - The summary above took maybe 10 minutes to set up/write in Hive, and the job took maybe 7 minutes. In addition to that summary, I ran a few jobs on the entry_referer field -- the URL that referred the user to us when the session started. Obvious caveats: this is only one day of data, and it's only the mobile site. Draw conclusions with care. First, I pulled out the top referring domains. It's mostly as you'd expect -- search engines -- though you'll also note that several Wikipedia mobile sites show up. My working hypothesis is that people don't tend to close tabs on smartphones; when they later come back, it is often to an open Wikipedia tab: clicking a link or perform a search means the referrer is still us. Since -- as expected -- so much of the data pertained to search engines, I also calculated the top search queries and top keywords that sent people to us. (For keywords, I've filtered out common "stop words": de, of, in, is, la, and, el, es, to, en, di, los, le, da, se, las, les, il, du, a, i, o, y, e.) In both, you see the predictable: lots of searches for porn, for "facebook", for "wiki", etc. But you also see a few things that surprised me: - Tons of Japanese. Japan is the most mobile-enabled country in the world so I guess we should have expected to see many searches in Japanese show up in the top queries. I've left them URL-encoded in the results -- you'll see them as weird lines with % in them. - Apparently people search for movies and TV so they can spoil their fun by reading about them on Wikipedia. Both of "movies" and "film" show up in the top keywords; Iron Man 1, 2, AND 3 all show up in the top search queries. I didn't expect this was a major use-case, but -- wikigroaning aside -- it's an interesting fact. I'm sure we're only scratching the surface here. This is an exciting dataset, and I'm sure there's lots more to learn! The full results: - Top Referring Entry Domains: http://stats.wikimedia.org/kraken-public/webrequest/mobile/views/sessions/m… - Top Referring Entry Search Queries: http://stats.wikimedia.org/kraken-public/webrequest/mobile/views/sessions/m… - Top Referring Entry Search Keywords: http://stats.wikimedia.org/kraken-public/webrequest/mobile/views/sessions/m… Questions are welcome! -- David Schoonover dsc(a)wikimedia.org _______________________________________________ Analytics mailing list Analytics(a)lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics

On Wed, Apr 24, 2013 at 9:17 PM, Dario Taraborelli <dtaraborelli(a)wikimedia.org> wrote: Dave, thanks for sharing this, the referral data is particularly fascinating. I mentioned during the quarterly review that I'd love to get a better sense of (1) the proportion of requests in the mobile request logs lacking a referral, (2) the possible causes of this gap and (3) to what extent these missing entries introduce a bias in the referral ranking. The 3rd most popular query (according to your dumps) is ビッグダディ (japanese for "Big Daddy"), which presumably refers to this guy: http://metro.co.uk/2013/03/20/giant-japanese-spider-crab-big-daddy-arrives-… What's interesting is that there's no such entry on the japanese Wikipedia and I am baffled that people may have landed on the website via a search engine query for a non-existing article. Do you have an explanation for this or am I misinterpreting what you mean by search query? There is an article on this on ja.wiki :) It may have been renamed since then, but it's still the 2nd Google hit for ビッグダディ: http://ja.wikipedia.org/wiki/%E7%97%9B%E5%BF%AB!%E3%83%93%E3%83%83%E3%82%B0… Dario On Apr 24, 2013, at 8:40 PM, David Schoonover <dsc(a)wikimedia.org> wrote: -- Maryana Pinchuk Associate Product Manager, Wikimedia Foundation wikimediafoundation.org

Maryana, that Wikipedia article is about a TV series which is being broadcasted since 2006, but I don't think it's very popular. On the other hand, nobody seems to mention the crab Big Daddy in the Japanese internet culture. *--* *Haitham Shammaa* *Contribution Research Manager* *Wikimedia Foundation* *Imagine a world in which every single human being can freely share in the sum of all knowledge. * *Click the "edit" button now, and help us make it a reality!* On Thu, Apr 25, 2013 at 10:19 AM, Maryana Pinchuk <mpinchuk(a)wikimedia.org>wrote;wrote: _______________________________________________ Analytics mailing list Analytics(a)lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics