On Fri, Nov 13, 2015 at 01:45:57PM -0800, Erik Bernhardson wrote: > Have you put any thought into normalizing page view data?
I haven't studied it, but I think you've got a good start: normalizing them by the # of pageviews of the community. So if someone types an entire French phrase into the English wikipedia, and you wanted to show both En and Fr options in the autocomplete, a simple normalization would be a good start for having something to sort by. Ditto for search. Your next question, about weighting over time, is really a question about how much data you have. It's nice to be able to push up current events, so that someone searching for Paris today could see (alas) the brand new article about today's attacks. But it's the amount of pageview data that really dictates how well you can do that. For the English wikipedia, there are so many pageviews that you probably have enough data over 24 hours to produce good, not-noisy counts. And for less than 24 hours, you'll probably end up magnifying Europe's favorites as America wakes up, and America's favorites as Asia wakes up. Probably not a good thing! For a less-used wiki, only 24 hours might produce pretty sparse and noisy counts. So you will need to look back farther, which reduces your ability to react to current events. You'd like to experiment with exponential decay, you can look at the statistics to try to figure out if you're just magnifying noise. Or Europe's preferences become popular when Americans wake up. (And if you're really interested in geography, you could divide the data up so that Europe, America, ANZ, Asia, etc have separate autocompletes... if you have enough pageview data.) -- greg _______________________________________________ Analytics mailing list [email protected] https://lists.wikimedia.org/mailman/listinfo/analytics
