This app is really cool. I wonder if beside future predictions, it
could be modified to support another use case: Assessing the impact of
past events and software changes on our pageviews.
As many of us are aware, the Wikimedia movement has been struggling
for a long time to understand the effects of our work (and of outside
events) on our readership. And while WMF engineering teams are getting
better about doing, say, A/B tests, it's often not possible to provide
a controlled environment for such experiments.
There's an established statistical technique aimed at such situations,
called "Intervention Analysis", see e.g. [1]. It requires modeling the
time series (here: monthly pageviews) with an ARIMA model just like it
has been done in the app. One then basically does a backdated forecast
from the time of the intervention, and uses the difference between
that forecast and the actual development to model the effect of the
intervention. I've been wondering recently if this has ever been used
for Wikipedia pageviews; yesterday while attending Morten's research
showcase talk about their "misalignment" paper I noticed that that
paper has indeed been applying it (to views of individual articles,
where it may be easier to isolate effects).[2] Is anyone aware of
other examples?
Would it be possible to modify the app to support such backdated
forecasts, as a first step, and also for calculating their difference
to the actual development?
[1]
https://onlinecourses.science.psu.edu/stat510/node/76
[2]
http://www-users.cs.umn.edu/~morten/publications/icwsm2015-popularity-quali…
(p.8)
On Tue, Sep 15, 2015 at 5:28 PM, Dario Taraborelli
<dtaraborelli(a)wikimedia.org> wrote:
An updated version of a pageview forecasting application written by Ellery (Research
& Data team) has just been released:
https://ewulczyn.shinyapps.io/pageview_forecasting
https://twitter.com/WikiResearch/status/643942154549592064
The data is refreshed monthly and it includes breakdowns by country and platform.
Dario
Dario Taraborelli Head of Research, Wikimedia Foundation
wikimediafoundation.org •
nitens.org • @readermeter
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