  Understanding how various external campaigns or events affect readership on
Wikipedia is important to efforts aimed at improving awareness and access to
its content. In this paper, we consider how to build time-series models aimed
at predicting page views on Wikipedia with the goal of detecting whether there
are significant changes to the existing trends. We test these models on two
different events: a video campaign aimed at increasing awareness of Hindi
Wikipedia in India and the page preview feature roll-out---a means of accessing
Wikipedia content without actually visiting the pages---on English and German
Wikipedia. Our models effectively estimate the impact of page preview roll-out,
but do not detect a significant change following the video campaign in India.
We also discuss the utility of other geographies or language editions for
predicting page views from a given area on a given language edition.
