Thank you Kerry for the comment.
** ** ** ** **
I think the idea that Wikipedia activity (or other social media activity)
can be used as some kind of predictor of public popularity is probably
relatively sound. If something is attracting a lot of public interest, then
one might expect that a certain proportion of interested people to be
editors of Wikipedia (or users of Twitter, etc) leading to a corresponding
uptick in activity in those spaces. Of course the editors of Wikipedia
aren’t a “typical” demographic sample, so probably things that appeal more
to the Wikipedia demographics are more likely to manifest as Wikipedia
activity, but for very popular movies the target market is somewhat similar
to the Wikipedia editor demographic so it probably correlates OK. However,
that might account for the lower ability to predict the box office for less
popular movies – maybe the audiences for those movies aren’t statistically
as likely to be Wikipedia editors?
That is one possibility, and the other would be existence of a threshold.
We see that for the less successful movies, the prediction usually
underestimates the box office revenue, suggesting that the movies should be
more popular than a threshold to evoke enough Wikipedia activity
proportional to their public popularity.
****
But I am less sure whether there is any practical use for this finding in
relation to movies. Where are the Wikipedia editors getting their advance
movie information from? Presumably from the marketing activity of the movie
itself. Which movies get the big marketing budget? The expected
blockbusters. It’s something of a self-fulfilling prophecy I suspect.
I'm not actually sure about this. I guess there are many professional movie
followers among Wikipedians who gather information much earlier than the
start of advertisement campaigns from different, more specialized channels.
That is basically the main difference and strength compare to the Twitter
model, where public audience start to tweet about the movie, most likely
evoked by marketing stimuli and only very close to release time.
****
From the point of view of the movie makers, there isn’t much they can
learn from the level of WP activity because from their perspective their
money has largely been spent long ago on making the movie. They need to be
able to predict its success a couple of years earlier, long before there
will be a single edit on WP or any tweeting. I guess my point is that the
ability to predict something is really only useful if the prediction can be
made in advance of making an important decision. A really exciting result
would be the ability to predict stock price movements from WP editing
behaviour! We could use the profits from that to fund the journal, which
could have a policy of publishing only unaffiliated authors as we would all
be retired on our stock market riches! J
Sure, but please note that we are not claiming at fortune-telling! We are
data people, and can not have any result before any data is generated.
There are movie consultant companies who have models to predict the movie
success at the "idea level". But nobody knows about their methods and
performance. The other thing is that we should distinguish between movie
makers and movie distributors. As far as I know, it is very important for
the movie distributor companies to have an estimation of movie success even
as late as the first weekend AFTER release. Our model gives good results
already one month BEFORE release.
Thank you again for the comments, and I would assure you that once I find a
really good money predictor, I would defiantly retire myself immediately
and leave academy toward a real life! ;-)
bests,
Taha
** **
Kerry ****
** **
------------------------------
*From:* wiki-research-l-bounces(a)lists.wikimedia.org [mailto:
wiki-research-l-bounces(a)lists.wikimedia.org] *On Behalf Of *Taha Yasseri
*Sent:* Wednesday, 7 November 2012 10:34 PM
*To:* Research into Wikimedia content and communities
*Subject:* [Wiki-research-l] Wikipedia Used to Predict Movie Box
OfficeRevenues****
** **
Hello Everybody,
In the temporary silence after hot election and Wikipedia research Journal
debates and discussions (I hope at least the second one continues), I would
like to use the opportunity to introduce our new manuscript,
titled "Early Prediction of Movie Box Office Success based on Wikipedia
Activity Big Data" and available at
http://arxiv.org/abs/1211.0970.
There is also a rather fair review of this work at
http://www.technologyreview.com/view/507076/now-wikipedia-used-to-predict-m…
.
As always, comments, critics, encouragements, etc, are most welcome (if
you are shy, please write me off-list).
Bests,
Taha Yasseri
Dr. Taha Yasseri.
---------------------------------------------
www.phy.bme.hu/~yasseri <http://www.phy.bme.hu/%7Eyasseri>
Department of Theoretical Physics
****Institute** of **Physics****
****Budapest** **University**** of Technology and Economics
Budafoki út 8.
H-1111 ****Budapest**, **Hungary****
tel: +36 1 463 4110
fax: +36 1 463 3567
---------------------------------------------****
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