The Crunch: Back from a Summer Break with a Bunch of Links
After a fairly extended Summer break, there's quite a lot of catch-up to do. I have a few posts already in the pipeline, including the second part of my series on Medium Data (the second article has grown big enough that it might turn into a mini-series of its own). I also have a lot more movie analytics work coming down the pike. First though, I have a big list of articles and web sites I've been meaning to share.
Catherine Rampell at the Economix blog in the New York Times has had a series of articles on return on investment on films of different types: Hollywood's Biggest Bang for Its Buck, A Rating With a High Return: NC-17, and Reviewing the Movies: Audiences vs. Critics. The articles make nice use of data from OpusData, and have some interesting results. They also highlight some of the challenges in doing this kind of analysis (the high rate of return for NC-17 films, for example, is largely down to a small sample size and low budgets for such films).
Film Business Asia has an interesting article on the evolution of China's film business, which I think has implications for the global business as a whole. Todd Cunningham picked up on this theme in The Wrap, and I'll have more to say on it in a future article.
Kickstarter has been in the news pretty constantly in the film business over the past couple of years, and Rob Trump's article in the New York Times, Why Would You Ever Give Money Through Kickstarter provides a good perspective on why people donate that is food for thought for anyone thinking of setting up a Kickstarter project. (Link via the NYU Cinema Research Institute blog.)
On film financing more broadly, David Christopher Loya wrote an interesting piece, The 12 elements that define the perfect independent motion picture investment opportunity..., which provides a useful (and challenging!) checklist of goals for an independent film-maker. I would quibble with a few details, but I think its a good starting point for someone thinking about how to make a successful film.
The Summer also brought its usual share of articles on systems for predicting film box office. The New York Times had Solving Equation of a Hit Film Script, With Data. Google published a paper called Quantifying Movie Magic with Google Search (which was widely, and somewhat misleadingly, reported as being "94% accurate"). I also came across Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data, which it turns out was originally published in November last year but recently got a new round of attention. I'll be talking about all three approaches in upcoming articles. Without wanting to give too much away, let's just say at least one of them suffers from the kind of problem I described in my Medium Data piece.
On a lighter note, Box Office Champs looks like a fun box office prediction game. Their next round starts on September 1, so now's a good time to check it out.
My favorite find of the Summer though is iknow.io, which combines our data with a very nice front end to create some really cool insights into the film business. See, for example, New or Old James Bonds?? Which ones are more successful? and Actors that are great directors. They have a section for Congress too, and plan to add other data-rich areas in the future.
If you see any articles, web sites or apps that you think are worth sharing, drop me a line and I'll include them in a future link round-up.
Date posted: 2013-08-24