Tallying-up the ‘Inglorious’ Reception: Someday is Today…
Inglorious Basterds won at the box office and dominated Twitter conversations this weekend. In addition to grossing nearly $37 million, Quentin Tarantino’s World War II-themed saga has been afixed to Twitter’s trending topics list since Friday.
Word of mouth referrals are nothing new to the movie business. But, as Simon Dumenco (@simondumenco) points out in Friday’s AdAge, Twitter brings an element of speed and reach that is entirely new – and, he argues – potentially threatening to Hollywood. To better understand Twitter content about new releases, Dumenco speculates that “…someday soon, someone’s going to get a PhD in the statistical parsing of Twitter data streams…”
Well, Mr. Dumenco, let us humbly assert that someday is today. Crimson Hexagon turned its algorithm (created by a Harvard PhD professor) loose on this weekend’s Twitter conversation about Inglorious Basterds.
We performed the PhD magic on a sample of over 4500 Tweets from this weekend and found that:
- 40% of all Tweets on Inglorious praised the film, with an additional 9% hailing it as classic Tarantino
- Anticipation was still high, with almost a quarter of all Twitters talking about the movie still eager to see it
- The critics? Quiet so far, with only 8% of Tweets expressing disappointment at Tarantino or the film
- Finally, 14% want to know others’ opinions about the movie: Glad we could help
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What is the source of your PhD magic you used to analyse the Twitter reaction? I'm intrigued to learn more about the process.
The only problem with doing stats (of any type, but especially based on counting commonly used phrases) is that many many Twitter spammers usually have tons of accounts where they will tweet the exact same message to all of them…
Do a search for a trending keyword and watch the results for a while (either using twitter's own search function or something like twitterfall) and you'll begin to see the EXACT same wording appear again and again in tweets from different 'people'. Further investigation will usually reveal those tweets are coming from 'sock puppet' or fake accounts.
NickAtFlare,
Our PHD magic is our propietary IP, what we call our “secret sauce”. The algorithm was developed at Harvards Institute for Quantative Social Science by one of our founders, Dr Gary King. Here is a link to the whitepaper that described the algorithm in detail. Email me at mog@crimsonhexagon.com if you'd like more details about the process.
correction – mpg@crimsonhexagon.com
Fox Krieger,
You are absolutely correct: keyword matching is an ineffective method for analyzing social media content. Our technology does not use keywords for the analysis. It uses keywords to collect the corpus of data to be analyzed but then leverages our statistical algorithm to analyze the data, recognizing and quantiying opinions and themes. We can also use this algorithm to filter out spam, again recognizing patterns and themes common across the spam content.