At the end of last year, we told you about a new project by YouTube called the “YouTube Slam“. The project pits two videos against one another in a “hot or not” style competition. The site lets you watch two videos and decide which one is better, or in the case of comedy, funnier.

That project alone wasn’t scientific or geeky enough for Google, so the company decided to delve deeper into what makes videos funnier and how the company can detect that you enjoyed it more than any other old video.

One place the company decided to go was within the comments on all of the videos that participated in the YouTube Slam. By looking at the content of the comments, it found that many people would leave a quick “hahaha” or “LOL”. Comments that display the humor you found in the video can help the company rank the popularity of a video in a slightly different way. This data on top of what it was already collecting with your votes, might just tell us which videos are actually funnier.

Surprisingly, the company found that the more o’s you put in your LOL comments on the video, the funnier you thought it was. It was a pattern it picked up time and time again, so Google has decided to build it in to an algorithm which ranks the funniest videos:

Next we needed an algorithm to rank these funny videos by comedic potential, e.g. is “Charlie bit my finger” funnier than “David after dentist”? Raw viewcount on its own is insufficient as a ranking metric since it is biased by video age and exposure. We noticed that viewers emphasize their reaction to funny videos in several ways: e.g. capitalization (LOL), elongation (loooooool), repetition (lolololol), exclamation (lolllll!!!!!), and combinations thereof. If a user uses an “loooooool” vs an “loool”, does it mean they were more amused? We designed features to quantify the degree of emphasis on words associated with amusement in viewer comments. We then trained a passive-aggressive ranking algorithm using human-annotated pairwise ground truth and a combination of text and audiovisual features. Similar to Music Slam, we used this ranker to populate candidates for human voting for our Comedy Slam.

How scientific is it exactly? Your guess is as good as mine, but the minds at Google always come up with a way to quantify huge amounts of data so the “LOLSignal” sounds just as good as any other.

If you haven’t participated in the YouTube Slam project yet, it’s a fun way to kill boredom for hours on end.

Tweets from across the USA have been used by researchers to gain an understanding of how Americans see their health.

The BBC reports that two computer scientists from  John Hopkins University, Baltimore developed a special search filter to identify 1.5 million health-related tweets published between May 2009 and October 2010. The duo then analysed these tweets to find that Twitter is a useful source of information about public attitudes to health.

Among the study’s findings were people taking antibiotics as a cure for the flu – something that doesn’t work and may actually stop our bodies from reacting to the drugs when we really need them to. Using geographic information from tweets and user profiles, researchers mapped out health trends across the United States. This revealed, for example, that allergy season started earlier in warmer states than in the  Midwest and Northeast.

The researchers did find that their study was limited by a lack of consistency in the information. Someone may tweet once about having a cold but never mention it again. This demonstrates the limitations of using any kind of online social data for this kind of study – people will only share what they want to, when they want to.

Still, it shows the potential of Twitter as a large-scale research tool. With the US Library of Congress storing an official archive of public tweets for academic study, approaching this data in the right way could reveal all sorts of fascinating insights into how we live and what we think. Google already operates a site called Flu Trends, which uses search data to map out how flu is affecting different parts of the world.