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30 March 2013 | NewScientist | 19

have looked at how people’s facial expressions change as they receive treatment for depression.

In work also to be presented at the Shanghai conference, Cohn’s team used four cameras to track the faces of 34 people diagnosed

with depression as they answered questions about their condition. This was used to train a machine learning system which looked at 66 different parts of the face to spot movements that betrayed certain emotions. The system can therefore also reveal any subtle changes in those movements as the severity of a person’s depression changes.

The team discovered that even though people with depression might smile, they inadvertently use facial muscles as “smile controls” to restrain their expressions.

Perhaps surprisingly, they also showed fewer expressions associated with sadness, something Cohn puts down to the “social risk hypothesis” – the idea

that people with depression try to minimise engaging with others.

There has always been interest in what the face can tell us about depression, but measuring people’s expressions has been a challenge, Cohn says. “What’s really changed is that the technology is getting sufficiently advanced that it can now begin to be used.” But we are just beginning on this road, he says.

Exactly how far along we are will soon be put to the test. In October, researchers from around the world will take part in a contest to find the most accurate system for diagnosing depression, to be held at the ACM Multimedia conference in Barcelona, Spain. Challengers will be given a video database of interviews, some involving clinically depressed people. Contestants will train their algorithms on these and will be scored on how good their system is at picking out depressed people from a group. Organiser Michel Valstar of the University of Nottingham, UK, says the challenge is a “unique opportunity for researchers to come together and try and contribute to the area of mental health in a possibly groundbreaking new way.” n

“ Screening does not look at non-verbal behaviour – this is where our technology can be put to work”

People spill their guts on social media, revealings things that they wouldn’t necessarily share face to face. So Munmun De Choudhury and colleagues at Microsoft Research in Redmond, Washington, mined Twitter to see whether it can be used to gauge levels of depression in society.

The team analysed the language of 69,000 tweets by 489 people who had previously been diagnosed with depression. They also tracked how many Twitter followers each user had and how many they followed, and the timing of users’ tweets over a three-month period.

Users with fewer retweets and replies and those who tweeted more at night were slightly more likely to

be depressed, the team found. The same was true of those whose tweets featured the word “I” more often than average.

An algorithm trained on this data was able to predict in 73 per cent of cases whether a Twitter user was depressed or not. The system was then applied to a large number of random Twitter posts to gauge depression levels in the “unhappiest cities in America” – 20 cities picked out by an earlier study that looked at antidepressant use. The Twitter depression index closely correlated with the antidepressant figures. The team will present the results at the WebSci conference in Paris, France, in May.

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tweets reveal if we are feeling blue

Ethical drones hunt the hunters

Animal welfare groups have a new weapon: drones. ShadowView, a non-profit organisation based in the UK and the Netherlands, is hiring out a variety of drones and an expert pilot to people it agrees with politically. This week, ShadowView agreed to supply drone surveillance to the British anti-fox-hunting group, the League Against Cruel Sports, which wants to find out whether the UK’s fox-hunting ban is being flouted. We know there might be trouble, says ShadowView co-founder Laurens de Groot. “Under some circumstances there may be a risk that our UAVs are shot at by poachers and wildlife criminals,” she says.

3D holograms look good from any angleMost glasses-free 3D only works if you view it from a certain angle, but David Fattal and a team at Hewlett-Packard labs have created a prototype display that can be viewed across 180 degrees and from a range of perspectives. The edges of the screen emit light from LEDs and diffract it into precise bands that correspond to different views of the subject. Fattal says you just need to move your head to see a 3D image from different angles. “You would see something like in Star Wars, with the famous hologram of Princess Leia,” he says.

Keep calm and tweet onIt can be hard to sift through Twitter at the best of times, but when you want information during a disaster or national uprising, it’s tougher. Shamanth Kumar of Arizona State University in Tempe came up with an approach that helps find tweeters who are generating high-quality information. He analysed 12.9 million tweets during the Arab Spring in 2011 to develop an automatic process that pinpoints tweeters who are closest to the incidents they’re describing, based on geotagged tweets. He also looked for those who were tweeting about topics that were of most interest to others, by looking at keywords. The approach could provide instant access to useful information in a future crisis.

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