Centre for the Analysis of Social Media
"The ambition of CASM (and, it should be said, others too) – is to unlock all the insight that social media now holds. We see the key to be a fully-fledged new discipline: social media science. New methods need to be built by technologists and social scientists working intensively together to produce ethical, robust insight that can practically change minds and influence decisions.
Two examples of how we are doing this: attitudes and prediction.
Attitudes. Since its birth twenty years ago, Demos has tried to include people’s voices in policy-making, and sought new ways to find them. Demos researchers have gone to hairdressers, built an urban beach, carried around a Domesday book, all in the search for what people really think.
Brits now spend 62 million hours a day on social media: that’s an hour a day for every adult and child in the UK. They do so on a number of platforms of course, but one of the fastest growing and most exciting is Twitter. Its 200 million active users worldwide post over 500 million ‘micro-blogs’, or tweets, a day. Tweets are short, snappy messages or updates of no more than 140 characters in length.
People turn to it to tweet about things that they have otherwise heard about in their daily lives. Major events – whether controversies, disasters or court cases – are now accompanied by a surging cloud of reaction on Twitter, a kaleidoscopic deluge of digital commentary, arguments, discussions, questions and answers. These ‘twitcidents’ are becoming a routine aftermath to events, a way that society reacts to and annotates the events it experiences. Indeed, they are becoming an important dimension of the events themselves.
Untangling these clouds of reaction is potentially very valuable. Doing so gives us a real-time picture of a society as it argues with itself about those experiences and points of controversy people find most important. Alongside surveys and polls, we can now have a real-time window into what people care and are talking about.
For over a year, we have been building technology to make sense of this deluge and develop an understanding of people’s views on the important events that they talk about. The fruits of this work – Vox Digitas: Understanding digital voices – will be published early this year.
The technology works using ‘natural language processing’ – a subfield of artificial intelligence and linguistics – through which algorithms are taught to automatically recognise whether tweets are relevant to one of the issues, whether they contain an attitude and (most ambitiously) what this attitude is. Each of these taught algorithms – 63 in total – act like sluice gates, controlling the flow of some tweets into deeper levels of the architecture, and siphoning off the rest into a waste pool.
Having this window could bring people and politicians closer together. Take a fairly routine and usual occurrence – a European Commission Summit. During one such summit, on the 14 March 2013, tweets mentioning Jose Manuel Barroso (the President of the Commission) surged to more than ten times its average.
Prediction. Once you understand people’s attitudes on social media, you can begin to predict how they act. To see if we could, we tried to predict the outcome of The X Factor (series 8) every week, solely based on what we could measure from social media. It’s a perfect experiment: every week, millions of people talk about which contestants they like and dislike, who they thought performed well or badly, and then they vote on it. Tweets about each of the contestants peaks as they take the stage." (http://quarterly.demos.co.uk/article/the-promise-of-social-media/)