Futurology, futurism, future studies. All terms for the same thing - predicting what's coming next. Not in a mysterious way, reading tea leaves or gazing in to a crystal balls, but in a much more practical sense.
Using a probability model and basing any initial assumptions on evidence rather than conjecture, you can easily get a good idea of whether or not something is likely to happen, or, at least, where you should be focusing your efforts.
The first and most important thing to remember when you're looking forwards is to Slow Down. There are no overnight successes. Things can grow quickly, but they often don't. Interesting changes spread in a measurable, observable, predictable pattern. In the past it was possible to actually plot the way an innovation moved through the world. Today, with communications happening instantaneously and social network moving ideas through social groups far more rapidly than was possible in the past it's more difficult to plot a geographic path for a new technology, but at the same time it's become much easier to track which groups spread new ideas. A simple keyword search plotted on a timeline can demonstrate how a technology has grown out from internet hubs (eg Hacker News, Reddit, Digg).
The second thing to note is that traditional media reacts far slower than even the least technologically minded futurist. For a media outlet being seen to bring their audience content that is accurate is considerably more important than being them content before their competition. Generally, the media follows the specialist press - in the case of cutting edge technology and ideas, that specialist press is user generated content shared on hub sites.
Don't start from now (Back-view mirror analysis)
All of this is leading to the idea that the primary barrier to an accurate forecast of what might happen in the future is the biases and filters that we apply to our every day thinking. By looking at the world with a narrow point of view based on your own assumptions and experience you inherently lose perspective on what might by the next big idea. This can be as simple and straight-forward as conflating your own bias toward liking a technology (eg "I think wearables will be huge because I've had a great experience with mine") to misreading data because you assume more about a trend than the data tells you (eg "Despite FourSquare's active user count falling for the past four quarters I believe they'll turn that around").