But this can also be overwhelming, as an EU-funded research project has been finding out. Social Sensor, a three-year project partly funded by the European Community's Seventh Framework Programme, has been underway for around a year now, in which time research has been carried out into how journalists across Europe currently filter the social web - and the difficulties they face doing so.
The research actually covers two use cases, news and infotainment. In the news case, for example, the research will help inform the creation of a prototype for an application designed for journalists searching social networks for news.
We spoke to senior research partner for SocialSensor at City University London Nic Newman, who up until 2010 was the BBC's future media controller for journalism, about what the research stage has found out, and what this has flagged up as the key components for any future solution.
He outlined some of the questions journalists were asked as part of the research, such as what tools they are currently using to filter social media and what they feel is missing.They talk about being overwhelmed by the amount of social media stuff coming at them. They talked about it being transformative, surprising, the speed, but the overwhelming thing, confusing thing, was a very strong messageNic Newman, senior research partner, SocialSensor
"They talk about being overwhelmed by the amount of social media stuff coming at them," Newman told Journalism.co.uk. "They talked about it being transformative, surprising, the speed, but the overwhelming thing, confusing thing, was a very strong message."
He added there was a "sense of all this stuff coming at you and it's very very hard to filter and find what you want really quickly because of the pressures of real-time".
Having identified these needs the research project has now identified has three key goals, to develop a tool the spots trends, that can pinpoint key influencers and can offer verification.
The research also identified a certain hierarchy to these issues, in terms of importance to the journalists asked. The most important was the ability to be alerted to breaking events, either generally or within a certain niche or patch, followed by the need for verification, then knowing you're following the key influencers and fourthly the ability to track trends.
As Newman stessed though, "there wasn't actually that much difference between those top four things in terms of overall scores, so what people also want is a tool that does that, all of those things and is sufficiently versatile to allow people to configure things and to give them the sort of fine-grain control that existing tools don't allow them to have."
Other key factors for any future product in this area is for it to operate across social networks, and offer journalists "more fine-grain control" to give social streams more order.
So over the next couple of years this research will feed into the building of the prototype. At the end of the project there will be a period of evaluation at which point the prototype application will either become a commercial product, or parts may feed into other commercial products. Similarly parts of the research itself may "be used in other ways going forward", Newman explained. Either way it seems the project is likely to help in some way with the development of improved tools to help journalists filter the web.
Research partners on the project include City University London, who Newman is working closely with, as well as Yahoo, IBM and Deutsche Welle.
The structure of the project means that each research partner is now in charge of a certain element of the infrastructure, with the Greek partner, for example, managing the trending mechanisms within the prototype, while City University and Deutsche Welle are looking at the design of the prototype, what features it should include and how they can be brought together.
There is more information on SocialSensor on the project website.
Free daily newsletter
- Tip: Advice for incorporating data skills into a journalism curriculum
- Tool for journalists: FOIA Predictor, for estimating the success rate of a Freedom of Information request in the US
- How to use data.world to collaborate on projects and datasets
- Tip: Here's how podcasts can be used to teach other journalism skills
- Kaleida launches The Attention Index, an open-source algorithm to measure the impact of stories