Few people are truly comfortable with the idea of corporations sifting through their 'likes', internet outbursts and browsing history, despite the wealth of personal data being divulged on a daily basis.
But making use of this ‘human data' often gives companies an insight into their customers and the ability to tailor services and apps to a specific audience.
Using this big data is becoming big business, regardless of the privacy concerns surrounding social networks.
Social analytics firm DataSift is doing particularly well out of this trend and is enjoying triple figure growth, according to chief executive Nick Halstead (pictured).
"Our growth has been phenomenal. In 2013 it was 400 percent. Last year was still in the hundreds of percent and will be this year if it continues as it is," he said in an interview with V3.
As part of this growth, Datasift recently announced a deal with Facebook, which will see the firm deploy its analytics platform behind the Facebook's firewall and gather data on Facebook's billion plus users.
Halstead explained this data is offered through a subscription service to DataSift's customers, which include companies such as Oracle and Hootsuite. Specific data is used in the development of marketing applications that companies can then deliver to end users.
"Social networks haven't been giving the depth of information about demographics to make better decisions," he said. "You could use demographics to target but you couldn't use demographics to research."
Halstead went on to explain how DataSift harvests relevant social data for a specific use, such as the way in which a particular audience demographic interacts with a topic.
Data from many social media platforms and networks is categorised as public, but information extracted from Facebook's users is not. Using this information has the potential risk of being seen as a breach of privacy, unless it is handled correctly.
"Before Facebook, all of the data [used by DataSift] was public data and what we class as ‘raw data'. Facebook has slightly changed that model in that it's now a very privacy-safe model where you only get aggregate data," said Halstead.
He explained that DataSift worked with Facebook for nine months to ensure that the data being harvested, analysed and provided to customers was stripped of identifying qualities to leave a mass of statistics rather than a catalogue of personal information.
This approach means DataSift removes the identity of Facebook users, and ensures that only anonymised data leaves Facebook's servers. Furthermore, detailed data used by DataSift to create the initial analysis is deleted within 30 days.
Halstead pointed out that anonymising data removes the opportunity to compromise people's privacy and is a way to pre-empt any privacy concerns that might surface as the use of social network data rises.
"I do think there has been this shift in people's expectations around privacy, and I think with [social analytics] technology we've been at the forefront of bringing it to market before people expected it or it was needed," he said.
Halstead added that this privacy-focused approach was enshrined in DataSift's operation long before its partnership with Facebook.
"We developed technologies four years ago to deal with all the terms of service of Twitter many years before anyone else was doing it, and even today we're the only company doing it properly," he said.
"If you delete a tweet two days later after you sent it, our historic store of that tweet is gone and we delete it ourselves and send a message to our 1,000 customers telling them to delete it from their databases."
Sifting for digital gold
Stripping out the identifying elements of data meant that DataSift needed to find a way to uncover value in mountains of anonymised aggregate data.
DataSift created an application programming interface called Pylon to make use of Facebook's 'firehose' of data. This allows social data to be contrasted against simple parameters that can reveal useful information for marketers.
For example, a social media post on a defined topic can be measured against the number of interactions it received.
This approach yields statistical data which can show the impact of a certain topic in a demographic, or how much a brand is being talked about, and by whom, all without needing any personal data.
Halstead reaffirmed DataSift's ambition to push beyond social network data analysis into the enterprise arena, and to make use of human data found in internal corporate blogs, forums and social networks such as Yammer and Hootsuite.
"We are very much taking DataSift beyond just social and applying it to the enterprise in the future," he said.
"Although social is our starting point, the technologies we have are agnostic to the input data. And later in the year we are going to be making announcements about how we bring that platform to other data."
Halstead added that working with internal corporate human data avoids some of the privacy concerns encountered with social network data.
"The joy, in some ways, with corporates working with this data is they have their own policies on how data is allowed to be used," he said.
While DataSift teams up with Facebook to harness the potential of human data, other technology companies are also joining forces with social networks. IBM recently teamed up with Twitter to drive big data analysis.
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