Needles in a Haystack
The term information overload was popularized in the 1970 book Future Shock by Adam Toffler, who correctly foresaw an era of rapid technological and sociological change that would leave many people feeling disconnected and disoriented. But even a futurist as prescient as Toffler probably would have been unable to comprehend the volume of information being produced and transmitted every day on Twitter, Facebook, and other forms of social media.
As Susan Etlinger notes in her article in the March/April issue of Information Outlook, "… when Beyonce went on the Video Music Awards and showed she was pregnant, that generated 8,000 tweets per second." Granted, it's unlikely that tweets about pregnant celebrities will be of interest to the average SLA member or his or her organization. Nonetheless, comments and discussions on Twitter, Facebook, and other social media are information resources, and Etlinger believes that information professionals should not flinch from trying to extract value from them.
"The librarian needs to be the strategist, the first line of defense, in understanding and recommending how social data should be used," she states. "… There's an incredible artifact of social data out there … that encapsulates opinions in a way we've never really seen before."
Etlinger cautions that much of the social data being produced are "a mess," but David Milward and Guy Singh have plenty to say about how to make sense of it. In their article, "Clarifying the Social Media Blur," Milward and Singh offer guidance and case studies on using agile text mining to identify not only the content of social data, but also the sentiments being expressed, the impact of those sentiments, and the key opinion leaders in various communities.
According to Milward and Singh, the imposing volume of social data is actually a blessing in disguise. "In the text mining world," they write, "the more documents there are, the better the results are likely to be."
To read more of what Etlinger, Milward and Singh have to say about making sense of social data, read the March/April issue of Information Outlook.
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