Using social media for research – Recap from #SoCapOtt

How I feel when I come across bad research posted online and spread through social media. Credit xkcd.com

It takes a lot to get me out of the sun on a hot Saturday in July and into an over-air-conditioned venue for a full day of learning, but fortunately the Social Capital Conference this weekend delivered a worthwhile, great time.

This past Saturday I joined over 200 others on the Algonquin College campus for a so-called “Social Media Learnathon.” I was even priviledged enough to present at the event. I spoke about using social media for research–and specifically for research to fuel a social or communications strategy.

The session started off about how bad research gets propagated online and how we should all pay close attention to the sources of research–always read before you retweet! My favourite example is the preposterous example of Business Insider’s 16-person survey (with no explanation of how this “sample” was chosen) that led to the publication damning groupon.

Using my preferred paid tool (Sysomos) I showed some examples of charts and graphs you can use to do research to support strategy development, but also told attendees about some free tools and work-arounds to accomplish similar tasks on a budget. Like most things–you do tend to get what you pay for and using free tools usually means a trade-off for quantity and quality of data as well as the time required for you to invest to get the same results. (Of course there are paid tools that aren’t worth the price tag so please be diligent and thorough in your tool search!)

The presentation also covered using social media for research to analyze media issues and to conduct a comparative analysis as other examples of how social media data can help fuel business intelligence.

The presentation quoted and covered a few concepts by Avinash Kaushik–the leading web analytics evangelist and probably my favourite presenter of all time. Although he speaks in the context of web analytics, many of his concepts can apply to other areas including data-driven decision making to combat the HiPPOs,  and the 90-10 rule for magnificent web analytics success.

One thing I wanted to talk about, but didn’t get around to, was the value of comments and dialogue in social media research. One huge limitation of the available tools is they are unable to capture reactions or additional comments that are relevant but do not include specific search terms. This is one instance where having a skilled analyst makes a big difference because he or she would know to dive deeper and look for this type of insight outside of a tool.

Unfortunately I can’t share my slides from the presentation, but I’m more than discuss the topic with you offline, just drop me a line at kellyrusk(at)gmail.com.

Thanks to Sherrilynne Starkie who posted a recap of my session, complete with video footage (aghhh! Don’t watch!!).