UberNoggin

Those who know me probably know that after finishing my PhD a year ago I went into a little bit of an academic funk. There was soul-searching, head banging, and more than a little bit of self doubt. Imposter syndrome and other forms of intellectual angst aren’t all that unusual in academia but I had it bad. Most of the turmoil was around the fact that I’ve switched disciplines. I went from being an English geek (rhetoric specifically) to teaching and researching in a Business school. Don’t get me wrong. It’s amazing. It kicks ass in a major way. However, learning the norms and conventions of being a researcher in a discipline that is so different from where I came from has its hurdles. Add to that the typical post-PhD trouble of establishing your personal research agenda with no more faculty/advisor hand holding and there are some non-trivial growing pains to get through.

I spent about three months last year writing a research question a day just to get ideas out. Afterwards, I went through them to see what trends I could uncover in my interests. There were certainly some “Gee, I know what I was thinking about that week” kind of trends but the overall picture helped me focus on my desire to make real meaning out of big data collected from social sources. Social technologies have been my thing for a long time. I even designed a giant certification program for Kelley about social technologies in business.  But in terms of research agenda, I still had some refining to do.

There are a couple of big issues related to being an academic who studies social technologies:

1. It moves FAST! You just can’t be an “expert” in everything related to these tools. For every new tool that comes to market another one becomes defunct and you’re constantly crossing your fingers that the dying ones aren’t the ones you’re studying and that the new ones don’t make your ideas completely wrong.
2. There are TONS of self-proclaimed social technology experts out there. You just don’t have this in other areas. Random people can’t profess themselves to be medical or legal experts. There aren’t “biology gurus” on Twitter. But you can’t throw a rock without hitting someone with a bio like “I’m a speaker, guru, and social media evangelist.” I’m not competing with these folks but to the general public it’s tough to discern the difference between these people and serious academics who study the same topics.
3. Not everyone takes social technology seriously yet. If I had a dollar for every time I heard that this whole internet thing is a fad or just something that the kids are into…well, my student loans would have been paid off a long time ago.

That being said, I’m not deterred. I know that even with hundreds of articles on Facebook alone, there’s still room for unique thoughts when it comes to research and social technologies. So where do I want to fit in and will that work in my new discipline?

I think I finally have the answer. It’s big data. It’s scraping millions of Tweets to answer big questions. It’s aggregating content created by prosumers from dozens of channels to see what we can find. I’m tired of hearing about monitoring services and clipping services that only serve to provide a biased pinhole view of the conversation. It’s time to stop looking just at the trees you think are relevant to you and start studying the forest and the ecosystem within it.

So, after all this time and all this hair pulling, I finally have it. I have my BIG question and a fairly good research agenda to back it up.  My goal is to found out if there is a better way to harness and uncover insights from big data gathered from social sources. Rather than asking a question and then gathering data directly related to that question, I want to find a scalable and repeatable way to conduct ongoing analysis of this data to shed light on unexpected trends and correlations that then lead to research questions. I want to find the freaky, unexpected, surprising and yet powerful revelations that make us wonder why and dig deeper.

Having arrived at this focus I feel excited and geared up. The path isn’t totally clear yet but it’s so much better than it was and I’m optimistic that I’ve landed somewhere that I can do some interesting and important things. It’s so good to finally feel that way.

1. Britt Watwood says:

   May 19, 2012 at 4:57 am

   Glad you are diving into the big data niche. One of our next big challenges in academia is to do some sense-making of all the data around learning, whether that be in college networks or student social networks, as ways to enhance learning and spot opportunities for interventions that could make students more successful. I look forward to following your future thoughts!
2. Bryan Alexander says:

   May 19, 2012 at 1:17 pm

   Good choice. Data is a killer, deep problem now.
3. Lanette Cadle says:

   May 21, 2012 at 5:44 am

   I’m glad you’re doing this. if Computers and Writing folk don’t take on the big questions, those questions will be answered tangentially and in ways that don’t serve the long view.