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H1N1 Naming Conventions and Folksonomy

April 13, 2010

Last May, I talked about what people were calling H1N1 influenza. I noted that crisis communicators could learn a lesson about what do call disasters that happened to their clients. It seemed that the vacillating that authorities did about the naming convention ultimately backfired and ended up confusing the public so much that they just called it swine flu.

Well, apparently, that wasn’t the only problem.

On Professor Crawford Kilian’s blog, he mentioned an abstract published in PLoS One by a couple of Danish researchers that caught upon the naming confusion and found another way that it was problematic. It turns out that due to inconsistency in naming conventions, it was possible to get wildly different scholarly article search results on PubMed. The authors explain below:

Methodology
We first formulated a PubMed search algorithm covering different names of the influenza pandemic and simulated the results that it would have retrieved from weekly searches for relevant new records during the first 10 weeks of the pandemic. To assess the impact of failing to include every term in this search, we then conducted the same searches but omitted in turn “h1n1,” “swine,” “influenza” and “flu” from the search string, and compared the results to those for the full string.

Principal Findings
On average, our core search string identified 44.3 potentially relevant new records at the end of each week. Of these, we determined that an average of 27.8 records were relevant. When we excluded one term from the string, the percentage of records missed out of the total number of relevant records averaged 18.7% for omitting “h1n1,” 13.6% for “swine,” 17.5% for “influenza,” and 20.6% for “flu.”

Now, I’ve always been a big fan of folksonomy, and believed that, over time, with enough users and interactions, proper tagging of information can take place. Look at the #pdxboom phenomenon, or really any conference Twitter hashtag discussions. More and more users change over to the popular tags; which does two things, it reinforces the popularity of the terminology and makes it more likely to be adopted by others, and allows for confirmation of the descriptiveness of the tag (because if it was wrong, or not exact, people wouldn’t use it).

Norgaard and Lazarus were able to show that improper—or imperfect—tagging renders information impossible to find. There is one difference between the two situations, though. In the social media example, everyone gets a say. At a particularly huge conference, dozens of people could refine the hashtag selection, until the contenders are reduced to just one. In the academic world, only the authors get to tag their article. If they disagree with calling something “swine flu,” for example, they won’t tag it that way and everyone looking for information on swine flu will be unable to find it. The authors argue that some fatherly figure should just establish some common language and let that be that. Those of us in PR and crisis communications know that what something is called is not up to any one person, and can change from hour to hour – especially if it’s an emergency situation getting lots of media attention (think, “TERROR on Route 9!!!” for a automobile accident).

I argue the opposite recommendation. Authors should get to recommend tags to their articles. Other academics who encounter the article and digest it can either support the recommended tags or recommend new ones. As more people read the article and more tags are added and those tags are refined, an exact set – a correct set – will emerge. Of course, that argument sounds very eerily like something an open access journal would do, so I’m guessing it won’t happen any time soon. And Drs. Norgaard and Lazarus’s theory will be borne out again in future emergencies.

What do you think? Would it work?

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