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Tracking online word-of-mouth: The people vs machines debate

Great debate, and good idea to conduct it this way. I've been working in online PR and online opinion research for a number of years now, and I tend to side with Mike. I agree that computers are better at coding in a consistent fashion, but they're terrible at "decoding" what it is they're actually reading. Humans are better at it, hands down. Now, I'm surprised to read, in Mark's email that "It’s actually well established that today’s automated systems can achieve 80% accuracy against humans". I would love to see this piece of research. Is it the one where the bulk of results ends up in the "neutral" column by default? And what would the results look like over something like Twitter? and to your point, Twitter is definitely relevant for early-warning monitoring, but exceedingly difficult for a machine to analyze on the fly. One more point: as is often the case, this debates starts with the premise that the social web only speaks English. Nothing could be further from the truth, and big brands need multi-lingual capabilities. And outside of the English-only comfort zone, automated systems fare even worse.

15-Jun-2009

8:48 pm