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Periodicity

I have a rather awkward subject to discuss. The last time I brought it up in mixed company, someone slapped me. But I’m going to do it anyway, because it’s worth discussing.

Natural language processing and semantic analysis allows us to extract sentiment from documents. Marketing organizations and community managers rely on tools from Scoutlabs, Radian6, and others that try to understand how online communities feel about their brands and products.

As we share more of our lives online, there’s more to analyze. Researchers from Northeastern University and Harvard University analyzed Twitter’s mood over the day. This kind of sentiment analysis can look at someone’s online messages and decide whether they’re angry or content, happy or sad. Given data over time, it can likely recognize patterns of mood, even cycles.

Such as those that occur every twenty-eight days.

(It’s at this point that my dinner companion launched a well-aimed palm at my somewhat scruffy chin.)
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Understanding human behaviour is vital for good product design. But you can’t just ask people what they need, you have to observe them first-hand. iPods, eBay and TiVo exist because designers watched people, noticed a problem with current products, and designed a solution for a problem people didn’t even know they had.

At OXO Foods in the UK, researchers studied how people measure liquids while cooking, and noticed that most people need to bend down repeatedly to read the markings on the side of the container. None of them reported this as a problem when interviewed. So OXO designed a measuring jug(cup) which could be viewed from above (shown right). This is an example of the growing science of design ethnography – product design based on direct human observation.

How to measure human behaviour “in the wild”?

Observational studies are expensive to conduct, and sometimes distorted because you can’t always observe someone in their natural environment. Fortunately, computers now make it much easier to collect data from “real world” activities. Such data is invaluable – for product designers to better understand their users, and also for us to help us cultivate a deeper understanding of ourselves. Read more »

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