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| Photo GrejGuide.dk @ Flickr |
As I mentioned in previous paper improvements I tried to get a lesson from previous mistakes and improve a lot. First, steps are increasing during the day and thus they are not so much independent. Better would be to use heart rate because is totally independent. Second, I can improve my records about sentiment in timing and evaluation. And last but least important is sentiment extraction, instead of supervised learning used in previous work I would like to used unsupervised classification.
So, let's get to details.
Experiment Design
We are still looking for relation between soft data (sentiment) and hard data (measurand). In first experiment it was text recorded via twitter and footsteps. This time it's again text recorded via twitter, but instead footsteps it's heart rate which is more idenpendent.
What's are the main objectives:
- One month experiment (30 days)
- 20 tweets per day (600 tweets minimum)
- Continuous heart rate measurement (24/7)
- Effective time for heart rate measurement between 7 and 23, i. e. 16 hours a day, rest used for wristband charging
- No sleep activity monitoring
- Steps monitoring? Perhaps.
