Last week Mashable reported that Twitter had gathered data about key words used in tweets which indicated the moods and behaviour of people on each day of the week for each month of the year.
Essentially they have aggregated the frequency of the following terms:
- “feel happy”
- “feel sad”
- “late for work”
So, what did this reveal?
The most interesting finding to me is that December is a month of highs and lows. While Tuesdays in December often attract “feel happy” tweets, this is the month of the year when users are most likely to use the term “feel sad” in their update.
Why am I interested in this?
Part of the ‘Cheer up love’ care labels project which I have not really explored here is exchanging data from mobile apps with a wearable item like the care labels I have talked about.
So it could be possible that setting the wearable would add a ‘signature’ to your texts, emails or social media updates. This might be the combination that you have set the wearable to that day.
But taking it further, could the wearable item receive data from your texts, emails, social media updates or other quantified self apps or devices which would prompt the wearer to adjust their labels?
I’ve spoken before about using a mood tracking program such as MoodScope to recommend care labels for that day. MoodScope currently only records one mood score per day – but other apps could continue to inform your choice of wearable care labels on a much more regular basis.