This June, I was carrying out a self-tracking experiment on my mood. I have been logging an emoji and a few words thrice a day. Every morning, afternoon and evening I logged a mood emoji in my Excel journal. In just 30 days, this helped me understand what generally influences my mood on a normal day.
For example I used 😊 for happy, 😌 for relaxed, 😃 for really happy and 😕 for dull. I wrote a few words of text with them to understand what factors influence my mood. Further I correlated these mood emojis with sleep, exercise and places data from Instant. I am displaying 10 days of my data here and also plotted a graph with the most common moods.
It was interesting to see with this experiment that I could make conclusions on my daily lifestyle affecting my mood in a short duration of time. I tried to focus on general events which take place everyday to make conclusions rather than one off events.
I drew some conclusions looking at the correlated data. In the morning, sleep attributes directly to my mood. My mood in afternoons are mostly influenced by the type of work I am doing & lunch. At night my mood is connected to my exercise and the people I eat dinner with. I also noted that I have a dull mood mostly from muscle soreness from my weight training. I have decided to increase my training in moderation so I don’t end up overdoing weights which cause muscle soreness.
Based on these experiments, at Emberify we are working on our active tracking journaling app called Journaly which we will be unveiling in a couple of weeks. This experiment helped me realise the importance of active tracking along with passive tracking that Instant has been doing for me.