Nivedit Majumdar Nivedit Majumdar

Quantifying Emotions: Mood Tracking Methods

The entire purpose of the Quantified Self movement has been to enable users to record various aspects of their life. The users can then use the recorded data to make informed decisions for an overall betterment. Fitness trackers have been prominent in this regard, as they are devices which track the daily activities of an individual in a completely non obtrusive manner. Sleep trackers come in at a close second, and they have proved to be effective in combating sleep disorders.

But in this article, I take a look at a more obscure aspect of the Quantified Self. Keeping a track of the emotions that an individual goes through in a day can invariably be beneficial, and that forms the crux of my article here: Mood Tracking, how is it done, and how can it be useful.


Like all phenomena and stimuli that are measured in the Quantified Self movement, Mood Tracking involves the maintenance of charts and diagrams to keep track of what kind of emotions a person experiences through the day. I will be explaining about these charts more in detail soon, but for now, let’s ease into the benefits of the concept itself.

Mood tracking proves to be extremely beneficial for people suffering from mood related disorders. Something as simple as getting anxious and frustrated on a regular basis, to genuine conditions such as Bipolar Disorder, Mood Tracking can enable people to keep a track of all the stimuli causing the emotions they experience, and to appropriately maximise the stimuli which make them feel better!

In fact, mood tracking is all the more relevant in this current day and age of ever increasing workload and stress, where people simply cannot keep up with the changing environments and ultimately succumb to mood related disorders. This is a statistic showing the prevalence of mood related disorders among adults in the United States between 2008 and 2012. The share of people with mood related disorders has gone up since then, which makes the concept of mood tracking as an active form of QS all the more relevant.

(Data Source: Statista)



Unlike recording fitness and sleep data, mood tracking is a very subjective affair and can be regarded as quite controversial, since different people have different definitions for emotions. Over the years, there have been various types of graphs and tools designed to record emotions, each bringing in more changes and improvements than the previous one.


The Circumplex approach basically incorporates a two-dimensional model in order to describe and measure mood. The X-Axis comprises of “pleasantness/unpleasantness,” that is referred to as valence. The Y-Axis comprises of  “arousal,” or “activation.”

(Image Source: QuantifiedSelf)

There are multiple variations of this type of approach, with all of them involving the emotions being defined on a two dimensional graph.

(Image Source: QuantifiedSelf)


(Image Source: QuantifiedSelf)

The biggest advantage of this approach is that it is simple enough to understand, and therefore it can suitable sum up simple emotions. However, when it comes to complex emotions (such as feeling happy and sad at the same time – a feeling of nostalgia perhaps?), the graph fails to work, since it generalises happy and sad emotions as opposite sides of a spectrum.


(Image Source: Relationship Between Attitudes and Evaluative Space; A Critical Review – John T. Cacioppo and Gary G. Bernsten)

The problem posed by the Circumplex approach was rectified, somewhat, by the evaluative approach. Popularised by John T. Cacioppo, this model presents emotions as part of an evaluative space, with the axes as coactivity and reciprocity.

(Image Source: Relationship Between Attitudes and Evaluative Space; A Critical Review – John T. Cacioppo and Gary G. Bernsten)

Depending upon the contours and distance from the target stimuli, various emotions can be graphed in a manner which incorporates much more emotions than the circumplex approach.


POMS – or Profile Of Mood States – is considered as the gold standard when it comes to a psychological assessment for measuring mood fluctuations that is used in clinical and research settings. The assessment comprises of 65 emotion adjectives that are each rated on a five-point scale, where 0= not at all; 1=a little; 2=moderately; 3=quite a bit; and 4=extremely. The answers that the user gives are then grouped into seven dimensions to give an overview of the mood state.

The seven groups are classified as:


Taking into consideration people with Bipolar Disorder, the seven groups were enhanced as under:



Modern day approaches to mood tracking involve a plethora of online and application tools which assess the individual’s moods through various analytical tests and patterns. Keeping mood scores, analysing the content of a written diary or text, voice analysis, facial recognition and various more forms of analysis approaches exist which enable users to actively keep a track of what are the emotions that they have been experiencing and accordingly replicate or introduce factors which might enhance the happiness factors.

(Image Source: QuantifiedSelf)

One of the approaches which I found very interesting was through the music that we listened to. Based on the artists that an individual listens to, a pattern can be developed, which can also be used to assess the moods that a person goes through. had something similar , where it could export the graphs of a user’s playlist to an external application, and this could be used to assess the emotions of the individual.


Psychologists and therapists suggest that actively keeping track of the emotions experienced through the day can help individuals effectively combat mood related disorders. This proves to be beneficial in cases of individuals suffering from depression, Bipolar Disorders, stress and even PMS.

The approaches of recording emotions are quite varied, and each of them comes with its own share of pros and cons. One thing is for sure: once the structure of emotions and moods is presented in a visual manner, it becomes all the more easier for a user to assess and accordingly experiment to enhance the positive emotions!

(For an extended overview of Mood Tracking, I would recommend going through the links on this page.)

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