Personal Instants

We live in a society governed by information, much of which is produced by us through the most diverse ubiquitous computing devices. Every day more people are connected to the Internet and more information is produced. In large part, this increase in online production is due to social networks and the content we produce and share on them. Instagram alone has more than 1 billion users. As almost all activities on social networks, many of our activities on Instagram are performed in a few seconds and quickly become part of the past and are forever forgotten.
From this reflection comes Personal Instants, a visual representation of our spontaneous activity on Instagram that aims to reveal the huge amount of data and content produced by us in this virtual universe and, at the same time, reveal our type of virtual persona, our online social stance, in a perpetual manner. The tool presents itself as a resource for users to explore all their activity in an overview mode so that they could discover unknown activity patterns and understand a little better the type of behaviour they have on the social network. The work resorts to the users own downloadable data about their Instagram activity which is then used to define the visualization elements and their disposition.


Visualization Organisms


Taking the metaphor of the universe of virtual organisms aforementioned, we wanted to represent each type of action/event through a distinct organism. Generally, when we talk about organisms from invisible universes we are often talking about microscopic organisms as if they were the unitary modules of something bigger, and for that reason, we chose a pixel-based approach to create the organisms, since the pixel is the module of the virtual universe when made visible.
The body core is common to all organisms, being distinguished only by the colour corresponding to the category of activity to which it belongs.
The type of action/event of the organism is indicated by its main colour. The remaining parts of the organism were designed to visibly resemble the icons that are generally used to represent the respective object or action. Active actions/events such as media production and sharing, giving likes and making comments take on more vivid colours in order to stand out more while passive activity, which does not involve the creation of new data, such as visualizing other users’ content or making new connections acquire less vivid colours (see Figure 1).

Figure 1

Type of action/events and corresponding organisms.


Grid Visualization


The visual mapping process was designed through a continuous thread (just like the feed is presented on Instagram) from left to right and from top to bottom, generating a visual mesh to be read in a familiar and natural process for the users.
To more easily locate the represented organisms in time and also to have a better perception of the user’s daily activity dimension, a tag containing the corresponding date was added to the beginning of each day’s activity.
Another temporal variable that was taken into account was the user inactivity interval, that is, the gap of days without any type of activity associated with the user account. To represent this interval, and to emphasize this personal behaviour which in our opinion is a piece of distinctive information in the user profile characterization, a visual interval was added to the mesh with the number of modules equal to the gap of inactivity days (See Figure 2).

Figure 2

Activity mesh mapping process, starting on the canvas top-left corner and taking a direction from left to right and from top to bottom.



Since the work was conceived with the intent of perceiving the different types of Instagram users profiles, namely through their behaviours, we requested the activity data from several users, of which the results of two can be seen in Figure 3 and Figure 4.

Figure 3

Grid visualization of one user data. On the right, can be seen a zoomed excerpt of the visualization.
A PDF version of the user can be consulted at: User 1 activity


Figure 4

A PDF version of the user can be consulted at: User 2 activity


Virtual Persona


In addition to the grid visualization, where all actions that constitute the user’s activity are broken down to a single organism, we also intended to represent that same activity in a more abstract and condensed way that could allow the profiling of the user’s online behaviour, as a self-portrait of the user activity. The data mapping process was based primarily on a polar coordinate system.

The six main types of activity (comments, connections, likes, media, saved, seen content) are represented in six points equally distanced, along a circumference, from the centre of the canvas. Each type of activity is represented by a circle filled with the corresponding colour, activity centroid (AC), marked from A to F in figure 5. The diameter of the circle is a mapped value representing the ratio of the total events of that type of activity divided by the entire user activity. At the same time, the bigger the diameter, the further away from the centre the AC will be. From this choice of design, the user can quickly and easily perceive a relationship between the amount of each type of activity.

Another visual element associated with each type of activity is the division of that same activity into four parts of the day: dawn, morning, afternoon and night. These parts of the day are divided between 0h – 6h, 6h – 12h, 12h – 18h, 18h – 24h, respectively. Each part is represented by a 90° arc around the activity circle. Starting from the top, the arcs are drawn clockwise. The stroke weight represents the relative amount of corresponding activity that occurred within that time period (See Figure 4).


Figure 5

Virtual Persona mapping process (1/2).

In order to provide also a global idea of the entire activity distribution throughout the day, the activity is distributed over the same four parts of the day and mapped into four circles, marked from G to J in figure 6, where the diameter and distance to the centre are calculated with the same formula applied to the circles that represent the different types of activity. To further distinguish types of personas among the users’ data, we use the AC points, in decreasing order of events, to draw a polygon through vertex curves. This gives origin to similar forms for similar types of behaviour. In a very similar way, another polygon was created using the same AC points. This polygon is coloured with an average colour, obtained with the average calculation of the RGB channels of the activity colours over the entire activity, thus obtaining a chromatic approximation to the user’s predominant type of activity/activities.


Figure 6

Virtual Persona mapping process (2/2).

The set of black circles within the area formed by the AC points represent the user activity days, each day is represented by a single circle. The circle diameter corresponds to the activities carried out on that given day. The circle position is, once more, obtained with an average calculation, using the AC points of the types of activities performed within that day (See Figure 7).

Figure 7

Mapping process for each black circle that represents a day’s activity.


Below are presented the virtual personas resulting from the data of six users that quickly reveal three distinct types of personas due to the predominant colour of the polygon, further emphasized with the AC circles position and dimension.

Figure 8

Virtual Personas resulting from six different Instagram users’ data.


The work can be accessed here so that users can explore their own data.




  • P. Silva, P. Martins, and P. Machado, “Personal Instants,” in 9th Conference on Computation, Communication, Aesthetics & X (xCoAx 2021), 2021.