On Instagram, certain profiles are private and thereby cannot be viewed by the average user. Such profiles however are not immune to investigation and their connections can nevertheless still be traced. In this guide, we will take a look at a given Instagram profile to illustrate how this can be done. Let us take @lizonntok (Liza Tokareva) for example. This is an authentic individual profile which is indeed set to ‘private’. But how might we find out who Liza is following and who is following her? The following steps will explore the ways in which these objectives can be reached.

Step one. Beginning the workaround

All endeavours have to start somewhere, and as with most investigations, we start by considering our input data, which in our case is an alias. So, we first need to drag and drop the Alias entity from the Entity Palette to the graph and enter @lizonntok into the properties tab. Next, we run the transform [Instagram] Get Profile to generate the result of Liza Tokareva’s Instagram profile. From this new entity, we can now try and find our subject’s Facebook page using the transform: [Facebook] Search by Face and Name.

From Liza Tokareva’s Instagram account we have also found her Facebook page.

Having successfully obtained Liza’s Facebook page, we now have access to all of her Facebook friends which can be extracted by running the transform: [Facebook] Get Friends. Since this transform invariably produces a lot of results, it can exceed its anticipated run-time, in which case an hourglass icon will appear instead of the expected entity. If this is the case, we simply rerun the transform from the hourglass icon and our intended results will be generated.

We now have the result of Lisa’s Facebook friends.

Step two. Generating initial results

Now that we have obtained these new entities, we can gain further insight by finding connections within this wider remit. The most effective way to do this is by returning to Instagram as our line of inquiry. By running the [Instagram] Search by Face and Name transform from our new Facebook profile entities, we can find their counterpart Instagram profiles, providing they exist.

The graph will now display all Instagram profiles connected with Lisa’s facebook friends.

These results now represent all the available Instagram profiles from Liza’s pool of Facebook friends, and can be compiled into a list from Liza’s Facebook profile by going to ‘Select Children’, then copying and pasting the results onto a new graph.

From this new graph, we can now expand our findings to include the followers and followees of these Instagram profiles via the transforms: [Instagram] Get Followers and [Instagram] Get Followees. Keeping the main objective of our investigation in mind, the next logical step is to highlight the accounts that have Lisa among their Followers / Followees and hide the other entities which are essentially extraneous. To achieve this, we go to ‘Add Neighbors’ from Liza's Instagram profile entity, then transfer these results to another new graph. The ensuing result will appear as follows:

The graph of Instagram profiles from Liza’s pool of Facebook friends.

Given that it wasn’t possible to view any Facebook friends prior to our search, the identification of eleven people can be considered a successful operation.

Step three. Expanding on findings

While the identification of eleven people is certainly better than none, there is of course still room for improvement. On inspection of Lisa’s Instagram profile, we can see that she has 387 followers and 350 followees, so how can we increase the percentage of identified profiles from the entire pool? Here’s how:

Proceeding from the assumption that a social media user uses the platform to communicate with multiple people, it stands to reason that these correspondents there will have mutual friends. So from this logic it follows that we should be able to expand upon our eleven profiles by searching among their followers and followees to see if any of them match with those of our main subject: Liza. The only condition here is that the accounts we are looking for must be open, otherwise it will not be possible to verify if Liza is following them or they are following her. Since this will inevitably give a multitude of results, we proceed by capping our results using the sliding scale in the ‘investigate’ tab of the toolbar. As our search progresses, we gradually identify more and more of Lisa’s followers and followees. But then we can expand this operation even further by reapplying the same transforms to our newly generated entities, and what will be the result?

  • 87 identified followers of Liza
  • 74 identified followees of Liza
  • An immense graph that does not fully fit into the window due to the sheer quantity of results

To conclude

In summation, we have shown how investigative obstacles can be overcome by applying transforms in an indirect manner. When accounts are set to private, this is not to say they are fundamentally impervious to extraction and analysis, it just means that slightly more oblique approaches may need to be taken to achieve the desired results. By applying these kinds of methods developed by Social Links for SL Pro, the user can explore a wider remit of open sources and derive a much greater amount of information for conducting cases.