Have you ever noticed that Facebook and other companies in the Meta group are always updating their metrics and statistics? This is because there is a great interest in understanding this user data to make platforms smarter and more attractive. To understand more about this, see here how Facebook does it data analysis.
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There are several resources that Facebook uses to be able to collect user data to then build metrics that will reveal user preferences and interests. But how exactly do they do it? If this is also a question for you, see here the most common methods that the social network employs.
Facial recognition
Every photo you post on Facebook and Instagram is computed in Facebook's databases. Plus, when collecting these photos, Meta uses Artificial Intelligence to create patterns of features on our faces and then perform facial recognition. This data can be used to prevent the creation of fake accounts with photos of someone else.
Analysis of texts
Anyone who thinks that after the video revolution on social media, Instagram or Facebook gave up analyzing texts is wrong. After all, most of the content on the network is in text format, be it comments, photo captions and surveys. In this case, all these words will be used to analyze your profile and understand your preferences on networks.
Sensitive content warnings
This is a point of much controversy for Facebook users, who do not always agree with these warnings. However, the social network categorizes content as sensitive after a large volume of user complaints, and this is also a way to collect data and create metrics.
Analysis of likes and engagement
Finally, we have the more traditional method, which most people are familiar with, which takes into account the likes, comments and engagement of the network as a whole. With this data, Facebook will be able to understand the preferences of its users to invest in content that goes viral more easily.
