The success of many social platforms brings together two groups: people seeking connection or content, and advertisers seeking an audience. A service can offer genuine social value while also being shaped by commercial incentives.
In an advertising-funded model, information about users and their activity helps select and measure advertisements. Data analysis and machine learning can support that process. The essential point is simpler than the technology: the organisation paying for advertising has a place in the platform’s priorities.
The social experience is therefore also designed. Systems make some actions easy, give some content greater visibility and reward some forms of participation. They do not reproduce the whole of human society; they model the parts that fit their objectives.
That is a reason to read terms, privacy notices and account settings carefully. It is not a reason to believe that private platforms sit outside data-protection law. The GDPR can apply to the processing carried out by social platforms and advertisers; the precise obligations depend on the activity and actors involved.
I do not want to demonise these services. They can help people share ideas, build communities and find customers. But visibility is not guaranteed, and advertising is not truly free simply because an account costs nothing to open. Time, attention, production and promotion all have a cost.
A search engine may offer a different interface while relying on a related advertising business model. That does not make every search engine a social network. Comparing incentives is more useful than forcing different services into the same category.
The internet grew through institutions and research with deep roots in the United States and later developed internationally. Understanding the history and ownership of the systems we use helps us make more deliberate decisions about them.