The post-API age in digital research has brought immediate consequences in research activities based on (big) data owned by online platforms. Even some initiatives made by online platforms themselves, mainly based on funding specific research projects, have not found a warm reception in the research community and have been considered not enough to do research on the most relevant phenomena of the digital public sphere. Therefore, since the access-to-data has become a relevant issue even for civil society organizations and public actors dealing with digital ecosystem, a specific brand-new issue network among public institutions, NGOs, and researches has been established. The technical expertise, the shared interests, and the fulfilment of similar goals in shaping public values in the online platforms activities seem to be crucial to the permanence and even to the institutionalization of such an issue network.
TopFor many years, digital research in social sciences has been based on the analysis of semi-structured and unstructured data (Veltri, 2020) from online platforms collected through the APIs (Application Programming Interfaces), allowing anyone with a few programming skills to gather massive volumes of data about a given platform’s users and content. Since the free collection of data has been simplified thanks to the collaboration between researchers and developers aware of the potential offered by this technology for the knowledge of social phenomena on the web, this opportunity has generated an approach to the computational social sciences based on the extraction of data records made available through the online platforms programming interfaces (Caliandro, Gandini, 2019). Numerous tools, e.g. Netvizz (Rieder, 2013) were born, for example, from the fruitful work of the Digital Methods Initiative (Rogers, 2013).
Furthermore, since social scientists doing digital research become part of an assembly, which includes human components, methodological devices and data, and which itself becomes the object of research (Lupton, 2018), access to data and the collection via APIs has allowed social researchers to analyze what kind of web epistemology the platforms convey when they shape the content, types and categories of knowledge they make accessible (Amaturo, Aragona, 2019) 1. Even the lack of transparency about how big data are collected and codified by private companies is a relevant issue digital research scholars should face (Veltri, 2020). Finally, the compliance of such big data to data quality requirements is becoming fundamental in the digital social research (Stefanizzi, 2021).
The Cambridge Analytica scandal in 2018, jointly with some restrictions aimed at protecting the users’ privacy, has led to the API shutdown2. As stated by Freelon (2018):
When companies can restrict or eliminate API access at any time, for any reason, and without any recourse, computational researchers and students need to seriously consider how to proceed. We find ourselves in a situation where heavy investment in teaching and learning platform-specific methods can be rendered useless overnight: this is what I mean by “the post-API age”. (p. 665)