#callfor Innovating Social Media Research in a Paid-API Era (Media and Communication)

Inicio: 01/04/2025 Fin: 15/04/2025

Entidad Organizadora:

Media and Communication

Localización:

 

By this point, it is well known that social media data is increasingly hard to source as free APIs are mostly locked down by exorbitant paywalls and may also require technological expertise to access and analyze data. This situation has become more dire in recent months and has further bifurcated social media researchers into data “haves” from data “have nots”—and our field is currently adrift as to what the most viable portals and best practices for acquiring social media data are, which has resulted in isolated data vaults and fragmented efforts.

This thematic issue invites proposals from visionaries working in this turbulent space, whether they are media scholars, data vendors, or technological experts looking to help others not only access social media data but also create innovative ways to store, model, and share this data.

Development of historical and contemporary datasets are welcome, as are collaborative enterprises that cross disciplines, regardless of for-profit or non-profit statuses. Indeed, as the days of “free data” have come to a close for many (if not all) social media platforms, the most potent and viable solutions may well originate with industry and market research.

We don’t place parameters on submissions, but some starting points may include, but are not limited to:

  • Who is capable of not only sourcing data, but also analyzing data once acquired—Does everyone need to learn Python, SQL, R, or other coding languages?
  • What sources of data are available for various social media platforms, and which tools or vendors can be used to access that data?
  • Where can we store social media data so that it is at once shareable for academic research but still respectful of privacy and safety concerns?
  • When does data speak for itself? When is enough data enough, and when is it possible to move research into the 21st century with AI and machine learning automations in real time?
  • How do interfaces work—Are they text or image based, and how can our tools leverage what is available to make a contribution to various cognate areas?

Non-ethical issues are paramount here, and while we can all appreciate the ability to problematize the collection and hyper-personalization of exploitative marketing through social media data, we are seeking solutions to existing problems. Essays or thought pieces that don’t advance tangible steps for the collection and analysis of large-scale social data are not the emphasis of this particular thematic issue as we attempt to move at the pace of data to overcome an existential crisis in our field.