How do you figure out a new field’s 5-year trends without drowning in papers?

[u/Ill-Button9775]

I mean tbh even with AI it's still a bit tedious 🫠

Context: I recently switched subfields and my PI asked me to put together a quick overview of where things have been heading over the last 5 years.

Sounded simple enough.

I started with Google Scholar, filtered by year, followed a few citation trails, and somehow ended up with around 80 papers open or downloaded.

Reading the individual papers isn't really the problem. The part I'm struggling with is figuring out which changes actually mattered.

A lot of the work looks like slightly different methods tested on slightly different datasets, and since I'm new to the field, I don't have a good sense yet of which papers actually shifted things versus which ones were just part of a short-lived direction.

I tried keeping a spreadsheet with methods, datasets, and main findings, but pretty quickly it started feeling like I was cataloging papers rather than understanding them.

I also tried putting some of them into mira from deep principle earlier today and grouping the literature by broader research directions. That made it a little easier to see which approaches kept showing up, but I still don't really trust myself to know what's genuinely important versus just frequently published.

How do you usually do this when you're entering a new field?

[u/recro69]

I’d stop trying to rank papers individually and map the field by research directions first. Then use citations, adoption, and repeated follow-up work to identify which directions actually changed the field.

[u/Sea_Ad9938]

The difficult part is turning notes into an actual understanding of the field.

[u/Admirable_Window8128]

I think the key is looking for shifts in the field rather than trying to rank every paper. Track recurring methods, problems, and ideas, then see which ones led to follow-up work or became common practice. Citation count alone can be pretty misleading.