cross-posted from: https://lemmy.ca/post/69219331

Among other things github interaction with projects is analyzed so I think this is relevant to programming too.

open access paper https://arxiv.org/abs/2511.03877

Cross-channel prediction outperforms same-channel pre- diction for early input-horizon, across all models. This is consistent with correlations plots in Figure 3 and Figure 2…

…

We establish Lead-Lag Forecasting (LLF) as a formal prediction problem, motivated by the gap between observed lead-lag dynam- ics in important domains—including scientific and technological impact—and popular time series forecasting benchmarks. We cat- alyze research on LLF by curating and releasing two novel datasets: arXiv papers and GitHub repositories. We establish lead-lag rela- tionships in streams of activity data and provide baseline numbers for several standard supervised machine learning methods on the task of predicting a 5-year outcome from as little as one month of observation. While our results demonstrate the existence of predic- tive signal, we speculate that there are opportunities for innovation to improve predictions.

Smells like Category Theory to me!