Modeling the Cognitive Effects of Social Media Algorithms With Textual and Behavioral Data: A Deep Hybrid DistilBERT , BiLSTM , and CatBoost Analysis
A replicable, empirically‐driven model of bias conscious ranking analysis in personalized feeds, which provides insights on content algorithms in a scalable way in both maintaining engagement and contributing to the passive process of rationalizing modeling behavioral proxies of user attention and selective exposure.