Abstract Sentiment analysis in digital humanities can reveal interpersonal relationships from large amounts of data across different texts at the same time. This study aims to automatically detect authors’ sentiments toward individuals mentioned in Late Ottoman—Early Turkish Republic period memoirs. We focused on two staged pipeline which allows understanding authors’ relationships with other individual personalities. We first fine-tuned BERTurk model for Named Entity Recognition (NER) task to detect individuals in memoirs. Secondly, while the literature acknowledges the challenges of sentiment analysis in historical and literary texts, we further endeavor to detect not only the general sentiments of the given text but also authors’ sentiments toward mentioned individuals. To address this, we experimentally explored possible ways to identify authors’ sentiments toward individuals, namely cross-individual sentiment analysis (CISA), by fine-tuning encoder-based PLMs. Our general sentiment analysis model achieved an F1 score of 0.9262, and our CISA pipeline achieved 0.8705. The framework from NER to sentiment analysis revealed promising results for such tasks, as shown in excerpts from İbrahim Temo’s memoir, subsequently offering the field of digital humanities a framework to analyse interpersonal relationships within large corpora of historical texts.
İlter et al. (Wed,) studied this question.