@inproceedings{fischer-biemann-2026-perspectives,
    title = "Perspectives {--} Interactive Document Clustering for Qualitative Data Analysis",
    author = "Fischer, Tim  and
      Biemann, Chris",
    editor = {Hamilton, Sil  and
      {\"O}hman, Emily  and
      Hicke, Rebecca M. M.  and
      Bizzoni, Yuri  and
      Bax, Axel  and
      Matthews, Jacob A.  and
      H{\"a}m{\"a}l{\"a}inen, Mika},
    booktitle = "Proceedings of the 6th International Conference on Natural Language Processing for the Digital Humanities",
    month = jul,
    year = "2026",
    address = "San Diego, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.nlp4dh-1.36/",
    pages = "411--422",
    ISBN = "979-8-89176-427-9",
    abstract = "This paper introduces \textit{Perspectives}, an interactive extension of a qualitative data analysis tool suite developed at our university, designed to empower Digital Humanities (DH) scholars to explore and organize large, unstructured document collections. \textit{Perspectives} implements a flexible, aspect-focused document clustering pipeline with human-in-the-loop refinement capabilities.We showcase how this process can be initially steered by defining analytical lenses through document rewriting prompts and instruction-based embeddings, and further aligned with user intent through tools for refining clusters and mechanisms for fine-tuning the embedding model. The demonstration highlights a typical workflow, illustrating how DH researchers can leverage \textit{Perspectives}{'}s interactive document map to uncover topics, sentiments, or other relevant categories, thereby gaining insights and preparing their data for subsequent in-depth analysis."
}