@inproceedings{masson-etal-2024-textbi,
    title = "{T}ext{BI}: An Interactive Dashboard for Visualizing Multidimensional {NLP} Annotations in Social Media Data",
    author = "Masson, Maxime  and
      Sallaberry, Christian  and
      Bessagnet, Marie-Noelle  and
      Le Parc Lacayrelle, Annig  and
      Roose, Philippe  and
      Agerri, Rodrigo",
    editor = "Aletras, Nikolaos  and
      De Clercq, Orphee",
    booktitle = "Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations",
    month = mar,
    year = "2024",
    address = "St. Julians, Malta",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.eacl-demo.1",
    pages = "1--9",
    abstract = "In this paper we introduce TextBI, a multimodal generic dashboard designed to present multidimensional text annotations on large volumes of multilingual social media data. This tool focuses on four core dimensions: spatial, temporal, thematic, and personal, and also supports additional enrichment data such as sentiment and engagement. Multiple visualization modes are offered, including frequency, movement, and association. This dashboard addresses the challenge of facilitating the interpretation of NLP annotations by visualizing them in a user-friendly, interactive interface catering to two categories of users: (1) domain stakeholders and (2) NLP researchers. We conducted experiments within the domain of tourism leveraging data from X (formerly Twitter) and incorporating requirements from tourism offices. Our approach, TextBI, represents a significant advancement in the field of visualizing NLP annotations by integrating and blending features from a variety of Business Intelligence, Geographical Information Systems and NLP tools. A demonstration video is also provided https://youtu.be/x714RKvo9Cg",
}