Abstract
For seven years, the Text2Story Workshop series has fostered a vibrant community dedicated to understanding narrative structure in text, resulting in significant contributions to the field and developing a shared understanding of the challenges in this domain. While traditional methods have yielded valuable insights, the advent of Transformers and LLMs have ignited a new wave of interest in narrative understanding. The previous iteration of the workshop also witnessed a surge in LLM-based approaches, demonstrating the community’s growing recognition of their potential. In this eighth edition we propose to go deeper into the role of LLMs in narrative understanding. While LLMs have revolutionized the field of NLP and are the go-to tools for any NLP task, the ability to capture, represent and analyze contextual nuances in longer texts is still an elusive goal, let alone the understanding of consistent fine-grained narrative structures in text. Consequently, this iteration of the workshop will explore the issues involved in using LLMs to unravel narrative structures, while also examining the characteristics of narratives generated by LLMs. By fostering dialogue on these emerging areas, we aim to continue the workshop's tradition of driving innovation in narrative understanding research. Text2Story encompasses sessions covering full research papers, work-in-progress, demos, resources, position and dissemination papers, along with one keynote talk.

Abstract
Purpose Citizen engagement plays a crucial role in transitioning to sustainable service ecosystems. While customer engagement has been extensively studied in service research, citizen engagement has received significantly less attention. By synthesizing customer and citizen engagement literatures, this study develops an integrated framework to conceptually clarify the dual role of customer-citizen engagement for sustainability. Design/methodology/approach This study builds on a systematic literature review of customer engagement literature in service research and citizen engagement literature. Following a theory synthesis approach, we qualitatively analyzed 126 articles to develop an integrated conceptual framework of customer-citizen engagement for sustainability through a process of abductive reasoning. Findings The analysis showed that customer engagement and citizen engagement literatures have developed mostly separately but provide complementary views. While the customer engagement literature has traditionally focused on business-related facets, such as engagement with brands, the citizen perspective broadens the engagement scope to other citizens, communities and society in general. The integrated framework highlights the interplay between citizen and customer roles and the impact of their relationships with multiple objects on sustainability. Originality/value This integrated framework contributes to advancing our understanding of customer-citizen engagement, broadening the scope of subject-object engagement by examining the interplay between these roles in how they engage for sustainability and moving beyond the traditional dyadic perspective to a multi-level perspective of service ecosystems. This framework also enables the development of a set of research directions to advance the understanding of engagement in sustainable service ecosystems.

Abstract
We propose an approach to cluster and classify compositional data. We transform the compositional data into directional data using the square root transformation. To cluster the compositional data, we apply the identification of a mixture of Watson distributions on the hypersphere and to classify the compositional data into predefined groups, we apply Bayes rules based on the Watson distribution to the directional data. We then compare our clustering results with those obtained in hierarchical clustering and in the K-means clustering using the log-ratio transformations of the data and compare our classification results with those obtained in linear discriminant analysis using log-ratio transformations of the data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Abstract
Context. HD135344AB is a young visual binary system that is best known for the protoplanetary disk around the secondary star. The circumstellar environment of the A0-type primary star, on the other hand, is already depleted. HD135344A is therefore an ideal target for the exploration of recently formed giant planets because it is not obscured by dust. Aims. We searched for and characterized substellar companions to HD135344A down to separations of about 10 au. Methods. We observed HD135344A with VLT/SPHERE in the H23 and K12 bands and obtained YJ and YJH spectroscopy. In addition, we carried out VLTI/GRAVITY observations for the further astrometric and spectroscopic confirmation of a detected companion. Results. We discovered a close-in young giant planet, HD135344Ab, with a mass of about 10 M-J. The multi-epoch astrometry confirms the bound nature based on common parallax and common proper motion. This firmly rules out the scenario of a non-stationary background star. The semi-major axis of the planetary orbit is approximately 15-20 au, and the photometry is consistent with that of a mid L-type object. The inferred atmospheric and bulk parameters further confirm the young and planetary nature of the companion. Conclusions. HD135344Ab is one of the youngest directly imaged planets that has fully formed and orbits on Solar System scales. It is a valuable target for studying the early evolution and atmosphere of a giant planet that could have formed in the vicinity of the snowline.

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