Abstract
The Text2Story Workshop series, dedicated to Narrative Extraction from Texts, has been running successfully since 2018. Over the past six years, significant progress, largely propelled by Transformers and Large Language Models, has advanced our understanding of natural language text. Nevertheless, the representation, analysis, generation, and comprehensive identification of the different elements that compose a narrative structure remains a challenging objective. In its seventh edition, the workshop strives to consolidate a common platform and a multidisciplinary community for discussing and addressing various issues related to narrative extraction tasks. In particular, we aim to bring to the forefront the challenges involved in understanding narrative structures and integrating their representation into established frameworks, as well as in modern architectures (e.g., transformers) and AI-powered language models (e.g., chatGPT) which are now common and form the backbone of almost every IR and NLP application. Text2Story encompasses sessions covering full research papers, work-in-progress, demos, resources, position and dissemination papers, along with keynote talks. Moreover, there is dedicated space for informal discussions on methods, challenges, and the future of research in this dynamic field.

Abstract
Deep Learning models are automating many daily routine tasks, indicating that in the future, even high-risk tasks will be automated, such as healthcare and automated driving areas. However, due to the complexity of such deep learning models, it is challenging to understand their reasoning. Furthermore, the black box nature of the designed deep learning models may undermine public confidence in critical areas. Current efforts on intrinsically interpretable models focus only on classification tasks, leaving a gap in models for object detection. Therefore, this paper proposes a deep learning model that is intrinsically explainable for the object detection task. The chosen design for such a model is a combination of the well-known Faster-RCNN model with the ProtoPNet model. For the Explainable AI experiments, the chosen performance metric was the similarity score from the ProtoPNet model. Our experiments show that this combination leads to a deep learning model that is able to explain its classifications, with similarity scores, using a visual bag of words, which are called prototypes, that are learned during the training process. Furthermore, the adoption of such an explainable method does not seem to hinder the performance of the proposed model, which achieved a mAP of 69% in the KITTI dataset and a mAP of 66% in the GRAZPEDWRI-DX dataset. Moreover, our explanations have shown a high reliability on the similarity score.

Abstract
PurposeThis study aims to estimate the impact of refugee inflows on host countries' entrepreneurial rates. The refugee crisis led to an increased scientific and public policy interest in the impact of refugee inflows on host countries. One important perspective of such an impact, which is still underexplored, is the impact of refugee inflows on host countries entrepreneurial rates. Given the high number of refugees that flow to some countries, it would be valuable to assess the extent to which such countries are likely to reap the benefits from increasing refugee inflows in terms of (native and non-native) entrepreneurial talent enhancement. Design/methodology/approachResorting to dynamic (two-step system generalized method of moments) panel data estimations, based on 186 countries over the period between 2000 and 2019, this study estimates the impact of refugee inflows on host countries' entrepreneurial rates, measured by the total early-stage entrepreneurial activity (TEA) rate and the self-employment rate. FindingsIn general, higher refugee inflows are associated with lower host countries' TEA rates. However, refugee inflows significantly foster self-employment rates of medium-high and high income host countries and host countries located in Africa. These results suggest that refugee inflows tend to enhance necessity related new ventures and/ or new ventures (from native and non-native population) operating in low value-added, low profit sectors. Originality/valueThis study constitutes a novel empirical contribution by providing a macroeconomic, quantitative assessment of the impact of refugee from distinct nationalities on a diverse set of host countries' entrepreneurship rates in the past two decades resorting to dynamic panel data models, which enable to address the heterogeneity of the countries and deal with the endogeneity of the variables of the model.

Abstract
How we perceive and experience the world around us is inherently multisensory. Most of the Virtual Reality (VR) literature is based on the senses of sight and hearing. However, there is a lot of potential for integrating additional stimuli into Virtual Environments (VEs), especially in a training context. Identifying the relevant stimuli for obtaining a virtual experience that is perceptually equivalent to a real experience will lead users to behave the same across environments, which adds substantial value for several training areas, such as firefighters. In this article, we present an experiment aiming to assess the impact of different sensory stimuli on stress, fatigue, cybersickness, Presence and knowledge transfer of users during a firefighter training VE. The results suggested that the stimulus that significantly impacted the user's response was wearing a firefighter's uniform and combining all sensory stimuli under study: heat, weight, uniform, and mask. The results also showed that the VE did not induce cybersickness and that it was successful in the task of transferring knowledge.

Abstract
This study investigated the effect of organizational culture (supportive culture, innovation culture, goal culture and rule culture) on turnover intentions and whether this relationship was mediated by organizational practices of competencies development (training, functional rotation and individualized support) and affective commitment. The study sample consisted of 369 participants working in organizations based in Portugal. The results show that only goal culture positively and significantly affects the three dimensions of organizational practices of development competencies and affective commitment. The culture of support has a positive and significant effect on functional rotation, individualized support and affective commitment. The culture of innovation has a positive and significant effect on training. Supportive culture, goal culture and the dimensions of organizational practices of development competencies negatively and significantly affect exit intentions. The serial mediating effect of organizational practices of development competencies and affective commitment on the relationship between organizational culture (supportive culture and goal culture) and turnover intentions was proven. Organizational culture, especially supportive culture and goal culture, proved to be relevant in boosting the implementation of organizational practices of development competencies, boosting affective commitment and reducing turnover intentions.

Abstract
The study of user logs plays a crucial role in understanding user behavior and preferences in various online environments. By analyzing user logs, researchers can gain valuable insights into how users interact with a system and make informed decisions on system improvements. They can also assess the effectiveness of different features and functionalities. In the field of game design, the exploration of user logs becomes even more important as it provides valuable information on player motivations, preferences, and gameplay patterns. This research explores the impact of Bartle Taxonomy on user behavior analysis through a Game with a Purpose (GWAP) named BartleZ. By analyzing user logs and decisions within the game, BartleZ aims to determine the dominant player type according to the Bartle Taxonomy classification. This research also investigates how different player types engage with the game and the implications for user experience design.