This article presents an affective-based sensemaking system for grouping and suggesting stories created by the users about the cultural artefacts in a museum. By relying on the TCL commonsense reasoning framework, the system exploits the spatial structure of the Plutchik’s “wheel of emotions” to organize the stories according to their extracted emotions. The process of emotion extraction, reasoning, and suggestion is triggered by an app, called GAMGame, and integrated with the sensemaking engine. Following the framework of Citizen Curation, the system allows classifying and suggesting stories encompassing cultural items able to evoke not only the very same emotions of already experienced or preferred museum objects but also novel items sharing different emotional stances and, therefore, able to break the filter bubble effect and open the users’ view toward more inclusive and empathy-based interpretations of cultural content. The system has been designed tested, in the context of the H2020EU SPICE project (Social cohesion, Participation, and Inclusion through Cultural Engagement), in cooperation with the community of the d/Deaf and on the collection of the Gallery of Modern Art (GAM) in Turin. We describe the user-centered design process of the web app and of its components and we report the results concerning the effectiveness of the diversity-seeking, affective-driven, recommendations of stories.

Marco Antonio Stranisci, Rossana Damiano, Enrico Mensa, Viviana Patti, Daniele Radicioni, Tommaso Caselli. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.

Abstract Values, as intended in ethics, determine the shape and validity of moral and social norms, grounding our everyday individual and community behavior on commonsense knowledge. The attempt to untangle human moral and social value-oriented structure of relations requires investigating both the dimension of subjective human perception of the world, and socio-cultural dynamics and multi-agent social interactions. Formalising latent moral content in human interaction is an appealing perspective that would enable a deeper understanding of both social dynamics and individual cognitive and behavioral dimension. To formalize this broad knowledge area, in the context of ValueNet, a modular ontology representing and operationalising moral and social values, we present two modules aiming at representing two main informal theories in literature: (i) the Basic Human Values theory by Shalom Schwartz and (ii) the Moral Foundations Theory by Graham and Haidt. ValueNet is based on reusable Ontology Design Patterns, is aligned to the DOLCE foundational ontology, and is a component of the Framester factual-linguistic knowledge graph.

Despite the large number of computational resources for emotion recognition, there is a lack of data sets relying on appraisal models. According to Appraisal theories, emotions are the outcome of a multi-dimensional evaluation of events. In this paper, we present APPReddit, the first corpus of non-experimental data annotated according to this theory. After describing its development, we compare our resource with enISEAR, a corpus of events created in an experimental setting and annotated for appraisal. Results show that the two corpora can be mapped notwithstanding different typologies of data and annotations schemes. A SVM model trained on APPReddit predicts four appraisal dimensions without significant loss. Merging both corpora in a single training set increases the prediction of 3 out of 4 dimensions. Such findings pave the way to a better performing classification model for appraisal prediction.

In today’s media and in the Web of Data, non-Western people still suffer a lack of representation. In our work, we address this issue by presenting a pipeline for collecting and semantically encoding Wikipedia biographies of writers who are under-represented due to their non-Western origins, or their legal status in a country. The two main components of the ontology will be described, together with a framework for mapping textual biographies to their corresponding semantic representations. A description of the data set, and some examples of biographical texts conversion to the Ontology Classes, will be provided.

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As a pervasive form of artistic expression through ages and me- dia, drama features a twofold nature of its tangible manifestations (theatrical performances, movies, books, etc.) and its intangible abstraction (the story of Cinderella underlying Disney movie and Perrault's fable). The encoding of the intangible drama abstraction of drama documents is relevant for the preservation of cultural heritage and the didactics and research on drama documents. This paper addresses the task of encoding the notion of intangible story abstraction from the drama documents. The reference model is provided by a computational ontology that formally encodes the elements that characterize a drama, for purposes of semantic link- ing and inclusion in annotation schemata. By providing a formal expression posited between drama as work and its manifestations, the ontology-based representation is compliant with the model of Functional Requirements for Bibliographic Records (FRBR).

[EN] Today¿s Internet is evolving toward an open society of humans and computational\nentities, where intelligent agent systems increasingly support the interaction between\nusers and computational components. In this scenario, affect plays a key role, with functions\nthat span from creating and maintaining interpersonal relations, to establishing\ncooperation and trust. Artificial systems¿which can act as both actors and facilitators\nof these interactions¿are more and more requested to integrate affective components\nin order to achieve truly realistic social behaviors and foster the creation of bonds with\nthe users, with timely reactions to their affective input and appropriate expressions\nof affect. Achieving this integration requires to understand and reproduce the role of\naffect in human expressive capabilities, and to account for affect-related phenomena\n(e.g., sentiment, emotions, and mood) that engage social abilities, such as empathy,\nand expressive means, such as irony. The expectation for complex phenomena such as\nempathy and irony is that effective approaches require an interdisciplinary approach\nand, above all, the integration of representational models and data-oriented processing\ntechniques. The aim of this special section is to bring together leading research\non computational models of affect-related phenomena in interactions occurring either\nin social media or agent-based systems, by attaining cross-fertilization between two\nrelevant perspectives: on the one hand, research on agent architectures and cognitive models, mainly concerned with the integration of affective states into agents and open\nto the creation of virtual and embodied agents; on the other hand, research on techniques\nfor sentiment analysis and opinion mining, mainly focused on the processing\nof affective information in social media, typically (but not only) expressed through\ntext. The integration of models and methods between the two perspectives can open\nthe way to the development of a new generation of social and interactive applications\nthat leverage the affective dimension to promote improved, spontaneous technologymediated\ninteractions, including human¿computer and human¿human interactions,\non small and large scale.\nOur goal here is to provide an overview of the open research challenges for the\ncommunity of researchers interested in analyzing and modeling the interplay between\naffect and interaction in agent-based systems and social media, as well as an introduction\nto the special section. The rest of the article is structured as follows. Section 2\ndiscusses a set of research challenges relevant in the context of this special issue,\nSection 3 briefly introduces the articles included in this ACM TOIT special section.\nSection 4 concludes the article.

Abstract Learning can benefit from the modern Web structure through the convergence of top‐down encyclopedic institutional knowledge and bottom‐up user‐generated annotations. A promising approach to such convergence consists in leveraging the social functionalities in 3.0 executable environments through the recommendation of tags with the mediation of lexical and semantic resources. This paper addresses such issues through the design and evaluation of a tag recommendation system in a Web 3.0 Web portal, ‘150 Digit’. Designed for schools, 150 Digit encourages students and teachers to interact with a set of four exhibitions on the historical and social aspects of the Italian unification process in a virtual environment. The website displays the exhibits and their related documents promoting the users' active participation through tagging, voting and commenting on the exhibits. Tags become a way for students to create and explore new relations among the site contents, orthogonal to the institutional viewpoint. In this paper, we illustrate the recommendation strategy incorporated in 150 Digit, which relies on a semantic middleware to mediate between the input expressed by the users through tags and the top‐down institutional classification provided by the curators of the exhibitions. Following this, we describe the evaluation process conducted in a real experimental setting and discuss the evaluation results and their implications for learning environments.

In recent years, a number of projects have been undertaken for the access to cultural heritage that rely on metadata derived from an ontology. Ontologies also open to visualization techniques that leverage the structure of semantic relations to bridge the gap between the complexity of data and the need for immediate, simplified access. In this paper, we address the representation and access to the intangible cultural heritage, that has received much attention recently and typically lacks a physical counterpart. In order to illustrate this approach, we describe two case studies in ontologies and visualization for cultural heritage. In the first case study, the user is immersed in a 3D labyrinth where turning points and paths represent, respectively, a set of cultural artifacts and the semantic relations holding among them, the second case study relies on an ontology of contemporary art and a cartographic visualization of the public art in a city.

The representation of characters' intentions in a story is of great importance for media scholars and analysts, and it is susceptible of applicative scenarios within the media industry. In this paper, we introduce an interactive system for the visualization of a story analysis based on a plan-based representation of the characters' intentions. The system relies on an ontology of drama and builds upon the unrestricted annotation provided by narrative enthusiasts and media students. The system is able to build the mapping between a library of plans and the users' annotation, and to visualize the contributions of the several characters' intentions to the whole plot. The system was tested on the analysis of a short movie.

The coverage of the semantic gap in video indexing and retrieval has gone through a continuous increase of the vocabulary of high - level features or semantic descriptors, sometimes organized in light - scale, corpus - specific, computational ontologies. This paper presents a computer - supported manual annotation method that relies on a very large scale, shared, commonsense ontologies for the selection of semantic descriptors. The ontological terms are accessed through a linguistic interface that relies on multi - lingual dictionaries and action/event template structures (or frames). The manual generation or check of annotations provides ground truth data for evaluation purposes and training data for knowledge acquisition. The novelty of the approach relies on the use of widely shared large - scale ontologies, that prevent arbitrariness of annotation and favor interoperability. We test the viability of the approach by carrying out some user studies on the annotation of narrative videos.

In this paper, we describe a virtual interpreter of the Italian sign language (Italian Sign Language, LIS). developed as part of the on--going ATLAS project, on the automatic translation from Italian to Italian Sign Language. The translation system communicates with the user through a virtual signer: the system takes as input a formal representation of a sign language sentence and produces the corresponding animation of the avatar. The architecture of the virtual signer consists of a resource planner, an executor of the planned sign animations, and an animation system.

Recently, there has been much development in the annotation and automatic editing of video segments. The major issue has been the re-use of segments through a number of different editing processes. However, the annotation of the story progression through video segments has not received much attention. This paper presents an intelligent tool for narrative-based annotation and editing of video segments. The annotation schema relies on a formal theory for the annotation of story structure in video segments and on a juxtaposition engine for the automatic editing. The method has been implemented in a software programme that has been employed, in the re-use perspective, for artistic applications and, in the analysis perspective, for cross-medial comparison of stories.