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Technical University of Valencia, Spain

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29 Papers

Divergent Emotional Patterns in Disinformation on Social Media? An Analysis of Tweets and TikToks About the DANA in Valencia

Topics: Sentiment Analysis; Emotion Recognition; Emotions

Authors: Iván Arcos ¹ , Paolo Rosso ^{1

;

2} and Ramón Salaverría ³

Affiliations: ¹ PRHLT Research Center, Universitat Politècnica de València, Valencia, Spain , ² ValgrAI Valencian Graduate School and Research Network of Artificial Intelligence, Spain , ³ School of Communication, Universidad de Navarra, Pamplona, Spain

Digital Object Identifier: 10.5220/0013392800003890

Proceedings of EAA 2025, ISBN: 978-989-758-737-5

Quick Abstract

This study investigates the dissemination of disinformation on social media platforms during the DANA event (DANA is a Spanish acronym for Depresion Aislada en Niveles Altos ´ , translating to high-altitude isolated depression) that resulted in extremely heavy rainfall and devastating floods in Valencia, Spain, on October 29, 2024. We created a novel dataset of 650 TikTok and X posts, which was manually annotated to differentiate between disinformation and trustworthy content. Additionally, a Few-Shot annotation approach with GPT-4o achieved substantial agreement (Cohen’s kappa of 0.684) with manual labels. Emotion analysis revealed that disinformation on X is mainly associated with increased sadness and fear, while on TikTok, it correlates with higher levels of anger and disgust. Linguistic analysis using the LIWC dictionary showed that trustworthy content utilizes more articulate and factual language, whereas disinformation employs negations, perceptual words, and personal anecdotes to appear credible. Audio analysis of TikTok posts highlighted distinct patterns: trustworthy audios featured brighter tones and robotic or monotone narration, promoting clarity and credibility, while disinformation audios leveraged tonal variation, emotional depth, and manipulative musical elements to amplify engagement. In detection models, SVM+TF-IDF achieved the highest F1-Score, excelling with limited data. Incorporating audio features into roberta-large-bne improved both Accuracy and F1-Score, surpassing its text-only counterpart and SVM in Accuracy. GPT-4o Few-Shot also performed well, showcasing the potential of large language models for automated disinformation detection. These findings demonstrate the importance of leveraging both textual and audio features for improved disinformation detection on multimodal platforms like TikTok.

Towards a Model of Empathic Pedagogical Agent for Educating Children and Teenagers on Good Practices in the Use of Social Networks

Topics: Multi-Agent Systems; Agent Models and Architectures; Privacy, Safety and Security

Authors: Joaquín Taverner , Emilio Vivancos and Vicente Botti

Affiliation: Valencian Research Institute for Artificial Intelligence (VRAIN). Universitat Politècnica de València, Valencia, Spain

Digital Object Identifier: 10.5220/0010345504390445

Proceedings of ICAART 2021, ISBN: 978-989-758-484-8

Quick Abstract

Social networks have been a revolution for our society. The rapid expansion of these networks results in more and more children and teenagers using them regularly. However, despite the fact that most social networks have privacy control systems, most young people do not use these controls because teenagers are usually unaware of the privacy risks that exist in the Internet. This inadequate use of social media can lead to different social problems such as cyber-bullying, grooming, or sexting. The best way to prevent these risks is through education. In this paper we propose an empathic pedagogical agent model for education on good practices in the use of social networks. The agent interacts empathetically with users through the social network. The user’s emotion is recognized through a camera and is processed in real time to obtain the emotion. The agent analyzes the recognized emotion and the users’ actions and looks for the best strategy to advice and educate the teenager in the correct use of the social network.

Towards a Computational Approach to Emotion Elicitation in Affective Agents

Topics: Cognitive Systems; Simulation; Emotional Intelligence

Authors: Joaquín Taverner , Emilio Vivancos and Vicente Botti

Affiliation: Departamento de Sistemas Informááticos y Computación, Universitat Politècnica de València and Spain

Digital Object Identifier: 10.5220/0007579302750280

Proceedings of ICAART 2019, ISBN: 978-989-758-350-6

Quick Abstract

Interest in affective computing is increasing in recent years. Different emotional approaches have been developed to incorporate emotions in multi-agent systems. However, most of these models do not offer an adequate representation of emotions. An internal representation of emotions allows to define emotions according to different affective variables. In addition, many of these approaches do not take into account factors such as culture and language when defining emotions. In this work we show the results obtained in an experiment carried out to design an affective model for a multi-agent system taking into account factors such as language and culture.

Related Ontology Subjects/Areas/Topics (14)

Agents	Computational Intelligence	Operational Research
Artificial Intelligence	Enterprise Information Systems	Simulation
Bioinformatics	Evolutionary Computing	Soft Computing
Biomedical Engineering	Information Systems Analysis and Specification	Symbolic Systems
Cognitive Systems	Methodologies and Technologies

Modeling Personality in the Affective Agent Architecture GenIA3

Topics: Agent Models and Architectures; Programming Environments and Languages

Authors: Joaquin Taverner , Bexy Alfonso , Emilio Vivancos and Vicente Botti

Affiliation: Universitat Politècnica de València, Spain

Digital Object Identifier: 10.5220/0006597202360243

Proceedings of ICAART 2018, ISBN: 978-989-758-275-2

Quick Abstract

In the last few years there has been a growing interest in affective computing. This type of computation tries to include and use emotions in different software processes. One of the most relevant areas is the simulation of human behavior where various affective models are used to represent different affective characteristics such as emotions, mood, or personality. Personality is defined as a set of individual characteristics that influence motivations and behaviors when a human being faces a particular circumstance. Personality plays a very important role in modeling affective processes. Through the simulation of emotions we can improve, among others, the experience of users dealing with machines, and human simulations in decision-making processes using multi-agent systems. In this work we propose a model for the use of personality in the general purpose architecture for affective agents GenIA3, as well as the development of the model in the current GenIA3 platform.

Related Ontology Subjects/Areas/Topics (4)

Agent Models and Architectures		Artificial Intelligence		Programming Environments and Languages
Agents

Optimized 4D DPM for Pose Estimation on RGBD Channels using Polisphere Models

Topics: Object Detection and Localization; Event and Human Activity Recognition; Human and Computer Interaction

Authors: Enrique Martinez ¹ , Oliver Nina ² , Antonio J. Sánchez ¹ and Carlos Ricolfe ³

Affiliations: ¹ Universitat Politecnica de Valencia, Spain , ² University of Central Florida, United States , ³ Universitat Politecnica de València, Spain

Digital Object Identifier: 10.5220/0006133702810288

Proceedings of VISAPP 2017/VISIGRAPP, ISBN: 978-989-758-226-4

Quick Abstract

The Deformable Parts Model (DPM) is a standard method to perform human pose estimation on RGB images, 3 channels. Although there has been much work to improve such method, little work has been done on utilizing DPM on other types of imagery such as RGBD data. In this paper, we describe a formulation of the DPM model that makes use of depth information channels in order to improve joint detection and pose estimation using 4 channels. In order to offset the time complexity and overhead added to the model due to extra channels to process, we propose an optimization for the proposed algorithm based on solving direct and inverse kinematic equations, that form we can reduce the interested points reducing, at the same time, the time complexity. Our results show a significant improvement on pose estimation over the standard DPM model on our own RGBD dataset and on the public CAD60 dataset.

Related Ontology Subjects/Areas/Topics (5)

Applications and Services		Enterprise Information Systems		Human-Computer Interaction
Computer Vision, Visualization and Computer Graphics		Human and Computer Interaction

Integrating Expectations into Jason for Appraisal in Emotion Modeling

Topic: Artificial Life

Authors: Joaquín Taverner , Bexy Alfonso , Emilio Vivancos and Vicente Botti

Affiliation: Universitat Politècnica de València, Spain

Digital Object Identifier: 10.5220/0006070202310238

Proceedings of ECTA 2016/IJCCI, ISBN: 978-989-758-201-1

Quick Abstract

Emotions have a strong influence on human reasoning and behavior, thus, in order to build intelligent agents which simulate human behavior, it is necessary to consider emotions. Expectations are one of the bases for emotion generation through the appraisal process. In this work we have extended the Jason agent language and platform for handling expectations. Unlike other approaches focused on expectations handling, we have modified the agent reasoning cycle to manage expectations, avoiding complex additional mechanisms such as monitors. This tool is part of the GenIA³ architecture and, hence, is a step towards the standardization of the emotion modeling process in BDI (Beliefs-Desires-Intentions) agents.

Related Ontology Subjects/Areas/Topics (5)

Artificial Intelligence		Computational Intelligence		Soft Computing
Artificial Life		Evolutionary Computing

Building Emotional Agents for Strategic Decision Making

Topics: Multi-Agent Systems; Cognitive Systems; Agent Models and Architectures; Economic Agent Models

Authors: Bexy Alfonso ¹ , Emilio Vivancos ¹ , Vicente Botti ¹ and Penélope Hernández ²

Affiliations: ¹ Universitat Politècnica de València, Spain , ² Universidad de Valencia, Spain

Digital Object Identifier: 10.5220/0005204703900397

Proceedings of ICAART 2015, ISBN: 978-989-758-074-1

Quick Abstract

Experimental economics has many works that demonstrate the influence of emotions and affective issues on the process of human strategic decision making. Personality, emotions and mood produce biases on what would be considered the strategic solution (Nash equilibrium) to many games. %CAMBIO% Thus considering these issues on simulations of human behavior may produce results more aligned with real situations. We think that computational agents are a suitable %CAMBIO% technology to simulate such phenomena. We propose to use O3A, an Open Affective Agent Architecture to model rational and affective agents, in order to perform simulations where agents must take decisions as close as possible to humans. The approach evaluation is performed trough the classical `prisoner dilemma' and `trust' games.

Related Ontology Subjects/Areas/Topics (16)

Agent Models and Architectures	Distributed and Mobile Software Systems	Knowledge-Based Systems
Agents	Economic Agent Models	Multi-Agent Systems
Artificial Intelligence	Enterprise Information Systems	Soft Computing
Artificial Intelligence and Decision Support Systems	Evolutionary Computing	Software Engineering
Cognitive Systems	Knowledge Engineering and Ontology Development	Symbolic Systems
Computational Intelligence

MINERVA Project, mid- To near Infrared Spectroscopy for Improved Medical Diagnostics

Author: Valery Naranjo

Affiliation: Polytechnic University of Valencia, Spain

Digital Object Identifier: 10.5220/0006162400530069

Proceedings of EPS Lisbon 2015, ISBN: 978-989-758-095-6

Quick Abstract

The main idea behind the MINERVA project is the recognition that for the first time, through breakthroughs in photonic technology, it is possible to open the mid-IR electromagnetic spectrum (3-12 m) for rapid medical imaging. In particular this could greatly improve the chances of early cancer diagnosis. MINERVA will exploit and develop the advances in soft glass optical fibres, acousto-optic (AO) modulator design, crystal growth, fibre lasers, supercontinuum sources and detectors in the mid-IR. Two specific high impact applications will be addressed: high volume pathology screening (i.e. automated microscopebased examination of routine patient samples) and human skin surface examination (i.e. non-invasive investigation of suspected skin cancer). In an Integrating Project of this scale it is possible to pursue several targets in parallel, each of which alone brings significant benefits. Together they could begin a new branch of the bio-medical imaging industry.

Segmentation of LG Enhanced Cardiac MRI

Topics: Magnetic Resonance Imaging (MRI); Image Processing Methods

Authors: Kjersti Engan ¹ , Valery Naranjo ² , Trygve Eftestøl ¹ , Stein Ørn ³ and Leik Woie ⁴

Affiliations: ¹ University of Stavanger, Norway , ² Polytechnic University of Valencia, Spain , ³ Stavanger Universtiy Hospital, Norway , ⁴ Stavanger University Hospital, Norway

Digital Object Identifier: 10.5220/0005169200470055

Proceedings of BIOIMAGING 2015/BIOSTEC, ISBN: 978-989-758-072-7

Quick Abstract

In this paper a method for segmentation of the endocardium in Late Gadolinium Enhanced Cardiac Magnetic Resonance (LGE-CMR) images is presented and combined with a previously proposed method for segmentation of the epicardium. The method is fully automatic and based on utilizing a priori knowledge about the type of images. No other image modalities, like CINE images, are used. Using a combination of a rough a priori model and preprocessed images, an a posteriori model is built. The final segmentation step is performed in the polar domain. We compare our results on a set of 395 images from 54 patients with segmentation using marker controlled watershed with different gradient images and different markers. The proposed method gives a mean Dice and Jaccard indices over all images as 0.85 and 0.74 respectively.

Related Ontology Subjects/Areas/Topics (9)

Bioimaging	Cardiovascular Technologies	Magnetic Resonance Imaging
Biomedical Engineering	Health Engineering and Technology Applications	NeuroSensing and Diagnosis
Cardiovascular Imaging and Cardiography	Image Processing Methods	Neurotechnology, Electronics and Informatics

Studying the User Experience with a Multimodal Pedestrian Navigation Assistant

Topics: Augmented, Mixed and Virtual Environments; Advanced User Interfaces

Authors: Gustavo Rovelo ¹ , Francisco Abad ² , M. C.- Juan ² and Emilio Camahort ²

Affiliations: ¹ Hasselt University and Universitat Politècnica de València, Belgium , ² Universitat Politècnica de València, Spain

Digital Object Identifier: 10.5220/0005297504380445

Proceedings of GRAPP 2015/VISIGRAPP, ISBN: 978-989-758-087-1

Quick Abstract

The widespread usage of mobile devices together with their computational capabilities enables the implementation of novel interaction techniques to improve user performance in traditional mobile applications. Navigation assistance is an important area in the mobile domain, and probably Google Maps is the most popular example. This type of applications is highly demanding for user’s attention, especially in the visual channel. Tactile and auditory feedback have been studied as alternatives to visual feedback for navigation assistance to reduce this dependency. However, there is still room for improvement and more research is needed to understand, for example, how the three feedback modalities complement each other, especially with the appearance of new technology such as smart watches and new displays such as Google Glass. The goal of our work is to study how the users perceives multimodal feedback when their route is augmented with directional cues. Our results show that tactile guidance cues produced the worst user performance, both objectively and subjectively. Participants reported that vibration patterns were hard to decode. However, tactile feedback was an unobtrusive technique to inform participants when to look to the mobile screen or listen to the spoken directions. The results show that combining feedback modalities produces good user performance.

Related Ontology Subjects/Areas/Topics (4)

Advanced User Interfaces		Computer Vision, Visualization and Computer Graphics		Interactive Environments
Augmented, Mixed and Virtual Environments

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