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[EN] The concept of privacy in online social networks (OSNs) is a challenge, especially for teenagers. Previous works deal with teaching about privacy using educational online content, and media literacy. However, these tools do not necessarily promote less risky behaviors, and do not allow the assessment of users' behavior after the learning period. Moreover, few research studies about the effects of social gamification have been performed for this population segment (i.e., teenagers). To address this problem in this article, we propose the use of gamification in an OSN called Pesedia to facilitate the teaching/learning process, and assess its effectiveness in promoting suitable privacy behaviors. We tested our proposal comparing teenagers' performance in two editions of a course about social networks, and privacy (with, and without gamification) for one month. We measured the impact of gamification in the participants' behaviors toward privacy concepts as a consequence of the privacy teaching/learning process, and the participants' engagement in the educational process. The results show that there are significant differences in participants' behavior regarding privacy, and engagement in the gamified social network. Moreover, there is also a significant difference in participants' engagement for the gamified male participants. The gamified social network proposed in this article may be relevant, and useful for educators who wish to develop, and enhance teenagers' privacy skills, or for a broader base of aspects related to the development of digital competences, and technology in education. ; This work was supported in part by the Spanish Government Project TIN2017-89156-R, and in part by the FPI under Grant BFS-2015-074498. (Corresponding author: Elena Del Vol.) ; Alemany-Bordera, J.; Del Val, E.; García-Fornes, A. (2020). Assessing the Effectiveness of a Gamified Social Network for Applying Privacy Concepts: An Empirical Study with Teens. IEEE Transactions on Learning Technologies. 13(4):777-789. ...

[EN] The present work is a study of the detection of negative emotional states that people have using social network sites (SNSs), and the effect that this negative state has on the repercussions of posted messages. We aim to discover in which grade a user having an affective state considered negative by an Analyzer can affect other users and generate bad repercussions. Those Analyzers that we propose are a Sentiment Analyzer, a Stress Analyzer and a novel combined Analyzer. We also want to discover what Analyzer is more suitable to predict a bad future situation, and in what context. We designed a Multi-Agent System (MAS) that uses different Analyzers to protect or advise users. This MAS uses the trained and tested Analyzers to predict future bad situations in social media, which could be triggered by the actions of a user that has an emotional state considered negative. We conducted an experimentation with different datasets of text messages from Twitter.com to examine the ability of the system to predict bad repercussions, by comparing the polarity, stress level or combined value classification of the messages that are replies to the ones of the messages that originated them. ; This work was supported by the project TIN2017-89156-R of the Spanish government. ; Aguado-Sarrió, G.; Julian Inglada, VJ.; García-Fornes, A. (2018). Towards Aiding Decision-Making in Social Networks by Using Sentiment and Stress Combined Analysis. Information. 9(5):1-13. https://doi.org/10.3390/info9050107 ; S ; 1 ; 13 ; 9 ; 5

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. ; [EN] Argument mining is defined as the task of automatically identifying and extracting argumentative components (e.g., premises, claims, etc.) and detecting the existing relations among them (i.e., support, attack, rephrase, no relation). One of the main issues when approaching this problem is the lack of data, and the size of the publicly available corpora. In this work, we use the recently annotated US2016 debate corpus. US2016 is the largest existing argument annotated corpus, which allows exploring the benefits of the most recent advances in natural language processing in a complex domain like argument (relation) mining. We present an exhaustive analysis of the behavior of transformer-based models (i.e., BERT, XLNET, RoBERTa, DistilBERT, and ALBERT) when predicting argument relations. Finally, we evaluate the models in five different domains, with the objective of finding the less domain-dependent model. We obtain a macro F1-score of 0.70 with the US2016 evaluation corpus, and a macro F1-score of 0.61 with the Moral Maze cross-domain corpus. ; This work was supported in part by the Spanish Government project under Grant TIN2017-89,156-R, in part by the FPI under grant BES-2015-074,498, and in part by the Valencian Government project under Grant PROMETEO/2018/002. The authors gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan V GPUs used for this research. ; Ruiz-Dolz, R.; Alemany-Bordera, J.; Heras, S.; García-Fornes, A. (2021). Transformer-Based Models for Automatic Identification of Argument Relations: A Cross-Domain Evaluation. IEEE Intelligent Systems. 36(6):62-70. ...

[EN] Privacy has been a concern for humans long before the explosive growth of the Internet. The advances in information technologies have further increased these concerns. This is because the increasing power and sophistication of computer applications offers both tremendous opportunities for individuals, but also significant threats to personal privacy. Autonomous agents and multi-agent systems are examples of the level of sophistication of computer applications. Autonomous agents usually encapsulate personal information describing their principals, and therefore they play a crucial role in preserving privacy. Moreover, autonomous agents themselves can be used to increase the privacy of computer applications by taking advantage of the intrinsic features they provide, such as artificial intelligence, pro-activeness, autonomy, and the like. This article introduces the problem of preserving privacy in computer applications and its relation to autonomous agents and multi-agent systems. It also surveys privacy-related studies in the field of multi-agent systems and identifies open challenges to be addressed by future research. ; This work has been partially supported by CONSOLIDER-INGENIO 2010 under grant CSD2007-00022, and project TIN2011-27652-C03-00 of the Spanish Government. ; Such Aparicio, JM.; Espinosa Minguet, AR.; García-Fornes, A. (2014). A survey of privacy in multi-agent systems. The Knowledge Engineering Review. 29(3):314-344. doi:10.1017/S0269888913000180 ; S ; 314 ; 344 ; 29 ; 3

Electronic versíon of an article published as International Journal on Artificial Intelligent Tools, Volume 20, issue 2, 2011. 10.1142/S0218213011000152. © World Scientific Publishing Company ; [EN] An agent-based Virtual Organization is a complex entity where dynamic collections of agents agree to share resources in order to accomplish a global goal or offer a complex service. An important problem for the performance of the Virtual Organization is the distribution of the agents across the computational resources. The final distribution should provide a good load balancing for the organization. In this article, a genetic algorithm is applied to calculate a proper distribution across hosts in an agent-based Virtual Organization. Additionally, an abstract multi-agent system architecture which provides infrastructure for Virtual Organization distribution is introduced. The developed genetic solution employs an elitist crossover operator where one of the children inherits the most promising genetic material from the parents with higher probability. In order to validate the genetic proposal, the designed genetic algorithm has been successfully compared to several heuristics in different scenarios. © 2011 World Scientific Publishing Company. ; This work is supported by TIN2008-04446, TIN2009-13839-C03-01, CSD2007-00022 and FPU grant AP2008-00600 of the Spanish government, and PROMETEO 2008/051 of the Generalitat Valenciana. ; Sánchez Anguix, V.; Valero Cubas, S.; García Fornes, AM. (2011). A genetic approach for long term virtual organization distribution. International Journal on Artificial Intelligence Tools. 20(2):271-295. https://doi.org/10.1142/S0218213011000152 ; S ; 271 ; 295 ; 20 ; 2

[EN] The application of the latest Natural Language Processing breakthroughs in computational argumentation has shown promising results, which have raised the interest in this area of research. However, the available corpora with argumentative annotations are often limited to a very specific purpose or are not of adequate size to take advantage of state-of-the-art deep learning techniques (e.g., deep neural networks). In this paper, we present VivesDebate, a large, richly annotated and versatile professional debate corpus for computational argumentation research. The corpus has been created from 29 transcripts of a debate tournament in Catalan and has been machine-translated into Spanish and English. The annotation contains argumentative propositions, argumentative relations, debate interactions and professional evaluations of the arguments and argumentation. The presented corpus can be useful for research on a heterogeneous set of computational argumentation underlying tasks such as Argument Mining, Argument Analysis, Argument Evaluation or Argument Generation, among others. All this makes VivesDebate a valuable resource for computational argumentation research within the context of massive corpora aimed at Natural Language Processing tasks. ; This research was funded by the Spanish Government project PID2020-113416RB-I00; the Valencian Government project PROMETEO/2018/002; the MISMIS-Language project (PGC2018096212-B-C33) funded by Ministerio de Ciencia, Innovacion y Universidades; and the CLiC Research Group (2017SGR341) funded by Generalitat de Catalunya. ; Ruiz-Dolz, R.; Montserrat Nofre; Mariona Taulé; Heras, S.; García-Fornes, A. (2021). VivesDebate: A New Annotated Multilingual Corpus of Argumentation in a Debate Tournament. Applied Sciences. 11(15):1-20. https://doi.org/10.3390/app11157160 ; S ; 1 ; 20 ; 11 ; 15

[EN] In this article we study the impact of the negotiation environment on the performance of several intra-team strategies (team dynamics) for agent-based negotiation teams that negotiate with an opponent. An agent-based negotiation team is a group of agents that joins together as a party because they share common interests in the negotiation at hand. It is experimentally shown how negotiation environment conditions like the deadline of both parties, the concession speed of the opponent, similarity among team members, and team size affect performance metrics like the minimum utility of team members, the average utility of team members, and the number of negotiation rounds. Our goal is identifying which intra-team strategies work better in different environmental conditions in order to provide useful knowledge for team members to select appropriate intra-team strategies according to environmental conditions. ; This work is supported by TIN2011-27652-C03-01, TIN2009-13839-C03-01, CSD2007-00022 of the Spanish Government, and FPU Grant AP2008-00600 awarded to Victor Sanchez-Anguix. We would also like to thank anonymous reviewers and assistants of AAMAS 2011 who helped us to improve our previous work, making this present work possible. ; Sanchez-Anguix, V.; Julian Inglada, VJ.; Botti, V.; García-Fornes, A. (2013). Studying the impact of negotiation environments on negotiation teams' performance. Information Sciences. 219:17-40. https://doi.org/10.1016/j.ins.2012.07.017 ; S ; 17 ; 40 ; 219

[EN] In this article, an agent-based negotiation model for negotiation teams that negotiate a deal with an opponent is presented. Agent-based negotiation teams are groups of agents that join together as a single negotiation party because they share an interest that is related to the negotiation process. The model relies on a trusted mediator that coordinates and helps team members in the decisions that they have to take during the negotiation process: which offer is sent to the opponent, and whether the offers received from the opponent are accepted. The main strength of the proposed negotiation model is the fact that it guarantees unanimity within team decisions since decisions report a utility to team members that is greater than or equal to their aspiration levels at each negotiation round. This work analyzes how unanimous decisions are taken within the team and the robustness of the model against different types of manipulations. An empirical evaluation is also performed to study the impact of the different parameters of the model. ; This work is supported by TIN2008-04446, PROMETEO/2008/051, TIN2009-13839-C03-01, CSD2007-00022 of the Spanish government, and FPU Grant AP2008-00600 awarded to Victor Sanchez-Anguix. This paper was recommended by Associate Editor X. Wang. ; Sanchez-Anguix, V.; Julian Inglada, VJ.; Botti, V.; García-Fornes, A. (2012). Reaching unanimous agreements within agent-based negotiation teams with linear and monotonic utility functions. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics. 42(3):778-792. https://doi.org/10.1109/TSMCB.2011.2177658 ; S ; 778 ; 792 ; 42 ; 3

This paper describes a scheduling algorithm that composes a scheduling plan which is able to predict the completion time of the arriving tasks. This is done by performing CPU booking. This prediction is used to establish a temporal commitment with the client that invokes the execution of the task. This kind of scheduler is very useful in scenarios where Service-Oriented Computing is deployed and the execution time is used as a parameter for QoS. This scheduler is part of an architecture that is based on the Distributed Goal-Oriented Computing paradigm, which allows agents to express their own goals and to reach them by means of service compositions. Moreover, the scheduler is also able to prioritize those tasks which provide greater benefits to the OS. In this work, the scheduler has been designed in several iterations and tested by means of a set of experiments that compare the scheduler algorithm with a representative set of scheduling algorithms. © 2012 Elsevier B.V. All rights reserved. ; This work is supported by the TIN2009-13839-C03-01 project of the Spanish government, PROMETEO/2008/051 project, FEDER funds and CONSOLIDER-INGENIO 2010 under grant CSD2007-00022. ; Palanca Cámara, J.; Navarro Llácer, M.; García-Fornes, A.; Julian Inglada, VJ. (2013). Deadline Prediction Scheduling based on Benefits. Future Generation Computer Systems. 29(1):61-73. https://doi.org/10.1016/j.future.2012.05.007 ; S ; 61 ; 73 ; 29 ; 1

For current computing frameworks, the ability to dynamically use the resources that are allocated in the network has become a key success factor. As long as the size of the network increases, it is more difficult to find how to solve the problems that the users are presenting. Users usually do know what they want to do, but they do not know how to do it. If the user knows its goals it could be easier to help him with a different approach. In this work we present a new computing paradigm based on goals. This paradigm is called Distributed goal-oriented computing paradigm. To implement this paradigm an execution framework for a goal-oriented operating system has been designed. In this paradigm users express their goals and the OS is in charge of helping the achievement of these goals by means of a service-oriented approach. © 2012 Elsevier Inc. All rights reserved. ; This work is supported by TIN2008-04446 and TIN2009-13839-C03-01 projects of the Spanish Government, PROMETEO/2008/051 project, FEDER funds and CONSOLIDER-INGENIO 2010 under grant CSD2007-00022. ; Palanca Cámara, J.; Navarro Llácer, M.; Julian Inglada, VJ.; García-Fornes, A. (2012). Distributed goal-oriented computing. Journal of Systems and Software. 85(7):1540-1557. https://doi.org/10.1016/j.jss.2012.01.045 ; S ; 1540 ; 1557 ; 85 ; 7

Social knowledge is one of the key aspects of MAS in order to face complex problems in dynamical environments. However, it is usually incorporated without specific support on behalf of the platform and that does not let agents take all of the advantage of this social knowledge. At present time, the authors of this paper are working in a general tracing system, which could be used by agents in the system to trace other agents' activity and that could be used as an alternative way for agents to perceive their environment. This paper presents first results of this work, consisting of the requirements which should be taken into account when designing such a tracing system. ; This work is partially supported by projects PROMETEO/2008/051, CSD2007-022 and TIN2008-04446, which is co-funded by the Spanish government and FEDER funds.

[EN] Nowadays there is a strong integration of online social platforms and applications with our daily life. Such interactions can make risks arise and compromise the information we share, thereby leading to privacy issues. In this work, a proposal that makes use of a software agent that performs sentiment analysis and another performing stress analysis on keystroke dynamics data has been designed and implemented. The proposal consists of a set of new agents that have been integrated into a multi-agent system (MAS) for guiding users interacting in online social environments, which has agents for sentiment and stress analysis on text. We propose a combined analysis using the different agents. The MAS analyzes the states of the users when they are interacting, and warns them if the messages they write are deemed negative. In this way, we aim to prevent potential negative outcomes on social network sites (SNSs). We performed experiments in the laboratory with our private SNS Pesedia over a period of one month, so we gathered data about text messages and keystroke dynamics data, and used the datasets to train the artificial neural networks (ANNs) of the agents. A set of experiments was performed for discovering which analysis is able to detect a state of the user that propagates more in the SNS, so it may be more informative for the MAS. Our study will help develop future intelligent systems that utilize user data in online social environments for guiding or helping them in their social experience. ; This work was funded by the project TIN2017-89156-R of the Spanish government. ; Aguado-Sarrió, G.; Julian Inglada, VJ.; García-Fornes, A.; Espinosa Minguet, AR. (2020). Using Keystroke Dynamics in a Multi-Agent System for User Guiding in Online Social Networks. Applied Sciences. 10(11):1-20. https://doi.org/10.3390/app10113754 ; S ; 1 ; 20 ; 10 ; 11 ; O'Keeffe, G. S., & Clarke-Pearson, K. (2011). The Impact of Social Media on Children, Adolescents, and Families. PEDIATRICS, 127(4), 800-804. ...

[EN] In the current world we live immersed in online applications, being one of the most present of them Social Network Sites (SNSs), and different issues arise from this interaction. Therefore, there is a need for research that addresses the potential issues born from the increasing user interaction when navigating. For this reason, in this survey we explore works in the line of prevention of risks that can arise from social interaction in online environments, focusing on works using Multi-Agent System (MAS) technologies. For being able to assess what techniques are available for prevention, works in the detection of sentiment polarity and stress levels of users in SNSs will be reviewed. We review with special attention works using MAS technologies for user recommendation and guiding. Through the analysis of previous approaches on detection of the user state and risk prevention in SNSs we elaborate potential future lines of work that might lead to future applications where users can navigate and interact between each other in a more safe way. ; This work was funded by the project TIN2017-89156-R of the Spanish government. ; Aguado-Sarrió, G.; Julian Inglada, VJ.; García-Fornes, A.; Espinosa Minguet, AR. (2020). A Review on MAS-Based Sentiment and Stress Analysis User-Guiding and Risk-Prevention Systems in Social Network Analysis. Applied Sciences. 10(19):1-29. https://doi.org/10.3390/app10196746 ; S ; 1 ; 29 ; 10 ; 19 ; Vanderhoven, E., Schellens, T., Vanderlinde, R., & Valcke, M. (2015). Developing educational materials about risks on social network sites: a design based research approach. Educational Technology Research and Development, 64(3), 459-480. doi:10.1007/s11423-015-9415-4 ; Teens and ICT: Risks and Opportunities. Belgium: TIRO http://www.belspo.be/belspo/fedra/proj.asp?l=en&COD=TA/00/08 ; Risks and Safety on the Internet: The Perspective of European Children: Full Findings and Policy Implications From the EU Kids Online Survey of 9–16 Year Olds and Their Parents in 25 Countries ...

[EN] The present work is a study of the detection of negative affective or emotional states, the high-stress levels that people have using social network sites (SNSs), and the effect that this negative state or stress level has on the repercussions of posted messages. We aim to discover to what extent a user that has a state detected as negative by an analyzer (Sentiment analyzer and Stress analyzer) can affect other users and generate negative repercussions, and also determine whether it is more suitable to predict a future negative situation using different analyzers. We propose two different methods for creating a combined model of sentiment and stress, and we use them in our experimentation to discern which one is more suitable for predicting future negative situations that could arise from the interaction between users, and in what context. Additionally, we designed a Multi-Agent System (MAS) that integrates the analyzers to protect or advise users on a SNS. We have conducted this study to help build future systems that prevent negative situations where a user that has a negative state creates a repercussion in the SNS. This can help users avoid getting into a bad mood or help avoid privacy issues (e.g. a user that has a negative state posting information that the user does not really want to post). ; This work was supported by the project TIN2017-89156-R of the Ministry of Economy, Industry and Competitiveness, Government of Spain. ; Aguado-Sarrió, G.; Julian Inglada, VJ.; García-Fornes, A.; Espinosa Minguet, AR. (2020). A Multi-Agent System for guiding users in on-line social environments. Engineering Applications of Artificial Intelligence. 94:1-14. https://doi.org/10.1016/j.engappai.2020.103740 ; S ; 1 ; 14 ; 94 ; Aguado, G., Julian, V., & Garcia-Fornes, A. (2018). Towards Aiding Decision-Making in Social Networks by Using Sentiment and Stress Combined Analysis. Information, 9(5), 107. doi:10.3390/info9050107 ; Alrubaian, M., Al-Qurishi, M., Alamri, A., Al-Rakhami, M., Hassan, M. M., & Fortino, ...

(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. ; [EN] Privacy risk in Online Social Networks has become an important social concern. Users, with different perceptions of risk, share information without considering the audience that has access to the information disclosed or how far a publication will go. According to this, we propose two metrics (Audience and Reachability) based on information flows and friendship layers that indicate the privacy risk of sharing information, addressing the posts¿ scope and invisible audience. We assess these metrics through agent simulations in well-known models of networks. The findings show a strong relationship between metrics and structural centrality network properties. We also studied scenarios where there is no previous information about users activity or the information about the traces of the messages cannot be obtained. To deal with privacy assessment in these scenarios, we analyze the relationship between the proposed privacy metrics and local centrality properties as an estimation of privacy risk. The results showed that effectiveness centrality can be used as a suitable approximation of the proposed privacy measures. ; This work was supported in part by the Spanish Government project under Grant TIN2017-89156-R, and in part by the FPI under Grant BES-2015-074498. ; Alemany-Bordera, J.; Del Val Noguera, E.; Alberola Oltra, JM.; García-Fornes, A. (2019). Metrics for privacy assessment when sharing information in online social networks. IEEE Access. 7:143631-143645. https://doi.org/10.1109/ACCESS.2019.2944723 ; S ; 143631 ; 143645 ; 7