Semantic Flooding: Semantic Search across Distributed Lightweight Ontologies

Lightweight ontologies are trees where links between nodes codify the fact that a node lower in the hierarchy describes a topic (and contains documents about this topic) which is more specific than the topic of the node one level above. In turn, multiple lightweight ontologies can be connected by semantic links which represent mappings among them and which can be computed, e.g., by ontology matching. In this paper we describe how these two types of links can be used to define a semantic overlay network which can cover any number of peers and which can be flooded to perform a semantic search on documents, i.e., to perform semantic flooding. We have evaluated our approach by simulating a network of 10,000 peers containing classifications which are fragments of the DMoz web directory. The results are promising and show that, in our approach, only a relatively small number of peers needs to be queried in order to achieve high accuracy

Social Interactions Mediated by the Internet and the Big- Five: a Cross-Country Analysis

This study analyzes the possible relationship between personality traits, in terms of Big Five (extraversion, agreeableness, responsibility, emotional stability and openness to experience), and social interactions mediated by digital platforms in different socioeconomic and cultural contexts. We considered data from a questionnaire and the experience of using a chatbot, as a mean of requesting and offering help, with students from 4 universities: University of Trento (Italy), the National University of Mongolia, the School of Economics of London (United Kingdom) and the Universidad Cat\'olica Nuestra Se\~nora de la Asunci\'on (Paraguay). The main findings confirm that personality traits may influence social interactions and active participation in groups. Therefore, they should be taken into account to enrich the recommendation of matching algorithms between people who ask for help and people who could respond not only on the basis of their knowledge and skills.Comment: 5 page

Social interactions mediated by the Internet and the Big-Five: a cross-country analysis

This study analyzes the possible relationship between personality traits, in terms of Big Five (extraversion, agreeableness, responsibility, emotional stability and openness to experience), and social interactions mediated by digital platforms in different socioeconomic and cultural contexts. We considered data from a questionnaire and the experience of using a chatbot, as a mean of requesting and offering help, with students from 4 universities: University of Trento (Italy), the National University of Mongolia, the School of Economics of London (United Kingdom) and the Universidad Cat\'olica Nuestra Se\~nora de la Asunci\'on (Paraguay). The main findings confirm that personality traits may influence social interactions and active participation in groups. Therefore, they should be taken into account to enrich the recommendation of matching algorithms between people who ask for help and people who could respond not only on the basis of their knowledge and skills.Comment: Diversity-aware Hybrid Human-Artificial Intelligence (DHHAI)2023 workshop, 5 page

SOS TUTORIA UC: A Diversity-Aware Application for Tutor Recommendation Based on Competence and Personality

SOS TUTORIA UC is a student connection application aimed at facilitating academic assistance between students through external tutoring outside of the application. To achieve this, a responsive web application was designed and implemented, integrated with the WeNet platform, which provides various services for user management and user recommendation algorithms. This study presents the development and validation of the experience in the application by evaluating the importance of incorporating the dimension of personality traits, according to the Big Five model, in the process of recommending students for academic tutoring. The goal is to provide support for students to find others with greater knowledge and with a personality that is \'different\', \'similar\' or \'indifferent\' to their own preferences for receiving academic assistance on a specific topic. The integration with the WeNet platform was successful in terms of components, and the results of the recommendation system testing were positive but have room for improvement.Comment: 5 page

Diversity and Neocolonialism in Big Data Research. Avoiding extractivism while struggling with paternalism.

The extractive logic of Big Data-driven technology and knowledge production has raised serious concerns. While most criticism initially focused on the impacts on Western societies, attention is now increasingly turning to the consequences for communities in the Global South. To date, debates have focused on private-sector activities. In this article, we start from the conviction that publicly funded knowledge and technology production must also be scrutinized for their potential neocolonial entanglements. To this end, we analyze the dynamics of collaboration in an European Union-funded research project that collects data for developing a social platform focused on diversity. The project includes pilot sites in China, Denmark, the United Kingdom, India, Italy, Mexico, Mongolia, and Paraguay. We present the experience at four field sites and reflect on the project’s initial conception, our collaboration, challenges, progress, and results. We then analyze the different experiences in comparison. We conclude that while we have succeeded in finding viable strategies to avoid contributing to the dynamics of unilateral data extraction as one side of the neocolonial circle, it has been infinitely more difficult to break through the much more subtle but no less powerful mechanisms of paternalism that we find to be prevalent in data-driven North–South relations. These mechanisms, however, can be identified as the other side of the neocolonial circle.</p

Analysis of the Big-Five personality traits in the Chatbot "UC - Paraguay"

In the context of the project "WeNet: Internet of us" we are studying the role of diversity in relation to Internet-mediated social interactions. In this paper, in particular, we analyze a possible relationship between personality aspects and social interaction mediated by digital platforms. More specifically, we rely on the five personality traits (Extraversion, Agreeableness, Conscientiousness, Emotional Stability and Openness to Experience), commonly referred to as "Big-five", and associate them to automatically extracted behavioral characteristics derived from the experience of using a Chatbot for a closed community of students at the Universidad Católica "Nuestra Señora de la Asunci´ón" (UC). The personality data comes from a self-report made by the users through questionnaires. According to a survey to the participants, overall the results show very positive appraisals about the use of the Chatbot in terms of user experience and its main functionalities, which is very encouraging for future pilots. As for the role of personality in relation to the main use of the Chatbot, although further experience is required to confirm trends, the results suggest that the Big-five personality traits are to some extent correlated with: the active participation (Agreeableness and Openess); the type of contribution in term of length of questions/requests for help and answers (Agreeableness, Neuroticism and Openness); and, the network of interactions evolution over time (Openness and Neuroticism)

Privacy for Peer Profiling in Collective Adaptive Systems

Part 5: Project Workshops and Tutorial PapersInternational audienceIn this paper, we introduce a privacy-enhanced Peer Manager, which is a fundamental building block for the implementation of a privacy-preserving collective adaptive systems computing platform. The Peer Manager is a user-centered identity management platform that keeps information owned by a user private and is built upon an attribute-based privacy policy. Furthermore, this paper explores the ethical, privacy and social values aspects of collective adaptive systems and their extensive capacity to transform lives. We discuss the privacy, social and ethical issues around profiles and present their legal privacy requirements from the European legislation perspective

Distributed Entity Search

Capturing information about entities of the real world (i.e. locations, people, institutions and others) is a goal that is gaining more attention in today’s web of data. We believe that this capturing would only be possible if users can contribute and interact as they do in the real world. The contribution and interaction of users may take place over a distributed network where they can publish information about known entities. We think that the contribution of users will not happen, if the network can not be considered also as a source of information for them. Therefore, this PHD thesis aims to address the problem of finding entities (i.e. information about entities) that are related to the information needs of the user, in order to consolidate a web of data, which is based on entities. These entities need to be found from a collection, which can be distributed and where each entity can be described from the points of view of different users. In this proposal we analyze different layers of abstractions in the context of an entity-centric application, which allow users to define and share their entities. Then, we describe the problem of entity search in a distributed environment considering the different abstraction layers. We end with a discussion of possible approaches for the solution, where a network architecture for the search is proposed

Distributed Name-based Entity Search

Internet can be seen as a network of peers that store digital representations of entities from the real world (e.g., person, locations, events). Different peers locally represent different “versions” (i.e., different points of view) of the same real world entity. In these different versions, entities are normally identified by multiple (possibly different) names. We propose a distributed entity search based on names that aims to (i) find all the different versions of an entity starting from any name used somewhere in the network to identify such entity; and (ii) allow peers to have full control over the privacy of their local representations. We evaluate our approach by setting up a network of 150 peers on Plan- etLab. The results show that the performance of our algorithms is stable with the network growth, which is promising in terms of scalability