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# Institut Politècnic d’Innovació i Recerca en Sostenibilitat (INSPIRES)

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INSPIRES és un centre de recerca de la Universitat de Lleida. Conforma un grup multidisciplinari que posa especial atenció a la recerca al voltant de la millor gestió energètica, l’eficiència, la usabilitat, la seguretat, la computació d’altes prestacions i la resolució i optimització de problemes, entre altres temes. Tot amb nexes comuns, girant al voltant de l’àmbit de la sostenibilitat i la tecnologia. Suposa una unió d’esforços dels diferents centres de recerca que de manera separada tractaven diferents línies i àrees, ara aquests esforços es comparteixen generant sinèrgies.[Més informació].

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### Browsing Institut Politècnic d’Innovació i Recerca en Sostenibilitat (INSPIRES) by Author "Alsinet, Teresa"

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- ItemOpen AccessA distributed argumentation algorithm for mining consistent opinions in weighted Twitter discussions(Springer, 2019) Alsinet, Teresa; Argelich Romà, Josep; Béjar Torres, Ramón; Cemeli Sánchez, Joel
Show more Twitter is one of the most powerful social media platforms, reflecting both support and contrary opinions among people who use it. In a recent work, we developed an argumentative approach for analyzing the major opinions accepted and rejected in Twitter discussions. A Twitter discussion is modeled as a weighted argumentation graph where each node denotes a tweet, each edge denotes a relationship between a pair of tweets of the discussion and each node is attached to a weight that denotes the social relevance of the corresponding tweet in the discussion. In the social network Twitter, a tweet always refers to previous tweets in the discussion, and therefore the underlying argument graph obtained is acyclic. However, when in a discussion we group the tweets by author, the graph that we obtain can contain cycles. Based on the structure of graphs, in this work we introduce a distributed algorithm to compute the set of globally accepted opinions of a Twitter discussion based on valued argumentation. To understand the usefulness of our distributed algorithm, we study cases of argumentation graphs that can be solved efficiently with it. Finally, we present an experimental investigation that shows that when solving acyclic argumentation graphs associated with Twitter discussions our algorithm scales at most with linear time with respect to the size of the discussion. For argumentation graphs with cycles, we study tractable cases and we analyze how frequent are these cases in Twitter. Moreover, for the non-tractable cases we analyze how close is the solution of the distributed algorithm with respect to the one computed with the general sequential algorithm, that we have previously developed, that solves any argumentation graph.Show more - ItemRestrictedA Max-SAT Solver with Lazy Data Structures(Springer Verlag, 2004) Alsinet, Teresa; Manyà Serres, Felip; Planes Cid, Jordi
Show more We present a new branch and bound algorithm for Max-SAT which incorporates original lazy data structures, a new variable selection heuristics and a lower bound of better quality. We provide experimental evidence that our solver outperforms some of the best performing Max- SAT solvers on a wide range of instances.Show more - ItemOpen AccessAn argumentative approach for discovering relevant opinions in Twitter with probabilistic valued relationships(Elsevier, 2017-07-08) Alsinet, Teresa; Argelich Romà, Josep; Béjar Torres, Ramón; Fernàndez Camon, César; Mateu Piñol, Carles; Planes Cid, Jordi
Show more Twitter is one of the most widely used social networks when it comes to sharing and criticizing relevant news and events. In order to understand the major opinions accepted and rejected in different domains by Twitter users, in a recent work we developed an analysis system based on valued abstract argumentation to model and reason about the social acceptance of tweets, considering different information sources from the social network. Given a Twitter discussion, the system outputs the set of accepted tweets from the discussion, considering two kinds of relationship between tweets: criticism and support. In this paper, we introduce and investigate a natural extension of the system, in which relationships between tweets are associated with a probability value, indicating the uncertainty that the relationships hold. An important element in our system is the notion of an uncertainty threshold, which characterizes how much uncertainty on probability values we are willing to tolerate: given an uncertainty threshold $\alpha$, we reject criticism and support relationships with probability below $\alpha$. We also extend our analysis system by incorporating support propagation when computing the social relevance of tweets. To this end, we extend the abstract argumentation framework with a new valuation function that propagates the support between tweets by taking into account not only the social relevance of tweets but also the probability that the support relationship holds, provided that it is above the specified uncertainty threshold $\alpha$. In order to test these new extensions, we analyze different Twitter discussions from the political domain. Our analysis shows that the social support of the accepted tweets is typically much stronger than the one for the rejected tweets. Also, the set of accepted tweets seems to be very stable with respect to changes to the social support of the tweets, and therefore even when considering support propagation we mainly observe differences in such set when using the more permissive probability thresholds.Show more - ItemOpen AccessApproximate and Optimal Solutions for the Bipartite Polarization Problem(IOS Press, 2022-10-17) Alsinet, Teresa; Argelich, Josep; Béjar Torres, Ramón; Martínez Rodríguez, Santi
Show more In a recent work we introduced a problem about finding the highest polarized bipartition on a weighted and labeled graph that represents a debate developed trough some social network, where nodes represent user’s opinions and edges agreement or disagreement between users. Finding this target bipartition is an optimization problem that can be seen as a generalization of the maxcut problem, so we first introduced a basic local search algorithm to find approximate solutions of the problem. In this paper we go one step further, and we present an exact algorithm for finding the optimal solution, based on an integer programming formulation, and compare the performance of a new variant of our local search algorithm with the exact algorithm. Our results show that at least on real instances of the problem, obtained from Reddit debates, the approximate solutions obtained are almost always identical to the optimal solutions.Show more - ItemRestrictedArgument-Based Expansion Operators in Possibilistic Defeasible Logic Programming: Characterization and Logical Properties(Springer Verlag, 2005) Chesñevar, Carlos Iván; Simari, Guillermo Ricardo; Godo i Lacasa, Lluís; Alsinet, Teresa
Show more Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty and fuzzy knowledge at object-language level. Defeasible argumentation in general and P-DeLP in particular provide a way of modelling non-monotonic inference. From a logical viewpoint, capturing defeasible inference relationships for modelling argument and warrant is particularly important, as well as the study of their logical properties. This paper analyzes two non-monotonic operators for P-DeLP which model the expansion of a given program P by adding new weighed facts associated with argument conclusions and warranted literals, resp. Different logical properties for the proposed expansion operators are studied and contrasted with a traditional SLD-based Horn logic. We will show that this analysis provides useful comparison criteria that can be extended and applied to other argumentation frameworksShow more - ItemRestrictedImproved Exact Solvers for Weighted Max-SAT(Springer Verlag, 2005) Alsinet, Teresa; Manyà Serres, Felip; Planes Cid, Jordi
Show more We present two new branch and bound weighted Max-SAT solvers (Lazy and Lazy ) which incorporate original data structures and inference rules, and a lower bound of better qualityShow more - ItemOpen AccessMeasuring Polarization in Online Debates(MDPI, 2021) Alsinet, Teresa; Argelich Romà, Josep; Béjar Torres, Ramón; Martínez Rodríguez, Santi
Show more Social networks can be a very successful tool to engage users to discuss relevant topics for society. However, there are also some dangers that are associated with them, such as the emergence of polarization in online discussions. Recently, there has been a growing interest to try to understand this phenomenon, as some consider that this can be harmful concerning the building of a healthy society in which citizens get used to polite discussions and even listening to opinions that may be different from theirs. In this work, we face the problem of defining a precise measure that can quantify in a meaningful way the level of polarization present in an online discussion. We focus on the Reddit social network, given that its primary focus is to foster discussions, in contrast to other social networks that have some other uses. Our measure is based on two different characteristics of an online discussion: the existence of a balanced bipartition of the users of the discussion, where one partition contains mainly users in agreement (regarding the topic of the discussion) and the other users in disagreement, and the degree of negativity of the sentiment of the interactions between these two groups of users. We discuss how different characteristics of the discussions affect the value of our polarization measure, and we finally perform an empirical evaluation over different sets of Reddit discussions about diverse classes of topics. Our results seem to indicate that our measure can capture differences in the polarization level of different discussions, which can be further understood when analyzing the values of the different factors used to define the measure.Show more - ItemOpen AccessMeasuring user relevance in online debates through an argumentative model(Elsevier, 2020) Alsinet, Teresa; Argelich Romà, Josep; Béjar Torres, Ramón; Martínez Rodríguez, Santi
Show more Online debating forums are important social media for people to voice their opinions and engage in debates with each other. Measuring user relevance on these forums can be useful to identify different user profiles or behaviors in online debates, for example, users that tend to participate at the beginning of a debate and whose comments trigger participation, or users that post relevant comments but are not replied too much. To help users to distinguish such different user profiles, we propose graded measures based on users’ influence, the controversy that they generate throughout the debates, their contribution to the polarization of the debates, and their social acceptance, that we extract by analyzing the debates in which the users participate. Our approach is based on an argumentation-based analysis that represents a debate as a valued argumentation framework, in which comments of a debate are arguments, the attack relation between arguments models disagreement between comments, and values for arguments represent the overall support of users for comments. Finally, we test our measures with a sample of users from Reddit debates, identifying four main groups of users, from users with almost no impact on the debate to very active ones with decisive comments for the outcome of the debate.Show more - ItemRestrictedMinimal and Redundant SAT Encodings for the All-Interval-Series Problem(Springer Verlag, 2002) Alsinet, Teresa; Béjar Torres, Ramón; Cabiscol i Teixidó, Alba; Fernàndez Camon, César; Manyà Serres, Felip
Show more The SAT encodings defined so far for the all-interval-series (ais) problem are very hard for local search but rather easy for systematic algorithms. We define different SAT encodings for the ais problem and provide experimental evidence that this problem can be efficiently solved with local search methods if one chooses a suitable SAT encoding.Show more - ItemRestrictedTowards an Automated Deduction System for First-Order Possibilistic Logic Programming with Fuzzy Constants(Wiley, 2002) Alsinet, Teresa; Godo i Lacasa, Lluís
Show more In this article, we present a first-order logic programming language for fuzzy reasoning under possibilistic uncertainty and poorly known information. Formulas are represented by a pair (ϕ, α), in which ϕ is a first-order Horn clause or a query with fuzzy constants and regular predicates, and α ∈ [0, 1] is a lower bound on the belief on ϕ in terms of necessity measures. Since fuzzy constants can occur in the logic component of formulas, the truth value of formulas is many-valued instead of Boolean. Moreover, since we have to reason about the possibilistic uncertainty of formulas with fuzzy constants, belief states are modeled by normalized possibility distributions on a set of many-valued interpretations. In this framework, (1) we define a syntax and a semantics of the underlying logic; (2) we give a sound modus ponens-style calculus by derivation based on a semantic unification pattern of fuzzy constants; (3) we develop a directional fuzzy unification algorithm based on the distinction between general and specific object constants; and (4) we describe a backward first-order proof procedure oriented to queries that is based on the calculus of the language and the computation of the unification degree between fuzzy constants in terms of a necessity measure for fuzzy events.Show more