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Atkinson, J., & Escudero, A. (2022). Evolutionary natural-language coreference resolution for sentiment analysis. Int. J. Inf. Manage. Data Insights, 2(2), 100115.
Abstract: Communicating messages on social media usually conveys much implicit linguistic knowledge, which makes it difficult to process texts for further analysis. One of the major problems, the linguistic coreference resolution task involves detecting coreference chains of entities and pronouns that coreference them. It has mostly been addressed for formal and full-sized text in which a relatively clear discourse structure can be discovered, using Natural-Language Processing techniques. However, texts in social media are short, informal and lack a lot of underlying linguistic information to make decisions so traditional methods can not be applied. Furthermore, this may significantly impact the performance of several tasks on social media applications such as opinion mining, network analysis, sentiment analysis, text categorization. In order to deal with these issues, this research address the task of linguistic co-referencing using an evolutionary computation approach. It combines discourse coreference analysis techniques, domain-based heuristics (i.e., syntactic, semantic and world knowledge), graph representation methods, and evolutionary computation algorithms to resolving implicit co-referencing within informal opinion texts. Experiments were conducted to assess the ability of the model to find implicit referents on informal messages, showing the promise of our approach when compared to related methods.
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Canals, C., Maroulis, S., Canessa, E., Chaigneau, S., & Mizala, A. (2022). Mechanisms Underlying Choice-Set Formation: The Case of School Choice in Chile. Soc. Sci. Comput. Rev., Early Access.
Abstract: Many decisions involve selecting among many more options than an individual can effectively examine and consider. Therefore, people usually consider smaller and different “choice sets” as viable options. To better understand the processes affecting choice-set formation, we developed a computational model of how households become aware of potential choices in a context for which understanding household decision-making has important public policy implications: market-based reforms in education. In the model, households learn about the schools to which they can send their children through three mechanisms: find out about geographically proximate schools, access to publicly available information, and information gathered from interactions with other households. We calibrated the model using data from four cities in Chile, where students are not required to attend their neighborhood school. We then used the model to conduct hypothetical computational experiments that assessed how each mechanism impacted the sets of schools known to households before they make their choice (their “awareness set”). We found that the inclusion of a social interaction mechanism was crucial for producing simulated awareness sets that matched the awareness sets provided in a survey conducted by the Chilean Ministry of Education. We also found that the social interaction mechanism played the largest role in determining the quality and price range of the choices available in households’ awareness sets. Our findings highlight the importance of social interactions in a stage of decision-making before the direct impact of other individuals is typically made explicit. Moreover, it validates an approach that can be used in future models where understanding how decision-makers become aware of their options may be as important as the way they choose among them.
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Carrasco, J. A., & Yanez, R. (2022). Sequential search and firm prominence. Econ. Theory, 74(1), 209–233.
Abstract: We explore the role of prominence in equilibrium pricing in markets where search is sequential and random. Our model key feature is that more prominent firms are more likely to be sampled first. In contrast to ordered-search models, we find that more prominent firms inherit larger but less elastic demands, and as such have incentives to post larger prices. However, they might post lower prices but still charge higher markups than less prominent competitors only if they are also sufficiently more efficient. Our results suggest that when search is sequential, the role of prominence depends on whether it modifies the order or just the chances with which firms are sampled.
Keywords: EQUILIBRIUM PRICE DISPERSION; CONSUMER SEARCH; INFORMATION; ECONOMICS; MODEL
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Liu, S. Z., Leiva, V., Ma, T. F., & Welsh, A. (2016). Influence diagnostic analysis in the possibly heteroskedastic linear model with exact restrictions. Stat. Method. Appl., 25(2), 227–249.
Abstract: The local influence method has proven to be a useful and powerful tool for detecting influential observations on the estimation of model parameters. This method has been widely applied in different studies related to econometric and statistical modelling. We propose a methodology based on the Lagrange multiplier method with a linear penalty function to assess local influence in the possibly heteroskedastic linear regression model with exact restrictions. The restricted maximum likelihood estimators and information matrices are presented for the postulated model. Several perturbation schemes for the local influence method are investigated to identify potentially influential observations. Three real-world examples are included to illustrate and validate our methodology.
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Moreno, S., Bórquez-Paredes, D., & Martínez, V. (2023). Analysis of the Characteristics and Speed of Spread of the 'FUNA' on Twitter. Mathematics, 11(7), 1749.
Abstract: The funa is a prevalent concept in Chile that aims to expose a persons bad behavior, punish the aggressor publicly, and warn the community about it. Despite its massive use on the social networks of Chilean society, the real dissemination of funas among communities is unknown. In this paper, we extract, generate, analyze, and compare the Twitter social networks spread of three tweets related to �funas� against three other trending topics, through the analysis of global network characteristics over time (degree distribution, clustering coefficient, hop plot, and betweenness centrality). As observed, funas have a specific behavior, and they disseminate as quickly as a common tweet or more quickly; however, they spread thanks to several network users, generating a cohesive group.
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Munoz-Herrera, S., & Suchan, K. (2022). Constrained Fitness Landscape Analysis of Capacitated Vehicle Routing Problems. Entropy, 24(1), 53.
Abstract: Vehicle Routing Problems (VRP) comprise many variants obtained by adding to the original problem constraints representing diverse system characteristics. Different variants are widely studied in the literature; however, the impact that these constraints have on the structure of the search space associated with the problem is unknown, and so is their influence on the performance of search algorithms used to solve it. This article explores how assignation constraints (such as a limited vehicle capacity) impact VRP by disturbing the network structure defined by the solution space and the local operators in use. This research focuses on Fitness Landscape Analysis for the multiple Traveling Salesman Problem (m-TSP) and Capacitated VRP (CVRP). We propose a new Fitness Landscape Analysis measure that provides valuable information to characterize the fitness landscape's structure under specific scenarios and obtain several relationships between the fitness landscape's structure and the algorithmic performance.
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Rapaport, I., Suchan, K., Todinca, I., & Verstraete, J. (2011). On Dissemination Thresholds in Regular and Irregular Graph Classes. Algorithmica, 59(1), 16–34.
Abstract: We investigate the natural situation of the dissemination of information on various graph classes starting with a random set of informed vertices called active. Initially active vertices are chosen independently with probability p, and at any stage in the process, a vertex becomes active if the majority of its neighbours are active, and thereafter never changes its state. This process is a particular case of bootstrap percolation. We show that in any cubic graph, with high probability, the information will not spread to all vertices in the graph if p < 1/2. We give families of graphs in which information spreads to all vertices with high probability for relatively small values of p.
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Rodriguez, R., Negrete-Pincetic, M., Lorca, A., Olivares, D., & Figueroa, N. (2021). The value of aggregators in local electricity markets: A game theory based comparative analysis. SEGAN, 27, 100498.
Abstract: Demand aggregators are expected to have a key role in future electricity systems. More specifically, aggregators can facilitate the harnessing of consumers' flexibility. This paper focuses on understanding the value of the aggregator in terms of aggregation of both flexibility and information. We consider the aggregation of flexibility as the ability to exercise a direct control over loads, while the aggregation of information refers to knowledge of the flexibility characteristics of the consumers. Several game theory formulations are used to model the interaction between the energy provider, consumers and the aggregator, each with a different information structure. We develop a potential game to obtain the Nash equilibrium of the non-cooperative game with complete information and we analyze the system dynamics of consumers using the adaptive expectations method in an incomplete information scenario. Several key insights about the value of aggregators are found. In particular, the value of the aggregator is mainly related to the aggregation of information rather than flexibility, and flexibility is valuable only when it can be coordinated. In this sense, prices are not enough to guarantee an effective coordination.
Keywords: Information; Flexibility; Potential game; Adaptive expectations method
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Salazar, O., Casanova, M., Fuentes, J. P., Galleguillos, M., Najera, F., Perez-Quezada, J., et al. (2022). Soil research, management, and policy priorities in Chile. Geoderma Reg., 29, e00502.
Abstract: Soils of Chile
Given the diversity of soil types in Chile, soil scientists face complex challenges to prioritize across different regions. Chile is located at the southwestern extreme of South America and is characterized by its well-marked latitudinal climate segmentation along 4300 km from 18◦ S to 56◦ S, spanning diverse transversal geomorphologic units across a narrow 180-km wide landscape from the Andes mountains, Andean foothills, Central Valley, and Coastal Range to the coastal plains. Chilean soils formed in geographic isolation flanked by the Pacific Ocean, Atacama Desert and the Andes mountains (Casanova et al., 2013). From the extreme hyperarid north to central Mediterranean Chile, Aridisols and Entisols dominate, with Histosols in only a few areas of the northern Altiplano highlands. Residual and colluvial soils coexist with soils derived from volcanic ashes, which in the temperate and rainy southcentral Chile allow Andisols to develop. Alluvial, glacial and fluvioglacial soils occur primarily along the Central Valley and southern Patagonia plains. The southern volcanic zones of the Andes influence central-southern Chile, which is dominated from 35◦ S to 49◦ S by soils derived from volcanic ashes, mainly Andisols and Ultisols, where about 70% of agricultural activities are carried out. All remaining Soil Taxonomy Orders are also found, except Oxisols. Quantitative and qualitative anthropogenic soil degradation due to land use change and agricultural management has been an old and serious problem in Chile as far back as the mid-eighteenth century, with adverse impacts on agricultural productivity, rural livelihoods, biodiversity, and on food security in some places. Numerous connections to local and global environmental problems such as climate change and ongoing drought call for action-oriented science to inform management and decision making. We identified five soil priorities of particular importance in Chile. |
Villena, M. G., & Zecchetto, F. (2011). Subject-specific performance information can worsen the tragedy of the commons: Experimental evidence. J. Econ. Psychol., 32(3), 330–347.
Abstract: The main aim of this article is to investigate the behavioral consequences of the provision of subject-specific information in the group effort levels chosen by players in an experimental CPR game. We examine two basic treatments, one with incomplete information and the other with complete information. In the former, subjects are informed only about their own individual payoffs and the aggregate extraction effort level of the group, and in the latter they are also informed about the individual effort levels and payoffs of each subject. Given this setting, the basic question we attempt to answer is: Will the provision of subject-specific performance information (i.e. individual's effort levels and payoffs) improve or worsen the tragedy of the commons (i.e. an exploitation effort level greater than the socially optimum level)? In order to motivate our hypotheses and explain our experimental results at the individual level, we make use of the theory of learning in games, which goes beyond standard non-cooperative game theory, allowing us to explore the three basic benchmarks in the commons context: Nash equilibrium, Pareto efficient, and open access outcomes. We use several learning and imitation theoretical models that are based on contrasting assumptions about the level of rationality and the information available to subjects, namely: best response, imitate the average, mix of best response and imitate the average, imitate the best and follow the exemplary learning rules. Finally, in order to econometrically test the hypotheses formulated from the theoretical predictions we use a random-effects model to assess the explanatory power of the different selected behavioral learning and imitation rules. (C) 2010 Elsevier B.V. All rights reserved.
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