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  • 1
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    The Dynamics of Emotions Online (2016)
    Royal Society
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    Publication Date: 2016-08-12
    Description: We study the changes in emotional states induced by reading and participating in online discussions, empirically testing a computational model of online emotional interaction. Using principles of dynamical systems, we quantify changes in valence and arousal through subjective reports, as recorded in three independent studies including 207 participants (110 female). In the context of online discussions, the dynamics of valence and arousal is composed of two forces: an internal relaxation towards baseline values independent of the emotional charge of the discussion and a driving force of emotional states that depends on the content of the discussion. The dynamics of valence show the existence of positive and negative tendencies, while arousal increases when reading emotional content regardless of its polarity. The tendency of participants to take part in the discussion increases with positive arousal. When participating in an online discussion, the content of participants' expression depends on their valence, and their arousal significantly decreases afterwards as a regulation mechanism. We illustrate how these results allow the design of agent-based models to reproduce and analyse emotions in online communities. Our work empirically validates the microdynamics of a model of online collective emotions, bridging online data analysis with research in the laboratory.
    Keywords: human-computer interaction
    Electronic ISSN: 2054-5703
    Topics: Natural Sciences in General
    Published by Royal Society
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  • 2
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    Social signals in Bitcoin trading (2015)
    Royal Society
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    Publication Date: 2015-10-01
    Description: The availability of data on digital traces is growing to unprecedented sizes, but inferring actionable knowledge from large-scale data is far from being trivial. This is especially important for computational finance, where digital traces of human behaviour offer a great potential to drive trading strategies. We contribute to this by providing a consistent approach that integrates various datasources in the design of algorithmic traders. This allows us to derive insights into the principles behind the profitability of our trading strategies. We illustrate our approach through the analysis of Bitcoin, a cryptocurrency known for its large price fluctuations. In our analysis, we include economic signals of volume and price of exchange for USD, adoption of the Bitcoin technology and transaction volume of Bitcoin. We add social signals related to information search, word of mouth volume, emotional valence and opinion polarization as expressed in tweets related to Bitcoin for more than 3 years. Our analysis reveals that increases in opinion polarization and exchange volume precede rising Bitcoin prices, and that emotional valence precedes opinion polarization and rising exchange volumes. We apply these insights to design algorithmic trading strategies for Bitcoin, reaching very high profits in less than a year. We verify this high profitability with robust statistical methods that take into account risk and trading costs, confirming the long-standing hypothesis that trading-based social media sentiment has the potential to yield positive returns on investment.
    Keywords: e-science
    Electronic ISSN: 2054-5703
    Topics: Natural Sciences in General
    Published by Royal Society
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  • 3
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    Surrogate modelling for the prediction of spatial fields based on simultaneous dimensionality reduction of high-dimensional input/output spaces (2018)
    Royal Society
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    Publication Date: 2018-04-26
    Description: Time-consuming numerical simulators for solving groundwater flow and dissolution models of physico-chemical processes in deep aquifers normally require some of the model inputs to be defined in high-dimensional spaces in order to return realistic results. Sometimes, the outputs of interest are spatial fields leading to high-dimensional output spaces. Although Gaussian process emulation has been satisfactorily used for computing faithful and inexpensive approximations of complex simulators, these have been mostly applied to problems defined in low-dimensional input spaces. In this paper, we propose a method for simultaneously reducing the dimensionality of very high-dimensional input and output spaces in Gaussian process emulators for stochastic partial differential equation models while retaining the qualitative features of the original models. This allows us to build a surrogate model for the prediction of spatial fields in such time-consuming simulators. We apply the methodology to a model of convection and dissolution processes occurring during carbon capture and storage.
    Keywords: computer modelling and simulation, applied mathematics
    Electronic ISSN: 2054-5703
    Topics: Natural Sciences in General
    Published by Royal Society
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  • 4
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    Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media (2017)
    Royal Society
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    Publication Date: 2017-08-10
    Description: In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen–Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.
    Keywords: computational mathematics, applied mathematics, fluid mechanics
    Electronic ISSN: 2054-5703
    Topics: Natural Sciences in General
    Published by Royal Society
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  • 5
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    Evidence of sexual dimorphism in skeletal morphology of a gonochoric reef coral (2018)
    Royal Society
    Details
    Publication Date: 2018-05-24
    Description: In the emerald coral Porites panamensis , the rates of elongation and calcification of colonies are higher in males than in females, probably because of the higher energetic demands of the latter in order to cope with the development of the large planulae produced throughout the year. This differing energetic demand could also be reflected in the sexual dimorphism of the calyces; hence, to test this hypothesis, 11 morphological traits of the corallite were assessed from 63 colonies that were collected in the southern Gulf of California, Mexico. Three traits showed statistical differences between sexes, enabling accurate distinction of males from females. Our results confirm for the first time the existence of external sexual dimorphism in a reef-building coral, opening the possibility that sex-related morphological differences may occur generally in gonochoric scleractinians. These findings can be very useful for the correct classification and characterization of recent and fossil records, helping to improve the historical and evolutive understanding of reef-building corals facing threats under environmental changes.
    Keywords: taxonomy and systematics, ecology
    Electronic ISSN: 2054-5703
    Topics: Natural Sciences in General
    Published by Royal Society
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