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Complexity and Entropy in Legal Language
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In: Frontiers of Physics, 9 (2021)
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Bidirectional String Anchors: A New String Sampling Mechanism ...
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Noise-skipping Earley parsing and in-order tree extraction from shared packed parse forests
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Temporal Social Network Analysis using Harvard Caselaw Access Project
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Sentiment classification for employees reviews using regression vector- stochastic gradient descent classifier (RV-SGDC)
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In: PeerJ Comput Sci (2021)
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Going beyond our means: A proposal for improving psycholinguistic methods
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Improving the Fitness Function of an Evolutionary Suspense Generator Through Sentiment Analysis
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In: IEEE Access, vol. 9, pp. 39626-39635, 2021 (2021)
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Abstract:
The perception of suspense in stories is affected not only by general literary aspects like narrative structure and linguistic features, but also by anticipation and evocation of feelings like aversion, disgust or empathy. As such, it is possible to alter the feeling of suspense by modifying components of a story that convey these feelings to the audience. Based on a previous straightforward model of suspense adaptation, this paper describes the design, implementation and evaluation of a computational system that adapts narrative scenes for conveying a specific user-defined amount of suspense. The system is designed to address the impact of different types of emotional components on the reader. The relative weighted suspense of these components is computed with a regression model based on a sentiment analysis tool, and used as a fitness function in an evolutionary algorithm. This new function is able to identify the different weights on the prediction of suspense in aspects like outcome, decorative elements, or threat's appearance. The results indicate that this approach represents a significant improvement over the previous existing approach.
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Keyword:
Automatic story generation; Computational modeling; Correlation; Distance measurement; Evolutionary computation; genetic programming; Prediction algorithms; predictive model; Predictive models; Sentiment analysis; suspense
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URL: http://hdl.handle.net/10498/24767 https://doi.org/10.1109/ACCESS.2021.3064242
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Multilabel convolution neural network for facial expression recognition and ordinal intensity estimation
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In: PeerJ Comput Sci (2021)
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Algorithmic Audiencing: Why we need to rethink free speech on social media
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Vowel Harmony Viewed as Error-Correcting Code
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In: Proceedings of the Society for Computation in Linguistics (2021)
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Extracting Human Behaviour and Personality Traits from Social Media
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Normalisation of 16th and 17th century texts in French and geographical named entity recognition
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In: 4th ACM SIGSPATIAL International Workshop on Geospatial Humanities ; ACM SIGSPATIAL GeoHumanities'20 ; https://hal-upec-upem.archives-ouvertes.fr/hal-02955867 ; ACM SIGSPATIAL GeoHumanities'20, ACM, Nov 2020, Seattle (virtual), United States. pp.28-34, ⟨10.1145/3423337.3429437⟩ ; https://ludovicmoncla.github.io/sigspatial-geohumanities-2020/ (2020)
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Unsupervised Structural Graph Node Representation Learning
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In: Boise State University Theses and Dissertations (2020)
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Who Should Take College-Level Courses? Impact Findings From an Evaluation of a Multiple Measures Assessment Strategy
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Building Collaboration-based Resources In Endowed African Languages: Case Of NTeALan Dictionaries Platform
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In: Proceedings of the First workshop on Resources for African Indigenous Languages (RAIL) ; https://hal.archives-ouvertes.fr/hal-02701162 ; Proceedings of the First workshop on Resources for African Indigenous Languages (RAIL), 2020 (2020)
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NTeALan Dictionaries Platforms: An Example Of Collaboration-Based Model
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In: Proceedings of the 1st International Workshop on Language Technology Platforms (IWLTP 2020) ; https://hal.archives-ouvertes.fr/hal-02701912 ; Proceedings of the 1st International Workshop on Language Technology Platforms (IWLTP 2020), 2020, pp.11 - 16 (2020)
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