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Publications

Publications by CRACS

2018

Human vs. Automatic Annotation Regarding the Task of Relevance Detection in Social Networks

Authors
Guimarães, N; Miranda, F; Figueira, Á;

Publication
Advances in Internet, Data & Web Technologies - Lecture Notes on Data Engineering and Communications Technologies

Abstract

2018

Twitter as a Source for Time- and Domain-Dependent Sentiment Lexicons

Authors
Guimarães, N; Torgo, L; Figueira, A;

Publication
Lecture Notes in Social Networks - Social Network Based Big Data Analysis and Applications

Abstract

2018

Parallel Asynchronous Strategies for the Execution of Feature Selection Algorithms

Authors
Silva, J; Aguiar, A; Silva, F;

Publication
International Journal of Parallel Programming

Abstract

2018

EmoSpell, a morphological and emotional word analyzer

Authors
Maia, MI; Leal, JP;

Publication
Information (Switzerland)

Abstract
The analysis of sentiments, emotions, and opinions in texts is increasingly important in the current digital world. The existing lexicons with emotional annotations for the Portuguese language are oriented to polarities, classifying words as positive, negative, or neutral. To identify the emotional load intended by the author, it is necessary to also categorize the emotions expressed by individual words. EmoSpell is an extension of a morphological analyzer with semantic annotations of the emotional value of words. It uses Jspell as the morphological analyzer and a new dictionary with emotional annotations. This dictionary incorporates the lexical base EMOTAIX.PT, which classifies words based on three different levels of emotions-global, specific, and intermediate. This paper describes the generation of the EmoSpell dictionary using three sources: the Jspell Portuguese dictionary and the lexical bases EMOTAIX.PT and SentiLex-PT. Additionally, this paper details the Web application and Web service that exploit this dictionary. It also presents a validation of the proposed approach using a corpus of student texts with different emotional loads. The validation compares the analyses provided by EmoSpell with the mentioned emotional lexical bases on the ability to recognize emotional words and extract the dominant emotion from a text. © 2018 by the authors.

2018

Video Dissemination in Untethered Edge-Clouds: A Case Study

Authors
Rodrigues, J; Marques, ERB; Silva, J; Lopes, LMB; Silva, F;

Publication
Distributed Applications and Interoperable Systems - Lecture Notes in Computer Science

Abstract

2018

Multi-dimensional lock-free arrays for multithreaded mode-directed tabling in Prolog

Authors
Areias, M; Rocha, R;

Publication
Concurrency and Computation: Practice and Experience

Abstract

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