Universal, Unsupervised (Rule-Based), Uncovered Sentiment Analysis

We present a novel unsupervised approach for multilingual sentiment analysis driven by compositional syntax-based rules. On the one hand, we exploit some of the main advantages of unsupervised algorithms: (1) the interpretability of their output, in contrast with most supervised models, which behave as a black box and (2) their robustness across different corpora and domains. On the other hand, by introducing the concept of compositional operations and exploiting syntactic information in the form of universal dependencies, we tackle one of their main drawbacks: their rigidity on data that are structured differently depending on the language concerned. Experiments show an improvement both over existing unsupervised methods, and over state-of-the-art supervised models when evaluating outside their corpus of origin. Experiments also show how the same compositional operations can be shared across languages. The system is available at http://www.grupolys.org/software/UUUSA/Comment: 19 pages, 5 Tables, 6 Figures. This is the authors version of a work that was accepted for publication in Knowledge-Based System

One model, two languages: training bilingual parsers with harmonized treebanks

We introduce an approach to train lexicalized parsers using bilingual corpora obtained by merging harmonized treebanks of different languages, producing parsers that can analyze sentences in either of the learned languages, or even sentences that mix both. We test the approach on the Universal Dependency Treebanks, training with MaltParser and MaltOptimizer. The results show that these bilingual parsers are more than competitive, as most combinations not only preserve accuracy, but some even achieve significant improvements over the corresponding monolingual parsers. Preliminary experiments also show the approach to be promising on texts with code-switching and when more languages are added.Comment: 7 pages, 4 tables, 1 figur

Towards Syntactic Iberian Polarity Classification

Lexicon-based methods using syntactic rules for polarity classification rely on parsers that are dependent on the language and on treebank guidelines. Thus, rules are also dependent and require adaptation, especially in multilingual scenarios. We tackle this challenge in the context of the Iberian Peninsula, releasing the first symbolic syntax-based Iberian system with rules shared across five official languages: Basque, Catalan, Galician, Portuguese and Spanish. The model is made available.Comment: 7 pages, 5 tables. Contribution to the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA-2017) at EMNLP 201

The velocity ellipsoid for giants and dwarfs

The solar motion and the velocity ellipsoid are derived from samples of stars of different spectral types and luminosity class. The equations used are those of the radial velocity component of motion, including the K-term and galactic rotation corrections. The results obtained are compared with the published ones. The complete paper will be published elsewhere.Asociación Argentina de Astronomí

The velocity ellipsoid for giants and dwarfs

The solar motion and the velocity ellipsoid are derived from samples of stars of different spectral types and luminosity class. The equations used are those of the radial velocity component of motion, including the K-term and galactic rotation corrections. The results obtained are compared with the published ones. The complete paper will be published elsewhere.Asociación Argentina de Astronomí

The velocity ellipsoid for giants and dwarfs

The solar motion and the velocity ellipsoid are derived from samples of stars of different spectral types and luminosity class. The equations used are those of the radial velocity component of motion, including the K-term and galactic rotation corrections. The results obtained are compared with the published ones. The complete paper will be published elsewhere.Asociación Argentina de Astronomí