Ontologías para la terminología : por qué, cuándo, cómo

Aquest article tracta sobre la utilitat que pot tenir per a un terminòleg la integració d'una ontologia en la seva feina, els criteris que cal considerar en el cas de plantejar-se fer-ho, les pautes que cal seguir i les eines que té a la seva disposició. Ofereix una visió actualitzada de l'àmbit d'aplicació de les ontologies, des de la perspectiva del Web Semàntic.Este artículo discute la utilidad que puede tener para el terminólogo la integración de una ontología en su trabajo, los criterios a considerar en el caso de plantearse hacerlo, las pautas a seguir y las herramientas a su disposición. Se ofrece una visión actualizada del ámbito de aplicación de las ontologías, desde la perspectiva de la Web Semántica.This article discusses the usefulness of integrating an ontology in one's work when dealing with terminology, the criteria to take into consideration if this is a consideration, the guidelines to follow and the tools available. This article offers an updated review of the application of ontologies from the perspective of Web Semántica

Lingmotif: una Herramienta de Análisis de Sentimiento Enfocada en el Usuario

In this paper, we describe Lingmotif, a lexicon-based, linguistically-motivated, user-friendly, GUI-enabled, multi-platform, Sentiment Analysis desktop application. Lingmotif can perform SA on any type of input texts, regardless of their length and topic. The analysis is based on the identification of sentiment-laden words and phrases contained in the application's rich core lexicons, and employs context rules to account for sentiment shifters. It offers easy-to-interpret visual representations of quantitative data, as well as a detailed, qualitative analysis of the text in terms of its sentiment. Lingmotif can also take user-provided plugin lexicons in order to account for domain-specific sentiment expression. As of version 1.0, Lingmotif analyzes English and Spanish texts. Lingmotif thus aims to become a general-purpose Sentiment Analysis tool for discourse analysis, rhetoric, psychology, marketing, the language industries, and others.En este artículo se describe Lingmotif, una aplicación de Análisis de Sentimiento multi-plataforma, con interfaz gráfica de usuario amigable, motivada lingüísticamente y basada en léxico. Lingmotif efectúa Análisis de Sentimiento sobre cualquier tipo de texto, independientemente de su tamaño o tema. El análisis se basa en la identificación en el texto de palabras y frases con carga afectiva, contenidas en los diccionarios de la aplicación, y aplica reglas de contexto para dar cabida a modificadores del sentimiento. Ofrece representaciones gráficas fáciles de interpretar de los datos cuantitativos, así como un análisis detallado del texto. Lingmotif también puede utilizar léxicos del usuario a modo de plugins, de tal modo que es posible analizar de forma efectiva la expresión del sentimiento en dominios específicos. La versión 1.0 de Lingmotif está preparada para trabajar con textos en español e inglés. De este modo, se conforma como una herramienta de propósito general en el ámbito del Análisis de Sentimiento para el análisis del discurso, retórica, psicología, marketing, las industrias de la lengua y otras.This research was supported by Spain’s MINECO through the funding of project Lingmotif2 (FFI2016-78141-P)

Periodontal granulation tissue preservation in surgical periodontal disease treatment: a pilot prospective cohort study

© Korean Academy of Periodontology 2022 . This manuscript version is made available under the CC-BY-NC 4.0 license http://creativecommons.org/licenses/by-nc/4.0/ This document is Published version of a Published Work that appeared in final form in Journal of Periodontal Implant Science. To access the final edited and published work see https://doi.org/10.5051/jpis.2105780289Purpose The aim of this study was to evaluate the clinical outcomes of periodontal granulation tissue preservation (PGTP) in access flap periodontal surgery. Methods Twenty patients (stage III–IV periodontitis) with 42 deep periodontal pockets that did not resolve after non-surgical treatment were consecutively recruited. Access flap periodontal surgery was modified using PGTP. The clinical periodontal parameters were evaluated at 9 months. The differences in the amount of granulation tissue width (GTw) preserved were evaluated and the influence of smoking was analyzed. Results GTw >1 mm was observed in 97.6% of interproximal defects, and the granulation tissue extended above the bone peak in 71.4% of defects. At 9 months, probing pocket depth reduction (4.33±1.43 mm) and clinical attachment gain (CAG; 4.10±1.75 mm) were statistically significant (P0 mm. The clinical results in smokers were significantly worse. Conclusions PGTP was used to modify access flap periodontal surgery by preserving affected tissues with the potential for recovery. The results show that preserving periodontal granulation tissue is an effective and conservative procedure in the surgical treatment of periodontal disease

Identifying Polarity in Financial Texts for Sentiment Analysis: A Corpus-based Approach

AbstractIn this paper we describe our methodology to integrate domain-specific sentiment analysis in a lexicon-based system initially designed for general language texts. Our approach to dealing with specialized domains is based on the idea of “plug-in” lexical resources which can be applied on demand. A simple 3-step model based on the weirdness ratio measure is proposed to extract candidate terms from specialized corpora, which are then matched against our existing general-language polarity database to obtain sentiment-bearing words whose polarity is domain-specific

Building the Great Recession News Corpus (GRNC): a contemporary diachronic corpus of economy news in English

The paper describes the process involved in developing the Great Recession News Corpus (GRNC); a specialized web corpus, which contains a wide range of written texts obtained from the Business section of The Guardian and The New York Times between 2007 and 2015. The corpus was compiled as the main resource in a sentiment analysis project on the economic/financial domain. In this paper we describe its design, compilation criteria and methodological approach, as well as the description of the overall creation process. Although the corpus can be used for a variety of purposes, we include a sentiment analysis study on the evolution of the sentiment conveyed by the word credit during the years of the Great Recession which we think provides validation of the corpus.Ministerio de Economía, Industria y Competitividad. Proyecto "Lingmotif2: Plataforma Universal de Análisis de Sentimiento" (FFI2016-78141-P

Strategies for the analysis of large social media corpora: sampling and keyword extraction methods

In the context of the COVID-19 pandemic, social media platforms such as Twitter have been of great importance for users to exchange news, ideas, and perceptions. Researchers from fields such as discourse analysis and the social sciences have resorted to this content to explore public opinion and stance on this topic, and they have tried to gather information through the compilation of large-scale corpora. However, the size of such corpora is both an advantage and a drawback, as simple text retrieval techniques and tools may prove to be impractical or altogether incapable of handling such masses of data. This study provides methodological and practical cues on how to manage the contents of a large-scale social media corpus such as Chen et al. (JMIR Public Health Surveill 6(2):e19273, 2020) COVID-19 corpus. We compare and evaluate, in terms of efficiency and efficacy, available methods to handle such a large corpus. First, we compare different sample sizes to assess whether it is possible to achieve similar results despite the size difference and evaluate sampling methods following a specific data management approach to storing the original corpus. Second, we examine two keyword extraction methodologies commonly used to obtain a compact representation of the main subject and topics of a text: the traditional method used in corpus linguistics, which compares word frequencies using a reference corpus, and graph-based techniques as developed in Natural Language Processing tasks. The methods and strategies discussed in this study enable valuable quantitative and qualitative analyses of an otherwise intractable mass of social media data.Funding for open access publishing: Universidad de Málaga/CBUA. This work was funded by the Spanish Ministry of Science and Innovation [Grant No. PID2020-115310RB-I00], the Regional Govvernment of Andalusia [Grant No. UMA18-FEDERJA-158] and the Spanish Ministry of Education and Vocational Training [Grant No. FPU 19/04880]. Funding for open access charge: Universidad de Málaga / CBU

Tracking diachronic sentiment change of economic terms in times of crisis: Connotative fluctuations of ‘inflation’ in the news discourse

The present study focuses on the fluctuation of sentiment in economic terminology to observe semantic changes in restricted diachrony. Our study examines the evolution of the target term ‘inflation’ in the business section of quality news and the impact of the Great Recession. This is carried out through the application of quantitative and qualitative methods: Sentiment Analysis, Usage Fluctuation Analysis, Corpus Linguistics, and Discourse Analysis. From the diachronic Great Recession News Corpus that covers the 2007–2015 period, we extracted sentences containing the term ‘inflation’. Several facts are evidenced: (i) terms become event words given the increase in their frequency of use due to the unfolding of relevant crisis events, and (ii) there are statistically significant culturally motivated changes in the form of emergent collocations with sentiment-laden words with a lower level of domain-specificity

Corpus annotation and analysis of sarcasm on Twitter: #CatsMovie vs. #TheRiseOfSkywalker

Sentiment analysis is a natural language processing task that has received increased attention in the last decade due to the vast amount of opinionated data on social media platforms such as Twitter. Although the methodologies employed have grown in number and sophistication, analysing irony and sarcasm still poses a severe problem. From the linguistic perspective, sarcasm has been studied in discourse analysis from several perspectives, but little attention has been given to specific metrics that measure its relevance. In this paper we describe the creation of a manually-annotated dataset where detailed text markers are included. This dataset is a sample from a larger corpus of tweets (n= 76,764) on two highly controversial films: Cats and Star Wars: The Rise of Skywalker. We took two different samples for each film, one before and one after their release, to compare reception and presence of sarcasm. We then used a sentiment analysis tool to measure the impact of sarcasm in polarity detection and then manually classified the mechanisms of sarcasm generation. The resulting corpus will be useful for machine learning approaches to sarcasm detection as well as discourse analysis studies on irony and sarcasm

The expression of sentiment in user reviews of hotels

The linguistic expression of sentiment, understood as the polarity of an opinion, is known to be domain-specific to a certain extent (Aue & Gamon, 2005; Choi et al., 2009). Even though many words and expressions convey the same evaluation across domains (e.g., “excellent”, “terrible”), many others acquire a more precise semantic orientation within a specific domain. For example, features such as size or location (and the lexical expressions that are used to express them) may or may not convey semantic orientation depending on the topic. In Sentiment Analysis (SA), it is critical that domain-specific expressions of sentiment be accounted for (Tan et al., 2007) if the system is to be useful to those who wish to explore the polarity of texts belonging in that domain. The software tool Lingmotif (Moreno-Ortiz, 2016) will be used to explore a corpus of hotel reviews in the English language. Lingmotif is a lexicon-based, linguistically-motivated, user-friendly, GUI-enabled, multi-platform, Sentiment Analysis desktop application. Lingmotif can perform SA on any type of input texts, regardless of size and topic. The analysis is based on the identification of sentiment-laden words and phrases contained in the application's rich core lexicons, and employs context rules to account for sentiment shifters. It offers easy-to-interpret visual representations of quantitative data (text polarity, sentiment intensity, sentiment profile), as well as a detailed, qualitative analysis of the text in terms of its sentiment. Lingmotif can also take user-provided plugin lexicons in order to account for domain-specific sentiment expression. In this paper, we describe our procedure to identify domain-specific lexical cues for the domain of user reviews of Spanish hotels. We made use of a recently compiled corpus of reviews from the online travel agency booking site booking.com. This corpus was analyzed entirely with Lingmotif using only its core (i.e., general-language lexicon), and then manually analyzed the results to find errors and omissions produced by the lack of specialized language cues. We then encoded the identified lexical cues as a Lingmotif plugin lexicon and reran the analysis with it. This methodology allowed us, first, to obtain a very concrete description of the expression of sentiment in this domain, and, from a practical perspective, to precisely measure to what extent this expression is domain-dependent.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Treatment alternatives for the rehabilitation of the posterior edentulous maxilla

Rehabilitation of the edentulous maxilla with implant-supported fixed dental prostheses can represent a significant clinical challenge due to limited bone availability and surgical access, among other factors. This review addresses several treatment options to replace missing teeth in posterior maxillary segments, namely the placement of standard implants in conjunction with maxillary sinus floor augmentation, short implants, tilted implants, and distal cantilever extensions. Pertinent technical information and a concise summary of relevant evidence on the reported outcomes of these different therapeutic approaches are presented, along with a set of clinical guidelines to facilitate decision-making processes and optimize the outcomes of therapy