Este trabajo se inserta en el marco del proyecto VITALEX y en él ofrecemos los datos relativos al léxico agrícola pertenecientes al punto Gr601 que se corresponde conel pueblo de Trevélez. Realizamos ...un estudio de vitalidad léxica de dicho municipio por medio de una metodología contrastiva donde comparamos los datos de VITALEX con los del tomo I del ALEA. Además, podemos observar una relación interesante entre la transformación económica y social de la comarca de La Alpujarra con los porcentajes de vitalidad y mortandad del léxico agrícola. Se hace contrastando los resultados obtenidos por las tres generaciones que configuran VITALEX en relación con los datos del ALEA.
In this piece, we honor the work of Albert Costa. His work focused on how bilinguals manage two languages, the brain mechanisms involved, and the ways in which language and emotion are related. We ...end by discussing ways in which his work will frame research in the field going forward.
Even though considerable attention has been given to the polarity of words (positive and negative) and the creation of large polarity lexicons, research in emotion analysis has had to rely on limited ...and small emotion lexicons. In this paper, we show how the combined strength and wisdom of the crowds can be used to generate a large, high‐quality, word–emotion and word–polarity association lexicon quickly and inexpensively. We enumerate the challenges in emotion annotation in a crowdsourcing scenario and propose solutions to address them. Most notably, in addition to questions about emotions associated with terms, we show how the inclusion of a word choice question can discourage malicious data entry, help to identify instances where the annotator may not be familiar with the target term (allowing us to reject such annotations), and help to obtain annotations at sense level (rather than at word level). We conducted experiments on how to formulate the emotion‐annotation questions, and show that asking if a term is associated with an emotion leads to markedly higher interannotator agreement than that obtained by asking if a term evokes an emotion.
DispoCen es un sistema para el análisis de la disponibilidad y la centralidad léxica. Aunque existen programas específicos para el cálculo de los citados índices, estos suelen restringir en exceso ...las posibilidades de análisis y explotación de los datos, bien porque se trata de herramientas obsoletas, bien porque sus códigos son excesivamente cerrados e inaccesibles. DispoCen está basado en una librería de herramientas en R que pone al alcance de quienes estudian el léxico el desarrollo de múltiples aplicaciones y modelos originales. En este trabajo hemos incluido los códigos necesarios para ejecutar los análisis, con lo que potenciamos la necesaria replicabilidad que favorece el trabajo autónomo de la comunidad investigadora. Para facilitar el acceso al sistema, también presentamos una sencilla utilidad gráfica que permite el acceso a los análisis más usuales. Como muestra de las posibilidades de DispoCen, incluimos un apartado específico con propuestas de análisis realizadas con filtros sociológicos.
From a very young age, monolingual children assume their language has no synonyms, or use the principle of mutual exclusivity (only one label per object). In contrast, bilingual children often accept ...more novel synonyms than monolinguals. One possible explanation for this difference is the lexicon structure hypothesis: having synonyms (across languages) in the lexicon reduces adherence to mutual exclusivity. The purpose of this study is to test the lexicon structure hypothesis by comparing three- to five-year-old children who speak either Canadian French or English. Canadian French allows more synonyms than English. French-speaking children should therefore accept more novel synonyms than English-speaking children. The children did a disambiguation task, choosing whether a familiar or an unfamiliar object was the referent of a novel word (e.g., moli). Surprisingly, the French-speaking children accepted significantly fewer novel synonyms than English-speaking children. However, they accepted the most synonyms for objects that had synonyms in French but they did not know both synonyms. These results support a modified version of the lexicon structure hypothesis, one that accounts for children’s weak access to synonyms.
Upaya melakukan analisis emosi pada teks komentar mahasiswa dalam evaluasi pembelajaran sangat penting dilakukan. Komentar dalam kuesener umumnya tidak diolah, padahal data tersebut mengandung ...informasi dalam mengungkap emosi mahasiswa dalam proses pembelajaran. Untuk itu deteksi dan klasifikasi emosi pada opini mahasiswa dapat memperbaiki hasil kuesioner. Penelitian ini bertujuan menerapkan metode klasifikasi emosi pada teks komentar mahasiswa berbasis pada leksikon emosi dari NRC Emolex. Jenis emosi yang akan dideteksi adalah 8 jenis emosi, yaitu marah (Anger), antisipasi (anticipation), jijik (disgust), takut (fear), bahagia (joy), sedih (sadness), terkejut (surprise) dan yakin (trust) . Data diambil dari komentar dan saran mahasiswa pada kuesioner pada Universitas AKPRIND Indonesia tahun 2020-2022 sebanyak 4000 data yang telah dilabeli secara manual. Tujuan lain dari studi ini adalah melihat sejauh mana efektivitas leksikon emosi Emolex untuk klasifikasi emosi teks kuesioner akademis. Hasil penelitian menunjukkan rata-rata akurasi sebesar 56,2%. Dari yang diketahui label emosinya 3 prosentase tertinggi ada pada label Sadness (19,2%), Joy(16,7%) dan Fear (13,5%) yang masing-masing memiliki akurasi 72%, 68% dan 68%. Dari penelitian terungkap bahwa kinerja Emolex untuk klasifikasi emosi masih kurang memuaskan dan memerlukan pengembangan leksikon lebih jauh lagi.
Sentiment analysis is held to be one of the highly dynamic recent research fields in Natural Language Processing, facilitated by the quickly growing volume of Web opinion data. Most of the approaches ...in this field are focused on English due to the lack of sentiment resources in other languages such as the Arabic language and its large variety of dialects. In most sentiment analysis applications, good sentiment resources play a critical role. Based on that, in this article, several publicly available sentiment analysis resources for Arabic are introduced. This article introduces the Arabic senti-lexicon, a list of 3880 positive and negative synsets annotated with their part of speech, polarity scores, dialects synsets and inflected forms. This article also presents a Multi-domain Arabic Sentiment Corpus (MASC) with a size of 8860 positive and negative reviews from different domains. In this article, an in-depth study has been conducted on five types of feature sets for exploiting effective features and investigating their effect on performance of Arabic sentiment analysis. The aim is to assess the quality of the developed language resources and to integrate different feature sets and classification algorithms to synthesise a more accurate sentiment analysis method. The Arabic senti-lexicon is used for generating feature vectors. Five well-known machine learning algorithms: naïve Bayes, k-nearest neighbours, support vector machines (SVMs), logistic linear regression and neural network are employed as base-classifiers for each of the feature sets. A wide range of comparative experiments on standard Arabic data sets were conducted, discussion is presented and conclusions are drawn. The experimental results show that the Arabic senti-lexicon is a very useful resource for Arabic sentiment analysis. Moreover, results show that classifiers which are trained on feature vectors derived from the corpus using the Arabic sentiment lexicon are more accurate than classifiers trained using the raw corpus.
Este trabajo se centra en el tratamiento de la variación léxica en el ámbito de la enseñanza del español como segunda lengua. En él se revisan oposiciones diatópicas del léxico hispánico y se ensaya ...una nueva metodología de aproximación al fenómeno de la representatividad. El objetivo último del análisis es proponer una renovación y actualización de las Nociones específicas del Plan Curricular del Instituto Cervantes (PCIC) incluyendo: (a) panhispanismos, (b) americanismos y (c) españolismos. El trabajo propone un nuevo índice de representatividad léxica y analiza los resultados del cálculo, comparándolos con los de modelos anteriores. Para la presentación de resultados se incluye una herramienta de acceso gratuito con mapas interactivos de geosinónimos. El estudio aporta una perspectiva lingüística plural, policéntrica y ecolingüística al inventario léxico del PCIC y compensa la restricción que supone describir el vocabulario únicamente a partir de la norma centro-norte peninsular española.
Advances in technology have fundamentally changed how information is produced and consumed by all actors involved in tourism. Tourists can now access different sources of information, and they can ...generate their own content and share their views and experiences. Tourism content shared through social media has become a very influential information source that impacts tourism in terms of both reputation and performance. However, the volume of data on the Internet has reached a level that makes manual processing almost impossible, demanding new analytical approaches. Sentiment analysis is rapidly emerging as an automated process of examining semantic relationships and meaning in reviews. In this article, different sentiment analysis approaches applied in tourism are reviewed and assessed in terms of the datasets used and performances on key evaluation metrics. The article concludes by outlining future research avenues to further advance sentiment analysis in tourism as part of a broader Big Data approach.