Academic Articles & Research Papers

Leveraging sentiment analysis of food delivery services reviews using deep learning and word embedding

Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods via online platforms is a cru...

Domain-Specific Sentiment Analysis: An Optimized Deep Learning Approach for the Financial Markets

Although different studies are caried out by deep learning models for financial markets sentiment analysis, there is a lack of specific embedding method that regards the domain. Therefore, the goal of this study is to discover what type of ...

Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing

In 2005, the Human Language Technology Conference (HLT) and the Conference on Empirical Methods in Natural Language Processing (EMNLP) were held together as a joint conference for the first time. The conference was co-sponsored by the organ...

A natural language processing based technique for sentiment analysis of college english corpus

The college English corpus can help us better master English, but how to obtain the desired information from a large number of English corpus has become the focus of information technology. Based on the natural language processing (NLP) tec...

Le contact de langues entre Darija et Hassaniyya dans la ville de Laâyoune

Dans la présente contribution, nous nous interrogeons sur les pratiques langagières des habitants de la ville de Laâyoune dans une situation de contact linguistique entre la darija et la hassaniyya. Autrement dit, comment se manifeste l’alt...

Les structures argumentatives de la locution adverbiale polyvalente jusqu’à un certain point

This paper sketches out possible argumentation structures that are activated by the use of the adverbial jusqu’à un certain point as found in a corpus of examples taken from Le Monde. It is in fact a multifunctional adverbial with both quan...

Unveiling Fall Risk Factors: Nurse-Driven Corpus Development for Natural Language Processing.

Content Analysis of Medical Research Articles: A corpus-based study

Introduction: Content analysis applied for comparing texts, a writer’s works with others or the same author, the texts written in a natural language with texts in other languages literature and review of specialized field. The present study...

Natural Language Processing

Natural language processing is a fast-evolving field with popular applications in language translation, speech recognition, text classification, and summarization of text, among others. The central aspect of NLP is vectorizing text data. Te...

Explainable Sentiment-Based Reputational Risk Modelling in Ugandan Megaprojects

Reputational risk reflected in digital public discourse can significantly influence stakeholder perceptions, public trust, and decision-making surrounding government megaprojects. Existing computational approaches primarily focus on sentime...

Zur Vokalquantität in der Mundart der Stadt Zürich

This paper analyses the vowel system of the dialect spoken in the city of Zürich, which shows a systematic use of distinctive length contrasts. In order to ascertain the acoustic correlates of the quantity feature, an experimental study has...

It-clefts as pragmatically-motivated extraposed constructions?

This paper investigates the discursive and pragmatic functions of it-clefts in contemporary English. The qualitative corpus-based study is based on the hypothesis that an it-cleft originates from the extraposition of a complex noun phrase i...

Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

Welcome to EMNLP 2010, Conference on Empirical Methods in Natural Language Processing! The conference is organized by SIGDAT, the Association for Computational Linguistics' special interest group on linguistic data and corpus-based approach...

Deep learning for natural language processing: advantages and challenges

Deep learning refers to machine learning technologies for learning and utilizing ‘deep’ artificial neural networks, such as deep neural networks (DNN), convolutional neural networks (CNN) and recurrent neural networks (RNN). Recently, deep ...

Historical Models and Serial Sources

Serial sources such as records, registers, and inventories are the ‘classic’ sources for quantitative history. Unstructured, narrative texts such as newspaper articles or reports were out of reach for historical analyses, both for practical...

Mention Detection for Coreference Resolution in Polish. Development of the Formal Grammar

Mention Detection for Coreference Resolution in Polish. Development of the Formal Grammar This paper presents the results of an improvement and extension of the Shallow Grammar of Polish, designed for the needs of the Computer-based Method...

Post-democratic discursive hegemony – a natural language processing-based analysis of Hungarian parliamentary discourses between 1998-2020

The parliament, as a key component of the public sphere, is both a reflection of and a stage for the post-democratic transition. Our study examines Hungarian parliamentary discourse as an indicator of a transition in which democratic instit...

Natural Language Processing for Requirements Engineering

Natural Language Processing for Requirements Engineering (NLP4RE) is an area of research and development that seeks to apply natural language processing (NLP) techniques, tools, and resources to the requirements engineering (RE) process, to...

Handbook of Natural Language Processing

Symbolic approaches to natural language processing tokenisation and sentence segmentation lexical analysis parsing techniques semantic analysis discourse structure and intention recognition natural language generation intelligent writing as...

Natural language processing

Previous ARIST chapters (Haas, 1996;Warner, 1987) described a number of theoretical developments that have influenced research in NLP.The most recent theoretical developments can be grouped into four classes: (i) statistical and corpus-base...