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Showing 19 of 39 academic articles

State of Art for Semantic Analysis of Natural Language Processing

Dastan Hussen Maulud, Subhi R. M. Zeebaree, Karwan Jacksi, Mohammed Mohammed Sadeeq et al. • Qubahan Academic Journal (2021)

Semantic analysis is an essential feature of the NLP approach. It indicates, in the appropriate format, the context of a sentence or paragraph. Semantics is about language significance study. The vocabulary used conveys the importance of th...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.48161/qaj.v1n2a40

National Leaders’ Usage of Twitter in Response to COVID-19: A Sentiment Analysis

Yuming Wang, Stephen M Croucher, Stephen M Croucher, Erika Pearson • Frontiers in Communication (2021)

Twitter is a powerful tool for world leaders to disseminate public health information and to reach citizens. While Twitter, like other platforms, affords world leaders the opportunity to rapidly present information to citizens, the discours...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcomm.2021.732399

Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review

Jiaqi Fu, Chaixiu Li, Chunlan Zhou, Wenji Li et al. • Journal of Medical Internet Research (2023)

BackgroundGiven the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews ...

DOAJ Open Access (DOAJ) DOI: 10.2196/43349

Paradigm Shift in Natural Language Processing

Tianxiang Sun, Xiang-Yang Liu, Xipeng Qiu, Xuanjing Huang • Machine Intelligence Research (2022)

Abstract In the era of deep learning, modeling for most natural language processing (NLP) tasks has converged into several mainstream paradigms. For example, we usually adopt the sequence labeling paradigm to solve a bundle of tasks such as...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11633-022-1331-6

Natural Language Processing

Pramod Kumar Singh • Apress eBooks (2018)

This chapter uncovers some of the basic techniques to tackle text data using PySpark. Today's textual form of data is being generated at a lightning pace with multiple social media platforms offering users the options to share their opinion...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-4131-8_9

Building Dynamic Lexicons for Sentiment Analysis

Nicolás Mechulam, Damián Salvia, Aiala Rosá, Mathias Etcheverry • Inteligencia Artificial (2019)

Nowadays, many approaches for Sentiment Analysis (SA) rely on affective lexicons to identify emotions transmitted in opinions. However, most of these lexicons do not consider that a word can express different sentiments in different predica...

DOAJ Open Access (DOAJ) DOI: 10.4114/intartif.vol22iss64pp1-13

Tracking discussions of complementary, alternative, and integrative medicine in the context of the COVID-19 pandemic: a month-by-month sentiment analysis of Twitter data

Jeremy Y. Ng, Wael Abdelkader, Cynthia Lokker • BMC Complementary Medicine and Therapies (2022)

Abstract Background Coronavirus disease 2019 (COVID-19) is a novel infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite the paucity of evidence, various complementary, alternative and integr...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12906-022-03586-1

Natural Language Processing Recipes

Akshay Kulkarni, Adarsha Shivananda • Apress eBooks (2019)

Implement natural language processing applications with Python in this problem-solution book. Here, coding exercises will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identi...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-4267-4

Handbook of Natural Language Processing

Nitin Indurkhya, Fred J. Damerau • Chapman & Hall/CRC eBooks (2010)

The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter ...

OPENALEX DOI: https://doi.org/10.1201/9781420085938

Unpacking Public Perceptions of Qris with Twitter Data: A Vader And LDA Methodology

Dzakiya Ishmatul Ulya, Anang Kunaefi, Dwi Rolliawati, Bayu Adhi Nugroho • Jurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer (2023)

QRIS, a mobile payment transaction system standardized by Bank Indonesia, has become the subject of extensive public discourse on Twitter. Employing VADER for sentiment analysis and LDA for topic modeling, this study aims to capture the nua...

DOAJ Open Access (DOAJ) DOI: 10.31961/eltikom.v7i2.742

Deep Learning--based Text Classification

Shervin Minaee, Nal Kalchbrenner, Erik Cambria, Narjes Nikzad-Khasmakhi et al. • ACM Computing Surveys (2021)

Deep learning--based models have surpassed classical machine learning--based approaches in various text classification tasks, including sentiment analysis, news categorization, question answering, and natural language inference. In this art...

OPENALEX Open Access DOI: https://doi.org/10.1145/3439726

ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning

Sarah Alhumoud, Asma Al Wazrah, Laila Alhussain, Lama Alrushud et al. • PeerJ Computer Science (2023)

COVID-19 has become a global pandemic that has affected not only the health sector but also economic, social, and psychological well-being. Individuals are using social media platforms to communicate their feelings and sentiments about the ...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.1507

Deep learning for sentiment analysis: A survey

Lei Zhang, Shuai Wang, Bing Liu • Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2018)

Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state‐of‐the‐art prediction results. Along with the success of deep learning in many appl...

OPENALEX Open Access DOI: https://doi.org/10.1002/widm.1253

Some results of the digital analysis of the semantic similarity of audiovisual translation texts (based on the films directed by Denis Villeneuve)

Aishat I. Lepshakova, Oleg V. Kurskikh • Актуальные проблемы филологии и педагогической лингвистики (2025)

The article analyses different translation versions of science fiction films directed by Denis Villeneuve with the aim of determining their semantic similarity through NLP analysis. There are four groups of metrics used in text analysis: se...

DOAJ Open Access (DOAJ) DOI: 10.29025/2079-6021-2025-1-132-150

On the use of aspect-based sentiment analysis of Twitter data to explore the experiences of African Americans during COVID-19

Meghna Chaudhary, Kristin Kosyluk, Sylvia Thomas, Tempestt Neal • Scientific Reports (2023)

Abstract According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rate...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-023-37592-1

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study

Ziru Fu, Yu Cheng Hsu, Christian S Chan, Chaak Ming Lau et al. • Journal of Medical Internet Research (2024)

BackgroundSentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its...

DOAJ Open Access (DOAJ) DOI: 10.2196/51069

AN IMPROVED GRU BASED ON RECURRENT ATTENTION UNIT AND SELF- ATTENTION TECHNIQUE FOR TEXT SENTIMENT ANALYSIS

Dhurgham Ali Mohammed, Kalyani A. Patel • ICTACT Journal on Soft Computing (2025)

In text sentiment analysis, a crucial challenge is that conventional word vectors fail to capture lexical ambiguity. The Gated Recurrent Unit (GRU), an advanced variant of RNN, is extensively utilized in natural language processing tasks su...

DOAJ Open Access (DOAJ) DOI: 10.21917/ijsc.2025.0518

Python Machine Learning

Sebastian Raschka (2015)

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This BookLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effect...

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