Ling, Xiaoxu Yan, Siyuan
Published in
Accountability in research
Much of the current attention on artificial intelligence (AI)-based natural language processing (NLP) systems has focused on research ethics and integrity but neglects their roles in the editorial and peer-reviewing process. We argue that the academic community needs to develop and apply a consistent end-to-end policy on the ethics and integrity of...
Puren, Marie
In 2015, the Annales journal, traditionally open to interdisciplinary approaches in history, referred to 'the current historiographical moment [as] call [ing] for an experimentation of approaches'. 1 Although this observation did not exclusively refer to the new possibilities offered by the technological advancements of the time -particularly in th...
jeyaraman, brindha priyadarshini dai, bing tian fang, yuan
Accurately predicting financial entity performance remains a challenge due to the dynamic nature of financial markets and vast unstructured textual data. Financial knowledge graphs (FKGs) offer a structured representation for tackling this problem by representing complex financial relationships and concepts. However, constructing a comprehensive an...
Chen, Lian Sun, Wenjun Badin, Flora
This article examines advances in phraseomatics (L. Chen, 2023) and digital phraseography through the DiCoP project and its DiCoP-Text corpus, aimed at enriching linguistic models and machine translation. The project evaluates the frequency of use of phraseological units (PUs) and improves their translation in different contexts, drawing on recent ...
alawneh, hussam hasasneh, ahmad maree, mohammed
Social media users often express their emotions through text in posts and tweets, and these can be used for sentiment analysis, identifying text as positive or negative. Sentiment analysis is critical for different fields such as politics, tourism, e-commerce, education, and health. However, sentiment analysis approaches that perform well on Englis...
eker, hasan
In this study, by using the texts describing the hazards and precautions taken during text mining, the necessary processes were carried out to first estimate the probability value and severity value of the risk and then calculate the risk values by Natural Language Processing analysis. In order to be used within the scope of the study, two data set...
soleimani, reza guo, shengjie haley, katarina l. jacks, adam lobaton, edgar
Dementia is primarily caused by neurodegenerative diseases like Alzheimer’s disease (AD). It affects millions worldwide, making detection and monitoring crucial. This study focuses on the detection of dementia from speech transcripts of controls and dementia groups. We propose encoding in-text pauses and filler words (e.g., “uh” and “um”) in text-b...
al-alshaqi, mohammed rawat, danda b. liu, chunmei
The proliferation of fake news across multiple modalities has emerged as a critical challenge in the modern information landscape, necessitating advanced detection methods. This study proposes a comprehensive framework for fake news detection integrating text, images, and videos using machine learning and deep learning techniques. The research empl...
azzat, media jacksi, karwan ali, ismael
Semantic ontologies have been widely utilized as crucial tools within natural language processing, underpinning applications such as knowledge extraction, question answering, machine translation, text comprehension, information retrieval, and text summarization. While the Kurdish language, a low-resource language, has been the subject of some ontol...
zakarija, ivona škopljanac-mačina, frano marušić, hrvoje blašković, bruno
Emerging research indicates that sentiment analyses of Dubrovnik focus mainly on hotel accommodations and restaurants. However, little attention has been paid to attractions, even though they are an important aspect of destinations and require more care and investment than amenities. This study examines how visitors experience Dubrovnik based on th...