Within the hospitality sector, restaurants face growing pressure to integrate sustainable practices while maintaining economic viability. Two fundamental questions remain: do sustainability practices command price premiums, and does this relationship...
Mitochondria are increasingly recognized as integrated bioenergetic and signaling hubs across disease contexts, but the rapidly expanding literature remains fragmented across mechanisms, diseases, and analytical vocabularies. This study mapped the di...
The aim of this study was to analyze public opinion about online learning during the COVID-19 (Coronavirus Disease 2019) pandemic. A total of 154 articles from online news and blogging websites related to online learning were extracted from Google an...
Social media have been a valuable data source for studying people’s opinions, intentions, and behaviours. Such a data source incorporating advanced big data analysis methods, such as machine-operated emotion and sentiment analysis, will open un...
The purpose of this research is to explore sustainable supply chain management (SSCM) trends, and firms’ strategic positioning and execution with regard to sustainability in the textile and apparel industry based on news articles and sustainability r...
Social media posts by individuals affected by disasters and their relatives provide a significant source of data for identifying emergencies and needs, assessing the situation, and determining affected areas. These posts often contain not only text b...
The defossilisation of the agricultural sector is driven by intense worldwide academic research on non-fossil, renewable and energy-efficient agriculture, and the acknowledgment of the need for sustainable farming practices. For this purpose, not onl...
Background: The substandard vaccine case of that broke out in July 2018 in China triggered an outburst of news reports both domestically and aboard. Distilling the abundant textual information is helpful for a better understanding of the character du...
In the present study, we employed qualitative and quantitative content analytic methods to explore how fans use social chatbots to engage with the object of their fandom. Drawing on theories of self-disclosure, the Computers Are Social Actors (CASA)...
The development of location-based services facilitates the use of location data for detecting urban events. Currently, most studies based on location data model the pattern of an urban dynamic and then extract the anomalies, which deviate significant...
The analysis of sentiments, emotions, and opinions in texts is increasingly important in the current digital world. The existing lexicons with emotional annotations for the Portuguese language are oriented to polarities, classifying words as positive...
Topic modeling of large news streams is widely used to reconstruct economic and political narratives, which requires coherent topics with low lexical overlap while remaining interpretable to domain experts. We propose TF-SYN-NER-Rel, a structural&nda...
To better facilitate government management and planning based on public opinion, it is essential to propose a method for extracting public opinion perception features in consideration of an integrated framework, which aims at industry monitoring and...
What drives persistent urban–rural tourism satisfaction gaps: whether from promotional over-promising or structural service deficits? This distinction fundamentally determines whether territorial development resources should target marketing so...
9 November 2021
In this paper, we study language used by suicidal users on Reddit social media platform. To do that, we firstly collect a large-scale dataset of Reddit posts and annotate it with highly trained and expert annotators under a rigorous annotation scheme...
Artificial intelligence (AI) adoption in strategic sectors such as energy is often framed in optimistic narratives, yet its actual economic contribution remains under-quantified. This study proposes a novel, multi-stage methodology at the intersectio...
This study aims to create an AI system that analyzes text to evaluate student engagement in STEAM education. It explores how sentiment analysis can measure emotional, cognitive, and behavioral involvement in learning. We developed an AI-based text se...
This research proposes a method for the detection of semantic similarities in text snippets; the method achieves an unsupervised extraction and comparison of semantic information by mimicking skills for the identification of clauses and possible verb...
Web text, using natural language to describe a disaster event, contains a considerable amount of disaster information. Automatic extraction from web text of this disaster information (e.g., time, location, casualties, and disaster losses) is an impor...
With the rapid increase of public opinion data, the technology of Weibo text sentiment analysis plays a more and more significant role in monitoring network public opinion. Due to the sparseness and high-dimensionality of text data and the complex se...
This paper connects two large research areas, namely sentiment analysis and human–robot interaction. Emotion analysis, as a subfield of sentiment analysis, explores text data and, based on the characteristics of the text and generally known emo...
An important role in the fundamental analysis is played by the acquisition and analysis of various types of information about the company. Text documents are an increasingly important source of this information. Their accurate and quick analysis is a...
Text representation is an important topic in the field of natural language processing, which can effectively transfer knowledge to downstream tasks. To extract effective semantic information from text with unsupervised methods, this paper proposes a...
Airline customers will often complain to the relevant authorities if they encounter an unpleasant flight experience. The specific complaint information can directly reflect the various service problems encountered, so conducting in-depth research on...
Previous analysis has shown that the use of narrative devices in the biomedical literature has changed over time. The purpose of the present study was to measure the degree of narrativity in corpora of scientific abstracts obtained from Pubmed throug...
Virtual users generate a gigantic volume of unbalanced sentiments over various online crowd-sourcing platforms which consist of text, emojis, or a combination of both. Its accurate analysis brings profits to various industries and their services. The...
Researchers from different fields have studied the effects of the COVID-19 pandemic and published their results in peer-reviewed journals indexed in international databases such as Web of Science (WoS), Scopus, PubMed. Focusing on efficient methods f...
This study examines the impact of supply chain finance on corporate zero-carbon transition using data from Chinese A-share listed companies from 2008 to 2023. Through text analysis, this study constructs a corporate zero-carbon transition index conta...
The international development and social impact evidence community is divided about the use of machine-centered approaches in carrying out systematic reviews and maps. While some researchers argue that machine-centered approaches such as machine lear...
The Internet is now a central enabler for sharing sustainability information. Yet, such enablement is complicated through an exponentially increasing array of information. What is lacking in the digital economy are objective and transparent mechanism...
One stepping stone for reducing the maternal mortality is to identify severe maternal morbidity (SMM) using Electronic Health Records (EHRs). We aim to develop a pipeline to represent and classify the unstructured text of maternal progress notes in e...
In this paper, we compute the affective-aesthetic potential (AAP) of literary texts by using a simple sentiment analysis tool called SentiArt. In contrast to other established tools, SentiArt is based on publicly available vector space models (VSMs)...
As the importance of providing personalized services increases, various studies on personalized recommendation systems are actively being conducted. Among the many methods used for recommendation systems, the most widely used is collaborative filteri...
This study investigates the challenges of promoting accessibility for deaf teachers and students in higher education, focusing on the development of inclusive teaching materials. A qualitative case study was conducted in ten teacher training programm...
The main goal of this research is to analyze the perception of service in public sector companies in the city of Bogota via Twitter and text mining to identify areas, problems, and topics aiming for quality service improvement. To achieve this object...
Since cyber-attacks are ever-increasing in number, intensity, and variety, a strong need for a global, standardized cyber-security knowledge database has emerged as a means to prevent and fight cybercrime. Attempts already exist in this regard. The C...
Manufacturing companies face significant challenges in leveraging artificial intelligence for equipment management due to high infrastructure costs and limited availability of labeled data for failures. While most manufacturing AI applications focus...
Heterogeneous corpora including Chinese, English, and emoji symbols are increasing on platforms. Previous sentiment analysis models are unable to calculate emotional scores of heterogeneous corpora. They also struggle to effectively fuse emotional te...
Marine storm surge disasters occur frequently with complex and variable scenarios, causing severe casualties and economic losses in coastal areas. However, existing research still has limitations in the integrated analysis of event chain and emergenc...
Accurately predicting carbon trading price is challenging due to pronounced nonlinearity, non-stationarity, and sensitivity to diverse factors, including macroeconomic conditions, market sentiment, and climate policy. This study proposes a novel hybr...
Predicting stock market movement direction is a challenging task due to its fuzzy, chaotic, volatile, nonlinear, and complex nature. However, with advancements in artificial intelligence, abundant data availability, and improved computational capabil...
This study aims to understand the public’s perspectives, sentiments, attitudes, and discourses regarding the adoption, integration, and use of augmented reality and virtual reality in education and in general by analyzing social media data. Due...
Based upon social identity theory, having a strategic entrepreneurial orientation is crucial for ventures seeking funding, since entrepreneurial orientation (viewed as an entrepreneurial organizational culture) has a significant influence on investor...
Nowadays, based on mobile devices and internet, social network services (SNS) are common trends to everyone. Social opinions as public opinions are very important to the government, company, and a person. Analysis and decision of social polarity of S...
Children with disabilities were especially vulnerable during the COVID-19 pandemic, and policies designed to mitigate its effects were limited in addressing their needs. We analyzed Canadian policies related to children with disabilities and their fa...
Background: Q&A corpora generated through university student–AI mental health support tools may reveal how physical activity (PA) and psychosocial themes are represented in support-oriented text. However, the absence of individual-level dem...
With the extensive availability of social media platforms, Twitter has become a significant tool for the acquisition of peoples’ views, opinions, attitudes, and emotions towards certain entities. Within this frame of reference, sentiment analysis of...
Artificial Intelligence (AI) has emerged as a transformative force in the global economy, yet its contribution to environmentally sustainable productivity growth remains insufficiently understood. Using 33,017 firm-year observations from 4079 Chinese...
Background: Alzheimer’s disease (AD) and dementia are growing global health challenges, yet public understanding of these conditions remains poorly characterized. Methods: This study analyzed 17,578 English-language tweets from Twitter/X collec...
With the rapid advancement of medical foundation models, their deployment in clinical practice is increasingly required. However, privacy constraints of hospital-specific data make large-scale retraining infeasible, limiting model adaptability. To ad...
of 2