Organizations communicate across many channels, yet official websites remain a controlled, authoritative space where firms articulate identity and strategy. This study examines how Croatia's top enterprises (n = 100) describe themselves on their websites and which emotional tones they use to...

Analyzing customer feedback, accessible on the Internet via social media platforms and tourism-related travel websites, empowers tourism service providers to pinpoint areas of success and concern. A notable approach to identifying factors determining customer satisfaction is the Kano method,...

This study analyzed 1480 job advertisements for business analysts using natural language processing (NLP) and sentiment analysis. While confirming the demand for technical, analytical and communication skills, the study reveals important patterns that expand upon existing knowledge....

The diverse rating scales used by brokerage firms pose significant challenges for aggregating analyst recommendations in financial research. We develop a momentum-based normalization framework that transforms heterogeneous rating changes into standardized sentiment signals using firm-relative,...

This research investigates the competing narratives surrounding decentralized cryptocurrencies, like Bitcoin, and state-backed Central Bank Digital Currencies (CBDCs). The primary contribution of this work is a conceptual model of these narratives, categorizing them into targeted positive and...

Addressing global environmental challenges necessitates an imperative shift in behavioural change and citizen engagement. This study centres on the integration of social media with Large Language Model (LLM) functionalities, sufficiently efficient in generating content relevant to the targeted...

This study investigates the media representation of female entrepreneurs in newspaper and magazine articles from 2014 to 2022. By employing a quantitative content analysis of 192 articles, the study examines dominant narratives, entrepreneurial identities, ethical behaviors, challenges depicted,...

The purpose of this study is to identify airline asymmetric attributes that affect customer satisfaction based on the three-factor theory and to build an Asymmetric Impact-Sentiment Analysis (AISA) for resource allocation prioritization. We identified food and beverage service as a basic factor;...

This study investigates how organisations respond to Corporate Sustainability Reporting Directive (CSRD) requirements through systematic analysis of corporate communications and sustainability reports. We employ multi-dimensional text mining analysis of 500 companies across 12 industries, using...

This study examines the evolution of sentiment in the sustainability reports of Turkish companies from 2014 to 2023, serving as an indicator of organisational change in response to shifting sustainability regulations. A longitudinal sample of corporate sustainability reports was subjected to...

This paper investigates the effects of air pollution on public mood using sentiment analysis of geolocated social media data. Analyzing approximately 7 million twitter posts from the United States in July 2015, we examine how fluctuations in air quality caused by Canadian wildfires influence...

Purpose - is to provide evidence of how social networks act as an indispensable channel in the cryptocurrency phenomenon and its public perception, analysing the context in which it occurs, as well as the patterns followed and the most commonly used channels. Research methodology - this article...

Massive Open Online Courses (MOOCs) and the broad adoption of distance learning over the past few years have caused a remarkable shift in the educational landscape. However, the vast majority of available MOOCs often challenge learners in selecting courses that align with their academic goals,...

This work introduces a novel method for sentiment analysis in the stock market by combining Deep Neural Networks (DNN) and an improved Firefly Algorithm (FA). It is essential to comprehend investor sentiment in financial markets in order to forecast stock price movements and make wise investment...

This study examines the impact of the tone used in communication by two major international organizations, the United Nations (UN) and the International Monetary Fund (IMF), on electricity prices in Türkiye, an energy-dependent developing country with the highest-growing energy demand among...

This study examines the impact of financial disclosure timing on the sentiment of corporate reports within an emerging market context. Leveraging a comprehensive dataset covering quarterly reports from all firms listed on Borsa Istanbul between 2018 and 2023, we categorized firms into three...

Accurate gold price forecasting is essential for informed financial decision-making, as gold is sensitive to economic, political, and social factors. This study presents a hybrid framework for multivariate gold price prediction that integrates classical econometric modelling, traditional machine...

This study investigates the integration of sentiment analysis with machine learning models to forecast stock price movements using the Nvidia Corporation as a case study. Sentiment scores were derived from Nvidia-related financial news headlines using two sentiment analysis tools: FinBERT, a...

In the context of the impressive development of Big Data, AI algorithms have proven their efficiency in processing and analyzing large volumes of data. Price prediction was no exception. In the modern economic fields, the need for advanced prediction models, with increased efficiency, has become...

User-generated content continues to shape global tourism trends, yet Africa's growing tourism sector has received limited attention. This study addresses this gap by investigating tourist sentiments and satisfaction across ten African destinations from 2018 to 2023. Employing a mixed method...

Central bank communication has become a crucial tool for steering the monetary policy stance and shaping the outlook of market participants. Traditionally, analyzing central bank communication required substantial human effort, expertise, and resources, making the process time-consuming. The...

This systematic review investigates sentiment analysis of news headlines in the banking sector, a field susceptible to public sentiment, as demonstrated by phenomena like bank runs leading to rapid deposit withdrawals. We trace the evolution of analytic methods from traditional machine learning...

This study explores consumer sentiments towards telemedicine and telehealth services using data from various digital platforms. Leveraging Brand24 for real-time data collection and NVivo 14 for in-depth content analysis, the research examines netizen reviews to reveal their perceptions,...

This study aims to address the common issue of biased estimation errors in time series modeling by analyzing the error in locating ideal hyperparameters and defining appropriate validation methods. Specifically, it focuses on predicting the stock price of Bank Rakyat Indonesia using a...

In behavioural economics, Big Social Data plays a crucial role in predicting stock market trends. This study aims to compare the effectiveness of the VAR model and the LSTM neural network in forecasting the relationship between social media and stock markets. Two hypotheses guide this work:...

This study extracts signals from more than 530,000 news articles from 15 large Swiss newspapers to measure economic sentiment in Switzerland. Economic sentiment includes consumer sentiment and business sentiment. The research period for the text sentiment analysis ranges from 2016 to 2022, so...

Anthropomorphic AI-based chatbots are reshaping human-machine interactions, enabling users to form emotional bonds with AI agents. While these systems provide companionship and engagement, they also raise concerns regarding digital entrapment: a complex and circular causal loop, progressively...

This study investigates the media representation of female entrepreneurs in newspaper and magazine articles from 2014 to 2022. By employing a quantitative content analysis of 192 articles, the study examines dominant narratives, entrepreneurial identities, ethical behaviors, challenges depicted,...

Central bank communication has become a crucial tool for steering the monetary policy stance and shaping the outlook of market participants. Traditionally, analyzing central bank communication required substantial human effort, expertise, and resources, making the process time-consuming. The...