This study investigates how organizations may increase innovation and productivity through the Metaverse environment efficacy (MVEE), Artificial intelligence usage (AIU), Internet of Things usage (IoTU), and Big Data Analytics usage (BDAU). The ...

• Identifies the applications of AI, IoT, and BDA to drive firm performance.
• Lays out the role of AI, IoT, and BDA in creating a dynamic metaverse ecosystem.
• Explains the revolutionary potential of augmented reality in business ...

Company disclosures greatly aid in the process of financial decision-making; therefore, they are consulted by financial investors and automated traders before exercising ownership in stocks. While humans are usually able to correctly interpret the ...

Watching online videos is a major leisure activity among Internet users. The largest video website, YouTube, stores billions of videos on its servers. Thus, previous studies have applied automatic video categorization methods to enable users to find ...

Social media has become the largest data source of public opinion. The application of sentiment analysis to social media texts has great potential, but faces great challenges because of domain heterogeneity. Sentiment orientation of words varies by ...

The growth of financial texts in the wake of big data has challenged most organizations and brought escalating demands for analysis tools. In general, text streams are more challenging to handle than numeric data streams. Text streams are unstructured ...

Decision support for financial news using natural language processing requires robust methods that process all sentences correctly, including those that are negated. To predict the corresponding negation scope, related literature commonly utilizes rule-...

Due to the huge popularity of microblogging services, microblogs have become important sources of customer opinions. Sentiment analysis systems can provide useful knowledge to decision support systems and decision makers by aggregating and summarizing ...

Lexicon acquisition is a key issue for sentiment analysis. This paper presents a novel and fast approach for creating stock market lexicons. The approach is based on statistical measures applied over a vast set of labeled messages from StockTwits, which ...

Event extraction, a specialized stream of information extraction rooted back into the 1980s, has greatly gained in popularity due to the advent of big data and the developments in the related fields of text mining and natural language processing. ...

The exploitation of structural aspects of content is becoming increasingly popular in rule-based polarity classification systems. Such systems typically weight the sentiment conveyed by text segments in accordance with these segments' roles in the ...

Twitter is a microblogging site in which users can post updates (tweets) to friends (followers). It has become an immense dataset of the so-called sentiments. In this paper, we introduce an approach that automatically classifies the sentiment of tweets ...

In the era of Web 2.0, there has been an explosive growth of consumer-contributed comments at social media and electronic commerce Web sites. Applying state-of-the-art social analytics methodology to analyze the sentiments embedded in these consumer ...

Twitter has become one of the most popular micro-blogging platform recently. Millions of users can share their thoughts and opinions about different aspects and events on the micro-blogging platform. Therefore, Twitter is considered as a rich source of ...

With the rapid development of information technologies, user-generated contents can be conveniently posted online. While individuals, businesses, and governments are interested in evaluating the sentiments behind this content, there are no consistent ...

With the globalization of business environments and rapid emergence and proliferation of the Internet, organizations or individuals often generate, acquire, and then archive documents written in different languages (i.e., poly-lingual documents). ...

Companies increasingly use business process modeling for documenting and redesigning their operations. However, due to the size of such modeling initiatives, they often struggle with the quality assurance of their model collections. While many model ...

Despite their similar meanings, near-synonyms may have different usages in different contexts, and the development of algorithms that can verify whether near-synonyms do match their given contexts has been the focus of increasing concern. Such ...

Artificial neural network approach is a well-known method that is a useful tool for time series forecasting. Since real life time series can generally contain both linear and nonlinear components, hybrid approaches which can model both these two ...

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy).This article has been retracted at the request of the Authors.This article contains significant overlap with a paper ...

A growing body of work has highlighted the challenges of identifying the stance that a speaker holds towards a particular topic, a task that involves identifying a holistic subjective disposition. We examine stance classification on a corpus of 4731 ...