Recognizing Textual Entailment (RTE) was proposed as a unified evaluation framework to
compare semantic understanding of different NLP systems. In this survey paper, we provide …

Financial and economic news is continuously monitored by financial market participants.
According to the efficient market hypothesis, all past information is reflected in stock prices …

In the task of text sentiment analysis, the main problem that we face is that the traditional
word vectors represent lack of polysemy, the Recurrent Neural Network cannot be trained in …

The purpose of this paper is to consider one of the most important modern technologies,
namely: Natural Language Processing (NLP) and the machine learning algorithms related to …

Lexicon-based sentiment analysis in finance leverages specialized, manually annotated
lexicons created by human experts to extract sentiment from financial texts effectively …

In a global world, no country, market, or economy is isolated. Interconnectivity is becoming a
fundamental feature of economic systems, including macroeconomic trends, traditional …

With the evolution of big data and information technology, sentiment analysis has become a
research hotspot in the financial market. Researchers are increasingly focused on improving …

Background In health care research, patient-reported opinions are a critical element of
personalized medicine and contribute to optimal health care delivery. The importance of …

In a world where no country, market, or economy is an island, interconnectivity is becoming
a fundamental feature of almost all social and economic systems. In the case of digital …

Accurate extraction and categorisation of large amount of textual data is pivotal for efficient
decision-making in this rapidly changing domain of finance. In this technical paper, the …