With the technology development of natural language processing, many researchers have
studied Machine Learning (ML), Deep Learning (DL), monolingual Sentiment Analysis (SA) …

Cross-lingual sentiment analysis (CLSA) leverages one or several source languages to help
the low-resource languages to perform sentiment analysis. Therefore, the problem of lack of …

[Objective] This paper teases out the research context of cross-lingual sentiment analysis
(CLSA).[Coverage] We searched “TS= cross lingual sentiment OR cross lingual word …

The usefulness of understanding public opinion across linguistic boundaries cannot be
overstated. Sentiment analysis is a great method for learning more about users' opinions …

The rise of the Internet has enabled people to express their opinions on various subjects
through social media, blogs, and website comments. As a result, there has been a significant …

Sentiment Analysis (SA) is one of the most active research areas in the Natural Language
Processing (NLP) field due to its potential for business and society. With the development of …

Sentiment analysis is an essential task in natural language processing that involves
identifying a text's polarity, whether it expresses positive, negative, or neutral sentiments …

With the emergence of Pre-trained Language Models (PLMs) and the success of large scale,
the field of Natural Language Processing (NLP) has achieved tremendous development …

Sentiment analysis is a rapidly growing field that aims to extract and analyze the opinions
and emotions expressed in text. With the increasing popularity of social media and the …

The inception and rapid growth of the Web, social media, and other online forums have
resulted in the continuous and rapid generation of opinionated textual data. Several real …