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In the contemporary era, social media platforms amass an extensive volume of social data contributed by their users. In order to promptly grasp the opinions and emotional inclinations of individuals regarding a product or event, it becomes…

Sentiment classification is an important process in understanding people's perception towards a product, service, or topic. Many natural language processing models have been proposed to solve the sentiment classification problem. However,…

Artificial intelligence and machine learning have significantly bolstered the technological world. This paper explores the potential of transfer learning in natural language processing focusing mainly on sentiment analysis. The models…

Digital platforms have an ever-expanding user base, and act as a hub for communication, business, and connectivity. However, this has also allowed for the spread of hate speech and misogyny. Artificial intelligence models have emerged as an…

Rapid increase in the volume of sentiment rich social media on the web has resulted in an increased interest among researchers regarding Sentimental Analysis and opinion mining. However, with so much social media available on the web,…

In recent years, there has been increased interest in building predictive models that harness natural language processing and machine learning techniques to detect emotions from various text sources, including social media posts,…

User and product information associated with a review is useful for sentiment polarity prediction. Typical approaches incorporating such information focus on modeling users and products as implicitly learned representation vectors. Most do…

Sentiment Analysis for Indian Languages (SAIL)-Code Mixed tools contest aimed at identifying the sentence level sentiment polarity of the code-mixed dataset of Indian languages pairs (Hi-En, Ben-Hi-En). Hi-En dataset is henceforth referred…

Sentiment analysis is the task of automatic analysis of opinions and emotions of users towards an entity or some aspect of that entity. Political Sentiment Analysis of social media helps the political strategists to scrutinize the…

Social Media has seen a tremendous growth in the last decade and is continuing to grow at a rapid pace. With such adoption, it is increasingly becoming a rich source of data for opinion mining and sentiment analysis. The detection and…

In today's interconnected society, social media platforms have become an important part of our lives, where individuals virtually express their thoughts, emotions, and moods. These expressions offer valuable insights into their mental…

Sentiment Analysis is a well-studied field of Natural Language Processing. However, the rapid growth of social media and noisy content within them poses significant challenges in addressing this problem with well-established methods and…

This paper enhances the study of sentiment analysis for the Central Kurdish language by integrating the Bidirectional Encoder Representations from Transformers (BERT) into Natural Language Processing techniques. Kurdish is a low-resourced…

Nowadays, people from all around the world use social media sites to share information. Twitter for example is a platform in which users send, read posts known as tweets and interact with different communities. Users share their daily…

BERT has revolutionized the NLP field by enabling transfer learning with large language models that can capture complex textual patterns, reaching the state-of-the-art for an expressive number of NLP applications. For text classification…

Traditional sentiment construction in finance relies heavily on the dictionary-based approach, with a few exceptions using simple machine learning techniques such as Naive Bayes classifier. While the current literature has not yet invoked…

Code mixing is a common phenomena in multilingual societies where people switch from one language to another for various reasons. Recent advances in public communication over different social media sites have led to an increase in the…

This paper proposes an interpretable non-model sharing collaborative data analysis method as one of the federated learning systems, which is an emerging technology to analyze distributed data. Analyzing distributed data is essential in many…

The rise in popularity and ubiquity of Twitter has made sentiment analysis of tweets an important and well-covered area of research. However, the 140 character limit imposed on tweets makes it hard to use standard linguistic methods for…

Predictive analysis of social media data has attracted considerable attention from the research community as well as the business world because of the essential and actionable information it can provide. Over the years, extensive…