Sentiment analysis is the process of recognizing positive or negative attitudes in text. This
technique makes use of computational linguistics, text analysis, and natural language …

Introduction Globally, the prevalence of mental health problems, especially depression, is at
an all-time high. The objective of this study is to utilize machine learning models and …

Background Depression detection in social media has gained attention in recent years with
the help of natural language processing (NLP) techniques. Because of the low-resource …

Aspect-based sentiment analysis (ABSA) seeks to extract fine-grained sentiment information
by locating sentiments connected to particular elements in a text. Traditional sentiment …

This study aims to help in the area of depression screening in the Philippine setting,
focusing on the detection of depression symptoms through language use and behavior in …

Twitter, a social media site is a rich source of user generated text. So there must be a way to
analyze and classify the tweets posted on Twitter. Twitter data set has been used for the …

Internet has become a rich source of user-generated his/her general opinion for products,
services, social events, company strategies etc. This has created a need for emotion mining …

Starting from 2020, many countries are affected by COVID-19 pandemic. E-commerce is one
of the platforms that increases its use in this pandemic condition, and provides features such …

Sentiment analysis in hotel reviews has become a prominent field of research in computer
science, closely tied to machine learning and deep learning. The surge of online platforms …

The rapid expansion of online platforms has resulted in a deluge of user-generated content,
emphasizing the need for sentiment analysis to gauge public opinion. Aspect-based …