A survey of sentiment analysis: Approaches, datasets, and future research
Sentiment analysis is a critical subfield of natural language processing that focuses on
categorizing text into three primary sentiments: positive, negative, and neutral. With the …
categorizing text into three primary sentiments: positive, negative, and neutral. With the …
Roberta-Gru: A hybrid deep learning model for enhanced sentiment analysis
This paper proposes a novel hybrid model for sentiment analysis. The model leverages the
strengths of both the Transformer model, represented by the Robustly Optimized BERT …
strengths of both the Transformer model, represented by the Robustly Optimized BERT …
A literature review on sentiment analysis techniques involving social media platforms
S Garg, DS Panwar, A Gupta… - 2020 Sixth International …, 2020 - ieeexplore.ieee.org
Sentiment analysis refers to the active field of Natural language processing that extracts the
attitude and emotion of a human being. With the growth of social media, more people are …
attitude and emotion of a human being. With the growth of social media, more people are …
A heterogeneous stacking ensemble based sentiment analysis framework using multiple word embeddings
B Subba, S Kumari - Computational Intelligence, 2022 - Wiley Online Library
Word embedding techniques have been proposed in the literature to analyze and determine
the sentiments expressed in various textual documents such as social media posts, online …
the sentiments expressed in various textual documents such as social media posts, online …
Mucs@ text-lt-edi@ acl 2022: Detecting sign of depression from social media text using supervised learning approach
Social media has seen enormous growth in its users recently and knowingly or unknowingly
the behavior of a person will be reflected in the comments she/he posts on social media …
the behavior of a person will be reflected in the comments she/he posts on social media …
[HTML][HTML] Classification of twitter vaping discourse using BERTweet: comparative deep learning study
Background: Twitter provides a valuable platform for the surveillance and monitoring of
public health topics; however, manually categorizing large quantities of Twitter data is labor …
public health topics; however, manually categorizing large quantities of Twitter data is labor …
Prediction of dogecoin price using deep learning and social media trends
INTRODUCTION: Cryptocurrency is a digital, decentralized form of money based on
blockchain technology, which makes it the most secure method of making a transaction …
blockchain technology, which makes it the most secure method of making a transaction …
A sentiment analysis anomaly detection system for cyber intelligence
R Maisano, GL Foresti - International Journal of Neural Systems, 2023 - World Scientific
Considering the 2030 United Nations intent of world connection, Cyber Intelligence
becomes the main area of the human dimension able of inflicting changes in geopolitical …
becomes the main area of the human dimension able of inflicting changes in geopolitical …
Feature engineering vs bert on twitter data
R Gani, L Chalaguine - arXiv preprint arXiv:2210.16168, 2022 - arxiv.org
In this paper, we compare the performances of traditional machine learning models using
feature engineering and word vectors and the state-of-the-art language model BERT using …
feature engineering and word vectors and the state-of-the-art language model BERT using …
MUCS@ LT-EDI2023: Detecting Signs of Depression in Social Media Text
Depression can lead to significant changes in individuals' posts on social media which is a
important task to identify. Automated techniques must be created for the identification task as …
important task to identify. Automated techniques must be created for the identification task as …