"Comprehensive Subtheme Sentiment Analysis of Customer Reviews Using Advanced NLP Techniques"
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Updated
Jun 9, 2024 - Python
"Comprehensive Subtheme Sentiment Analysis of Customer Reviews Using Advanced NLP Techniques"
Natural Language Processing Python Project creating a Sentiment Analysis Classifier with NLTK's VADER and Huggingface's Roberta Transformers
Leveraging sentiment analysis and data augmentation to recreate recipe scoring algorithm with sparse data. Used MLPs and Gradient Boosting Regressors to compare regression metrics such as RMSE and MSE between raw data and raw data in conjunction with augmented data.
For this project, machine learning algorithms are used on amazon fine food reviews dataset to analyze if the given review is a positive review or a negative review.
Tarzan is an automated trading bot designed for swing trading penny stocks. It aggregates data from multiple sources, including social media, and financial news providers to place well-timed trades. The bot aims to maximize returns by holding positions for an average period of 1-14 days.
Sentiment analysis is part of the NLP techniques that consists in extracting emotions related to some raw texts.
Implementing VADER, RoBERTa and TextCNN on a twitter dataset from Kaggle
Script loads news via APIs, analyzes sentiments using VADER, displays results on Streamlit.
Updated replacement for vader-sentiment (vaderSentiment-js) that runs original vaderSentiment natively, using CPython.
Get a better understanding on Amazon reviews overall sentiment for food goods group (April, 2024)
A CLI tool to perform simple sentiment analysis written in Rust, using a Rust port of VADER.
The global supply chain is a crucial driver of the world economy, enabling the movement of goods and services worldwide and directly impacting economic growth. Analyzing sentiment surrounding the global supply chain in March 2024 reveals whether it's positive or negative, offering insights into improvements and disruptions.
Here you can find Sentiment Analysis, NamedEntity Recognition, Social Media Analysis and Topic Modeling. Some of which are completed using NLP.
Sentiment Analysis of Amazon Food Reviews to the customer ratings using VADER, TextBlob and Flair
This Repository contains Sentiment Analysis of Amazon Product Reviews using VADER and roBERTa on the following Dataset; https://www.kaggle.com/datasets/snap/amazon-fine-food-reviews
This project predicts stock market performance using sentiment analysis of news headline. The sentiment is visualized using Treemap
A lightweight Natural Language Parsing API
Sentiment analysis for tweets written in Portuguese-Brazil
2022년 1학기 팀 프로젝트 : COVID-19 기간 트위터 텍스트 데이터 분석
I performed sentiment analysis aimed at determining the sentiment of 50000 imDB movie reviews, whether they are positive, negative, or neutral. I employed various NLP approaches including lexicon based approaches, machine learning models, PLM models, and hybrid models, and assessed the performance on each type of model.
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