In this notebook we will be doing some sentiment analysis in python using three different techniques:
- VADER (Valence Aware Dictionary and sEntiment Reasoner) - Bag of words approach
- Roberta Pretrained Model from 🤗
- Huggingface Pipeline
VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media. It is fully open-sourced under the [MIT License].
RoBERTa is a transformers model pretrained on a large corpus of English data in a self-supervised fashion. This means it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts.
A Transformer pipeline describes the flow of data from origin systems to destination systems and defines how to transform the data along the way. Sample Pipelines. Transformer provides sample pipelines that you can use to learn about Transformer features or as a template for building your own pipelines.
Kaggle Notebook - https://www.kaggle.com/code/najrulansari/sentiment-analysis/edit
Dataset - Amazon Fine Food Reviews
Dataset link - https://www.kaggle.com/datasets/snap/amazon-fine-food-reviews