Sentiment Analysis using BERT on Social Brew Café

(using BERT)

Overview

This project utilizes the BERT (Bidirectional Encoder Representations from Transformers) model for sentiment analysis on the reviews provided by customers on the Social Brew Cafe, Pyrmont. BERT is a state-of-the-art natural language processing model that has demonstrated remarkable performance in various language understanding tasks.

Research Paper

For a detailed understanding of the BERT model, please refer to the research paper:

• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Dependencies

Make sure to install the following libraries to run the project:

pip install transformers torch requests beautifulsoup4 numpy pandas

Libraries used:

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
import requests
from bs4 import BeautifulSoup
import re

import numpy as np
import pandas as pd

Collecting Reviews

Reviews are collected from the following Yelp page: Social Brew Cafe - Pyrmont.. These reviews are loaded into a dataframe, and each sentence is evaluated on a scale of 1-5 using the BERT model, where 1 is the minimum and 5 is the maximum.