This is the presentation related to the project Sentiment analysis of Restaurant reviews

1. BHASKAR P
SKILLS BUILD EMAIL ID : BHASKARP1654@GMAIL.COM
AICTE STUDENT ID : STU6453B491385E71683207313
COLLEGE NAME : SRI VENKATESHWARA COLLEGE OF ENGINEERING, BENGALURU
COLLEGE STATE : KARNATAKA
INTERNSHIP DOMAIN : ARTIFICIAL INTELLIGENCE
START DATE-END DATE : 15/08/2023 -30/09/2023

2. SENTIMENT ANALYSIS
OF
RESTAURANT REVIEWS

3. PROJECT TITLE :- SENTIMENT ANALYSIS OF RESTARENT REVIEWS
 PROBLEM STATEMENT :- The
problem statement is to find whether the Review of the Restaurant is positive or Negative.
There are different types of reviews given by the customers after completing eating food. It
might be either positive and negative.so we need to predict the how much percentage of good
review of Entire dataset.

4. AGENDA :
 The main agenda of Sentiment Analysis of Restaurant Review project is to find whether the review is positive or
negative.
 objectives are:
 Helping individuals whether the Restaurant is Good or Bad. How much will the overall feedback for the Restaurant
and it will helpful for Restaurant as well to improve the food quality.
 Contents of the presentation:
 Project overview.
 knowing who are the end users.
 Solutions and value proposition of the project.
 About how did I customize the project.
 Models that are used for the project.
 Results of the project.
 Links or References for the project.

5. PROJECT OVERVIEW :
 Project Goal: Our project aims to understand how people feel about restaurants by looking at what they write in their reviews. We
want to figure out if they liked the restaurant (positive), didn't like it (negative), or felt neutral about it (neither good nor bad).
 What We Do:
 Collect Reviews: We gather lots of reviews people write about restaurants from websites like Yelp and TripAdvisor.
 Understand the Reviews: We use computers to read these reviews and figure out if the words in them express positive, negative,
or neutral feelings.
 Tell the Owners: We then tell restaurant owners what customers are saying. If customers are happy, we let the owners know. If
customers are not happy, we tell them what needs to be improved.
 Why It Matters:
 It helps restaurant owners make their customers happier by fixing problems.
 It helps people decide which restaurant to go to based on what others say.
 It helps researchers learn more about what people like and don't like in restaurants.
 What We Hope to Achieve:
 Make it easier for restaurants to make their customers happy.
 Help people find great places to eat.
 Learn more about what makes a restaurant popular and successful.

6. WHO ARE THE END USERS OF THIS PROJECT?
Sentiment analysis of restaurant reviews can be valuable to a variety of end users in the restaurant industry and beyond. Here
are some potential end users who can benefit from analyzing restaurant reviews for sentiment:
 Restaurant Owners and Managers:
 Restaurant owners and managers can use sentiment analysis to gauge customer satisfaction and identify areas for
improvement in their establishments. Positive sentiment can highlight what's working well, while negative sentiment can
pinpoint specific issues that need addressing.
 Chefs and Culinary Teams:
 Chefs and culinary teams can use sentiment analysis to gather feedback on their dishes.
 Marketing and PR Teams:
 Marketing and public relations teams can utilize sentiment analysis to monitor the online reputation of a restaurant.
Customer Service Teams:
 Customer service teams can identify dissatisfied customers and address their concerns promptly.
 Food Critics and Reviewers:
 Professional food critics and reviewers can use sentiment analysis to supplement their reviews.

7. YOUR SOLUTION AND ITS VALUE PROPOSITION :
 Solution:
 The sentiment analysis of restaurant review project offers an intelligent solution for understanding and leveraging customer
feedback in the restaurant industry. It involves collecting and analyzing restaurant reviews to determine whether customers
had positive, negative, or neutral experiences. Here's how it provides value:
 Accurate Sentiment Classification.
 The project employs advanced natural language processing (NLP) techniques and machine learning models to accurately
classify sentiments in reviews. This ensures that restaurant owners receive reliable feedback.
 Value Proposition:
 The value proposition of the Sentiment Analysis of Restaurant Review Project is multi-faceted and benefits various
stakeholders:
 Restaurant Owners and Managers:
 Value: Actionable insights, improved customer satisfaction, and increased revenue.
 Customers:
 Value: Better dining experiences, access to reliable reviews, and informed decision-making about where to
eat.

8. HOW DID I CUSTOMIZE THIS PROJECT ON MY OWN
 In Sentiment Analysis on Restaurant Review Project, first I take the Restaurant Reviews Dataset from Kaggle and I
loaded it into the google Drive.
 Then I imported the Dataset from Google drive to Colab notebook.
 By using libraries like pandas, numpy, matplotlib, seaborn , dataset is described.
 By using Stopwords, Porterstemmer can able to remove the unnecessary words like(a,an,the,so…etc) from the Dataframe.
 Finnaly By using Naive Baise Classifier can able to predict the whether the Review is good or Bad and the percentages of it.

9. SNAPSHOTS :

10. MODELLING
 I used MultinomialNB model of Naïve Based Classifier to classify the Positive And Negative Review.

11. RESULTS
 Accuracy score is 76.5%
 Precision score is 76.42%
 Recall score is 78.64%

12. LINKS
 GOOGLE COLAB : https://colab.research.google.com/drive/1Vk8t7Y15aVZ-
eWmXn2nITzHLbXCMfX6b?usp=sharing
 GITHUB LINK : https://github.com/bhaskar165470/Sentiment-Analysis-on-Restaurant-Reviews
REFERENCES :
• IBM skills build
• Edunet Foundation
• Youtube