Sentiment Analysis Projects for Final Year

Byadmin Project Ideas

Sentiment Analysis Projects for final year students and the latest project ideas for BSc, BS, BE, BEng, MSc, MS, BCA, MCA, BTech and MTech. These Sentiment Analysis projects play an important role in a student’s final year learning. These projects help students understand real applications and apply technical concepts in a practical way. Choosing the right Sentiment Analysis project also improves practical knowledge and builds confidence for future careers.

Sentiment Analysis Projects for Final Year

Latest Sentiment Analysis Project Ideas

  1. Fake Product Review Monitoring & Removal For Genuine Ratings Php
    This project helps users find real reviews of products online. It detects fake reviews by tracking patterns and IP addresses of users posting reviews. If a review is found to be fake, the system alerts the admin to remove it. This ensures that people can trust the ratings before buying a product.
  2. Data Mining For Automated Personality Classification
    This project builds a system that can automatically figure out a person’s personality by studying their past behavior. It collects and analyzes large amounts of user data to learn patterns. Using these patterns, it can predict the personality of new users. The system can help social networks, advertisers, and government agencies understand people better.
  3. Opinion Mining For Restaurant Reviews
    This project is a web application that helps users rate and review restaurants automatically. It reads customer feedback and detects whether the comments are positive, negative, or neutral. Based on this, it gives a rating to the restaurant. The system also allows users to view restaurants, post their opinions, and helps people find good places to eat.
  4. TV Show Popularity Analysis Using Data Mining
    This project studies how popular TV shows are by looking at viewers’ comments. It collects details like age, gender, and location along with what people say about the shows. The system then analyzes these comments to see if viewers like or dislike a show. The results are shown in graphs and charts so anyone can see which shows are most popular.
  5. Detecting Fraud Apps Using Sentiment Analysis
    This project helps identify fake mobile applications using user reviews and comments. It studies what people feel about an app by analyzing their feedback. The system helps decide whether an app is genuine or fraud. This makes it safer for users to choose apps from app stores.
  6. Sentiment Analysis For Product Rating
    This project is a system that reads user comments on products and figures out if people like or dislike them. It shows a rating for each product based on these comments. Users can view products, share their opinions, and see what others think. The system helps people choose the right product and also makes them aware of new products.
  7. Opinion Mining For Comment Sentiment Analysis
    This project is a web application that studies user comments to find out how people feel about a post. It reads comments and decides if the topic is good, bad, or worst. Users can post comments, see reviews, and check their own status. Admins can add posts and maintain a list of sentiment words to help the system rate the comments accurately.
  8. Website Evaluation Using Opinion Mining
    This project is about a system that checks how good and trustworthy a website is by looking at what users say about it. Users can comment on websites, and the system reads these comments to decide if a website is genuine, delivers products on time, and gives good support. It uses a method called opinion mining to understand if the comments are positive or negative. This helps people make safe choices when shopping or using websites online.
  9. Opinion Mining For Hotel Rating Through Reviews
    This project studies hotel reviews shared by users on the internet. It automatically understands whether a review is positive or negative. Based on many reviews, the system gives an overall rating to each hotel. This helps people choose good hotels quickly without reading many reviews.
  10. Product Review Analysis For Genuine Rating
    This project is a system that helps people find the best products by analyzing user reviews. Users can rate and write reviews for different products after logging in. The system checks the reviews and decides if a product is good, bad, or worst based on positive or negative words. Admins can add products, descriptions, and buying links, making it easier for users to choose reliable products.
  11. Document Sentiment Analysis Using Opinion Mining
    This project uses computers to read and understand what people write in text. It finds words that show feelings and then decides if the writer feels positive, negative, or neutral about something. The system looks at user comments or documents and tags them with a sentiment score. It helps to see what most people think in the text data easily.
  12. Cooking Recipe Rating Based On Sentiment Analysis
    This project creates a system where users can post and rate cooking recipes. Visitors can comment on recipes and share their experiences. The system uses smart analysis to understand the feelings in comments and summarize important points. This helps other users find accurate and reliable recipes quickly.
  13. E Commerce Product Rating Based On Customer Review Mining
    This project helps online shopping websites understand what customers think about their products and services. Users can buy products and give reviews on the website. The system reads these reviews, finds important words, and decides if the feedback is positive or negative. Based on this, it gives a rating to the product and service to help companies improve.
  14. Data Mining for Sales Prediction in Tourism Industry
    This project uses data mining to predict sales in the tourism industry. It looks at two types of information: the number of times users order travel packages and the opinions they write in comments. The system counts popular packages and analyzes the comments to see if they are positive or negative. By combining these, it can estimate which packages will sell more in the future.
  15. Food Recipes Rating System based on Emotional Analysis
    This project is a Food Recipes Rating System that helps users find good recipes online. Users can post recipes and others can rate and comment on them. The system reads the comments and uses emotional analysis to understand if people liked the recipe or not. It then automatically gives a rating to help everyone choose the best recipes easily.
  16. Filtering political sentiment in social media from textual information
    This project studies how social media posts show support or opposition toward political ideas. It looks at the words people use in online posts and comments. The system learns common patterns from earlier examples. It then decides whether a new post shows a positive or negative political feeling.
  17. Sentiment Based Movie Rating System
    This project creates an online system that rates movies by understanding what people feel from their reviews. Users can freely post comments about movies on the platform. The system reads these comments and decides whether the opinion is positive or negative. Based on all reviews, it automatically gives a final movie rating and shows top rated movies.
  18. Student Feedback Review System using Python
    This project is a Student Feedback Review System built with Python. It allows students to give feedback about their classes and teachers easily. The system collects and analyzes these reviews to show summaries and insights. It helps schools and colleges improve teaching quality and understand students better.
  19. Social Media Community Using Optimized Clustering Algorithm
    This project creates a system that groups social media users based on their messages and interactions. It analyzes user comments and networks to find patterns in discussions. The system then identifies communities like film fans or political followers. This helps to understand how people participate and respond on social media.
  20. Hotel Recommendation System Based on Hybrid Recommendation Model
    This project is a web-based system that helps users find the best hotels by analyzing reviews. It reads what people write about hotels and figures out if the feedback is positive, negative, or neutral. The system then summarizes reviews and gives ratings for hotels. Users can see recommendations based on their searches and previous visits, making it easier to choose a suitable hotel before traveling.
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