CMPE 295B

Project Advisor –Prof. Hungwen Li

By

Abinaya Sampath

Mintu Abhraham

Purva Yadkikar

Neha Reddy Prodduturi

I Hungwen Li, certify that I have viewed the demo of this project and found the deliverables and outcomes satisfactory. Thereby I approve

this project

Project Advisor –Prof. Hungwen Li

Hungwen Li

* We have developed A tool which identify user’s opinion about a product and its features using user’s tweets.

* Product owners can used this tool to know the reviews about their product and its features, thereby make decisions to retain certain features that are good and enhance the features that need improvement.

* The solution also aims at analyzing the synonymous words and the combination of positive and negative words from tweets correctly .

* A recommendation system is also provided to give suggestions to the users.

* Perform sentiment analysis on public opinion related to smart phones and their features.

* This could help both the product owners as well as the Users

Objective * Extract the tweets from Twitter related to smart phones using

Twitter API.

* Analyze the overall sentiment of the product and display it to the users.

* Extract the words that represent features of Smart phones.

* Analyze the sentiment about the features and display the opinion to the users.

* We have designed a feature based sentiment analysis model to know people’s opinion about a smartphone and its features. This model is implemented using the following:

* Python - for application/business logic

* MongoDB - to store sentiment scores of products and features

* MySQL - to store user and recommendation related data

* Django - to provide the results for a request from python programs on the dashboard

* Bootstrap, HTML5 and CSS - to visually present the results on the UI dashboard (front-end)

We are grateful to Prof. Hungwen Li for providing necessary guidance and continuous encouragement. His valuable suggestion and remarks helped us a lot.

We thank our colleagues from San Jose State University who greatly assisted us during project research.

Words are inadequate in offering our thanks to the Project Advisor and Department Chair, SJSU for their encouragement and cooperation in carrying out the project work.

* We have decided to use big dataset and improve accuracy of our analysis.

*  We used Horton works in our current project, as it is open source. But Cloudera is also useful for analyzing, storing and managing big data.

*  It reduces deployment time and provides automated installation process.

*  We will also convert our web application into mobile application. Also we will continue our research on data preprocessing techniques to get best sentiments from tweets.