Sentiment Analyzer A Chrome extension that allows you to analyze the sentiment of highlighted text on web pages.
Installation Clone this repository or download the ZIP file and extract it. Open the Chrome browser and go to chrome://extensions. Turn on the Developer mode. Click on the "Load unpacked" button and select the folder where you extracted the extension files. How to use Navigate to a webpage where you want to analyze the sentiment of text. Highlight the text that you want to analyze. Right-click on the highlighted text and select "Analyze Sentiment" from the context menu. The extension will display the sentiment analysis result in a popup window. Technologies used JavaScript HTML CSS Credits This extension was created by Oluwadara. If you have any questions or suggestions, please feel free to contact me.
Inspiration: The inspiration for this project came from a personal need for a tool that could quickly analyze the sentiment of text on web pages. As a frequent user of social media and online news sources, I often found myself wanting to gauge the overall sentiment of a piece of content or the comments section. However, I didn't want to spend a lot of time manually analyzing the text. This project aims to provide a simple solution to this problem.
Motive: The purpose of this project is to provide a quick and easy way for users to analyze the sentiment of text on web pages. This tool will be useful for individuals who want to quickly gauge the overall sentiment of a piece of content or the comments section. It will also be helpful for businesses and organizations that want to monitor the sentiment of their brand or products online.
Aim: The goal of this project is to create a simple and user-friendly Chrome extension that can quickly analyze the sentiment of text on web pages. The extension will use the Sentiment API to provide accurate and reliable sentiment analysis results. In the future, I plan to expand this project by adding support for additional languages and improving the accuracy of the sentiment analysis.
Challenges: The main challenge faced during the development of this project was learning how to create a Chrome extension from scratch. I had to research and understand the various components of a Chrome extension, such as the manifest file, background script, and content script. Additionally, integrating the Sentiment API into the extension and handling errors and exceptions was also a challenge.
Achievements: I am proud of being able to successfully create a functioning Chrome extension that provides sentiment analysis results for text on web pages. I also gained valuable experience in working with Chrome extensions and integrating APIs. Overall, this project has allowed me to improve my skills in web development and programming.