Sentiment Analysis ChatBot

A chatbot that analyzes a user's sentiment during a conversation.

Context & My Role

This project involves the development of a chatbot capable of analyzing user input and providing real-time insights into the sentiment expressed in conversations. The chatbot processes textual input from users, assigns a sentiment score (e.g., positive, neutral, or negative), and plots the results on a dynamic chart to visualize the sentiment trend over time. My role in this project focused on coding, primarily handling the sentiment analysis and data visualization components.

Description & Features

The system leverages Natural Language Processing (NLP) techniques to perform sentiment analysis, detecting emotional tone and intent within the user’s messages.

Each interaction is evaluated, and the sentiment scores are aggregated into a graphical representation using Matplotlib to help users track emotional patterns across multiple conversations.

The sentiment analysis is powered by the VADER sentiment analysis tool from the NLTK library, which effectively analyzes user input.

The entire system was programmed in Python.

Key features include:

Real-time sentiment analysis: Instantly processes user input and assigns sentiment labels (positive, negative, neutral) using VADER.

Dynamic chart visualization: Graphs sentiment data over time with Matplotlib, allowing users to observe emotional trends during a session.

User-friendly interface: Displays sentiment feedback clearly, helping users reflect on their emotional state.

Data tracking: Option to log past conversations and visualize trends over longer periods.

Here is a part of a sample conversation with a generated chart based on it.

Possible applications

This chatbot serves various applications, including mental health monitoring, where it can help users track their emotional well-being over time, providing insights into mood patterns and potential triggers. In the realm of customer feedback analysis, the chatbot can assess sentiment in user interactions, enabling businesses to gauge customer satisfaction and identify areas for improvement. Additionally, it offers a platform for personal journaling, allowing users to reflect on their emotions and experiences through data visualization. Recognizing its potential, my friend and I plan to further enhance this chatbot with more features in the future, aiming to expand its functionality and improve user experience.