Charactolyzer (A Whatsapp Group Chat Analyzer)
"WhatsApp Chat Analyzer- Charactolyzer: An intelligent machine learning application that leverages advanced algorithms to analyze and extract valuable insights from WhatsApp conversations."
Created on 15th May 2023
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Charactolyzer (A Whatsapp Group Chat Analyzer)
"WhatsApp Chat Analyzer- Charactolyzer: An intelligent machine learning application that leverages advanced algorithms to analyze and extract valuable insights from WhatsApp conversations."
The problem Charactolyzer (A Whatsapp Group Chat Analyzer) solves
Sentiment Analysis: The application can analyze the sentiment of conversations in WhatsApp chats, helping users understand the overall tone and emotions expressed within the chat.
Topic Extraction: It can identify and extract key topics and themes discussed in the chat, providing users with a summary or overview of the main subjects covered.
User Behavior Analysis: By analyzing patterns and trends in conversations, the application can provide insights into individual users' communication habits, such as their most frequently used words or their active participation in the chat.
Spam Detection: The application can detect and flag potential spam messages or unwanted promotional content within the chat, helping users filter out irrelevant or intrusive information by saying
Language Translation: With machine learning algorithms, the application can automatically translate messages in different languages, facilitating multilingual communication within the chat group.
Challenges we ran into
Overcoming Challenges in Text Extraction and Data Cleaning from WhatsApp Chats
Abstract:
WhatsApp has become one of the most popular messaging platforms globally, facilitating seamless communication between individuals and groups. However, extracting meaningful text data from WhatsApp chats and effectively cleaning unnecessary information present unique challenges. In this article, we delve into the intricacies of text extraction and data cleaning from WhatsApp chats, discussing the hurdles faced and providing potential solutions to address these issues.
Introduction
WhatsApp chats contain a wealth of information, ranging from personal conversations to professional collaborations. Extracting and analyzing this data can provide valuable insights for various purposes such as sentiment analysis, user behavior analysis, topic extraction, and spam detection. However, the unstructured nature of WhatsApp chats presents challenges in extracting text and cleaning irrelevant data.
Formatting Variations:
WhatsApp chats exhibit diverse formatting styles, including timestamps, user names, message bubbles, emojis, media files, and system notifications. These variations make it difficult to extract only the relevant text content for further analysis.