Analyzing Whatsapp Chat Data for User Interaction and Sentiment: A Comprehensive Approach

Author(s)	Mohammad Ali Siddiqui, Krishna Agarwal
Country	India
Abstract	The proliferation of instant messaging applications like WhatsApp has revolutionized personal and professional communication. This research paper presents a detailed methodology for analyzing WhatsApp chat data to gain insights into user interaction patterns, message content, and sentiment. By employing various data preprocessing techniques and analytical methods, the project extracts meaningful statistics, generates word clouds, identifies frequently used words and emojis, analyzes user activity over time, and calculates response times. Additionally, sentiment analysis is performed to understand the emotional tone of conversations. This study provides a framework for leveraging chat data to inform social behavior analysis, digital communication studies, and personalized user experiences.
Keywords	WhatsApp Chat Analysis, Text Mining, Natural Language Processing (NLP), Sentiment Analysis, Response Time Analysis, User Interaction Patterns, Social Behavior Analysis
Field	Engineering
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-06-05
Cite This	Analyzing Whatsapp Chat Data for User Interaction and Sentiment: A Comprehensive Approach - Mohammad Ali Siddiqui, Krishna Agarwal - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.22069
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.22069
Short DOI	https://doi.org/gtxrmm

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International Journal For Multidisciplinary Research