WhatsApp Analyser (WA) - Shong, Wei Jun; Mohamad Mohsin, Mohamad Farhan (Multidisciplinary Applied Research and Innovation, 2023)
This project provides an overview of WhatsApp Analyser (WA) where it analyses a group of discussion from WhatsApp. Nowadays, WhatsApp is one of the hot platforms for people all over the world to communicate as it allows people to conduct discussions in groups. During discussion, members can reply to messages, give comments, share ideas, and attach files on certain issues into groups. The discussion log remains in the group for a certain period. Without knowing the log contains valuable information, the user will normally clean the log to save storage. WhatsApp discussion logs can reveal information about user behavior. However, extracting the hidden knowledge from the log is difficult because it requires a user to have a programming background. In this project, we propose a system called WhatsApp Analyser (WA) to analyse log group discussion and extract hidden information. Through this system, users can select input discussion log files and extract the knowledge that is hidden in discussion messages such as the most active user, most active day, time highly active, maximum number of words, mostly used words and generate reports.  As a result, this system helps users to perform analysis on the hidden knowledge generated, which may be useful in decision-making or problem-solving processes.