Social media chat data visualization

Social media chat data visualization

There are various existing applications that analyzes the chat log for instant messaging applications such as WhatsApp and Telegram. The primary goal of this project is to aid in a quick understanding of a long chat history. This project makes use of Term Frequency-Inverse Document Frequency (TF-IDF...

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Bibliographic Details
Main Author: Tan, Royce Chun Wei
Other Authors: Cham Tat Jen
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Document and text processing
Online Access:https://hdl.handle.net/10356/166155
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Institution: Nanyang Technological University
Language: English
Description
Summary:There are various existing applications that analyzes the chat log for instant messaging applications such as WhatsApp and Telegram. The primary goal of this project is to aid in a quick understanding of a long chat history. This project makes use of Term Frequency-Inverse Document Frequency (TF-IDF), an algorithm for Natural Language Processing, to identify important words or possibly topics being discussed every week throughout the chat history. This project also features other functions to display who sent the longest messages, generate a word cloud, frequency of words, and the most popular emoji within the group or a one-to-one chat log. The author also explored using various parameters to create a sensible output.

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