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Analyzing a WhatsApp Conversation for both Textual Contents and Emotional Sentiments

Vineethalakshmi Boyapati1 , Jyothireddy Dronadula2 , Smilysrinidhi Gollapati3 , Udayasri Bodapati4 , Shakeelahmed Md5

  1. Dept. of Information Technology, Vasireddy Venkatadri Institute of Technology, Andhra Pradesh, India.
  2. Dept. of Information Technology, Vasireddy Venkatadri Institute of Technology, Andhra Pradesh, India.
  3. Dept. of Information Technology, Vasireddy Venkatadri Institute of Technology, Andhra Pradesh, India.
  4. Dept. of Information Technology, Vasireddy Venkatadri Institute of Technology, Andhra Pradesh, India.
  5. Dept. of Information Technology, Vasireddy Venkatadri Institute of Technology, Andhra Pradesh, India.

Section:Research Paper, Product Type: Journal Paper
Volume-11 , Issue-10 , Page no. 64-70, Oct-2023

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v11i10.6470

Online published on Oct 31, 2023

Copyright © Vineethalakshmi Boyapati, Jyothireddy Dronadula, Smilysrinidhi Gollapati, Udayasri Bodapati, Shakeelahmed Md . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Vineethalakshmi Boyapati, Jyothireddy Dronadula, Smilysrinidhi Gollapati, Udayasri Bodapati, Shakeelahmed Md, “Analyzing a WhatsApp Conversation for both Textual Contents and Emotional Sentiments,” International Journal of Computer Sciences and Engineering, Vol.11, Issue.10, pp.64-70, 2023.

MLA Style Citation: Vineethalakshmi Boyapati, Jyothireddy Dronadula, Smilysrinidhi Gollapati, Udayasri Bodapati, Shakeelahmed Md "Analyzing a WhatsApp Conversation for both Textual Contents and Emotional Sentiments." International Journal of Computer Sciences and Engineering 11.10 (2023): 64-70.

APA Style Citation: Vineethalakshmi Boyapati, Jyothireddy Dronadula, Smilysrinidhi Gollapati, Udayasri Bodapati, Shakeelahmed Md, (2023). Analyzing a WhatsApp Conversation for both Textual Contents and Emotional Sentiments. International Journal of Computer Sciences and Engineering, 11(10), 64-70.

BibTex Style Citation:
@article{Boyapati_2023,
author = {Vineethalakshmi Boyapati, Jyothireddy Dronadula, Smilysrinidhi Gollapati, Udayasri Bodapati, Shakeelahmed Md},
title = {Analyzing a WhatsApp Conversation for both Textual Contents and Emotional Sentiments},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2023},
volume = {11},
Issue = {10},
month = {10},
year = {2023},
issn = {2347-2693},
pages = {64-70},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5634},
doi = {https://doi.org/10.26438/ijcse/v11i10.6470}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v11i10.6470}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5634
TI - Analyzing a WhatsApp Conversation for both Textual Contents and Emotional Sentiments
T2 - International Journal of Computer Sciences and Engineering
AU - Vineethalakshmi Boyapati, Jyothireddy Dronadula, Smilysrinidhi Gollapati, Udayasri Bodapati, Shakeelahmed Md
PY - 2023
DA - 2023/10/31
PB - IJCSE, Indore, INDIA
SP - 64-70
IS - 10
VL - 11
SN - 2347-2693
ER -

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Abstract

WhatsApp, one of the most widely used instant messaging applications, has transformed the way people communicate globally. It presents an overview of WhatsApp chat analysis, a burgeoning field that leverages the vast amount of textual data generated through WhatsApp with the help of this platform users now have a convenient way to connect with their social networks, professional networks, and commercial partners. This give an analysis of the WhatsApp group data in order to determine the degree of participation and involvement among the group`s members. Additionally, it requires analyzing the most active day in the group, the quantity of messages sent on that date, the most active user overall, the list of active admins in the group, the overall user count, the quantity of posts made by each user in the group, and the most frequently used term on the platform. The analysis was able to demonstrate the level of participation of the various people on the specified WhatsApp group.

Key-Words / Index Term

WhatsApp Chat, Sentiment Analysis, Stream lit, Nature Language Processing, NMF, Emotion Analysis, Vader

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