International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 10 Issue: 04 | Apr 2023 www.irjet.net p-ISSN: 2395-0072

WhatsApp Activity Analyzer

Asst. Prof. Sadia Patka1, Harsh Tandekar2, Asrar Sheikh3, Rakshit Lade4, MD. Farhan Khan5,
Tahseen Qureshi6, Sahil Dongre7

1Professor, Computer Science and Engineering, A.C.E.T. Nagpur, Maharashtra, India

2B.E. Student, Computer Science and Engineering, A.C.E.T. Nagpur, Maharashtra, India
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Abstract - This study presents a WhatsApp chat analyzer practices. Overall, the WhatsApp chat analyser tool is a
tool that uses data analysis techniques to extract insights and valuable resource for anyone looking to analyse group chats
trends from group chat data. The tool can be used to analyze and extract meaningful insights from their conversations.
conversations and identify Topics, keywords, and recognition
of messages Chat Analyzer can be used to analyze group 2.LITERATURE REVIEW
conversations of all types, including educational, business, and
personal The results can be used to improve communication In the study of D. Bouhnik and M. Deshen, "WhatsApp for
strategies communication and increase overall productivity. Schools [1]: In this research is presented to find the
The tool is straightforward to apply and may be utilized by classroom communication between faculty and students by
every body with simple pc skills. Overall, WhatsApp Chat the high use of WhatsApp. WhatsApp groups in the
Analyzer has the potential to provide valuable insights and relationship between teacher and student, performed by the
facilitate effective communication. application activities and how they generally affect learning
and learning.
Key Words: WhatsApp chat analyser, Chat data, pandas,
NumPy, wordcloud, Matplotlib and Seaborn. Analysis of the use and impact of WhatsApp Messenger based
on a demo study [2]: There has been a lot of research and
1.INTRODUCTION impact analysis of the use and impact of WhatsApp. Some of
these studies investigated the impact of WhatsApp on
One of the most generally utilized informing applications students, while others were based on local populations. A
overall is WhatsApp. Group chats have become an essential study conducted in South India surveyed 18 to 23 year olds to
tool for communication, with people using them for explore the importance of WhatsApp among young people.
personal, educational, and business purposes. The amount of From this research, we found that students spend 8 hours a
data generated from these group chats can be overwhelming, day on WhatsApp and about 16 hours online. He uses
making it difficult to extract meaningful insights and WhatsApp to exchange pictures, audio and video files with his
patterns. friends. In addition, it turned out that the only application
that young people use while spending time on their
To overcome this challenge, we have created WhatsApp chat smartphones is WhatsApp.
analyser tools that use data processing to extract valuable
information from these conversations. These tools can In the research on content analysis of whatsapp chat [3]: A
provide insights on topics discussed, frequently used research project to analyse theWhatsApp application's
keywords, and the sentiment of messages exchanged. effectiveness in Karachi. The Study will be a crucial piece of
research for exploring the possibilities of emergence of
The WhatsApp chat analyser can be useful in various WhatsApp as the leading mobile messaging application in
domains, such as education, business, and social settings. In Pakistan. As a result of the introduction of mobile phones
education, instructors can analyse student group chats to and the development of digital technology, Pakistan's
identify topics of interest and monitor engagement. In communication landscape has undergone significant change.
business, managers can analyse group chats to identify areas In Pakistan, smart phones and social networking apps are
of improvement and evaluate team communication. In social becoming more and more popular, making communication
settings, individuals can use the tool to analyse their chat faster and simpler than ever. As a result of the changing
history and gain insights into their communication patterns. environment, the use of quantitative and qualitative research
This paper presents a comprehensive overview of the methods has increased over time. Methods for measuring the
WhatsApp chat analyser tool and its applications. It provides nature and impact of communication tools on human
an in-depth analysis of WhatsApp chat used to extract behavior were developed.
insights and the challenges associated with analysing
WhatsApp group chats. Additionally, this paper highlights The Impact of WhatsApp Messenger Usage o Students [4]:
the potential benefits and limitations of using WhatsApp Analysis of WhatsApp as a communication medium in an
chat analyser tools and their impact on communication emergency surgical team in a London hospital. According to

© 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 1105
 International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 10 Issue: 04 | Apr 2023 www.irjet.net p-ISSN: 2395-0072

their findings, emergency medicine team members 3.2. PROPOSED SYSTEM ARCHITECTURE
participating in the study used WhatsApp for 19 weeks.
Compare the sender and receiver of the message and the
response time and type of communication that occurs. Data Collection Data
Security events are reported. Their research shows that
WhatsApp can consume students' study time. WhatsApp Inspecting
takes a lot of study time for students and can be frustrating
while learning.

Also [5]: A comprehensive review of the evidence from Data Data

published documents and information on the use of PubMed Exploration Transformation
and other resources discusses the various uses of Instagram
and WhatsApp for health and well-being. It also explains the
main issues with using WhatsApp and Instagram. It is used in
health and medicine. Visualization
WhatsApp Chat Analysis with R [6]: WhatsApp group chat
data used for analysis is 1 year old (May 2015-May 2016),
totaling 55563 file texts and sometimes users. WhatsApp
Figure 1 -architecture diagram
group chat is based on age of usage, length of usage days,
Response levels, types of messages sent by each person in the
group (smiley, text, multiplayer), reusable age groups, etc. Open chat
The main characteristics given in this analysis are the types of
messages sent, year/month/week/day. /time, time (am/pm), group
sender's age, gender (male/female).

3.PROPOSED WORK Go to
This section includes the problem statement & proposed setting
system architecture.

3.1. PROBLEM STATEMENT Export Chat

Analyzing WhatsApp chat data can be a time-consuming
task, especially for large groups or long conversations. There
is a need for a tool that can quickly and accurately analyze
WhatsApp chat data to provide insights into the Without
conversation's topics discussed. The tool should also provide media
visualizations to help users better understand the data and
draw conclusions about the conversation's underlying
meaning. The solution should be easy to use, accessible, and Figure 2 – Steps involved in data collection
scalable to handle large amounts of data.
Module 1 : Data collection

The first step is to collect data from WhatsApp chats. This can
be done by exporting the chat history as a text file from the
WhatsApp application.

Module 2 : Data pre-processing

Once data is collected, it needs to be preprocessed so that it

can be used for analysis. This involves tasks such as removing
unnecessary characters, converting the text to lowercase, and
removing stop words.

© 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 1106
 International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 10 Issue: 04 | Apr 2023 www.irjet.net p-ISSN: 2395-0072

Module 3 : Data Transformation

The raw string has to be spilled into date, time, user

&messages (using regular expression) and be arranged in the
tabular form (using Pandas) this data frame will use as the
database.

Module 3 : Data Exploration

Here the collected data is read and processed to train a

classification model. Then the model is evaluated and
serialized.

 Top Statistics: Shows all messages, total words and

links to shared media.
 Monthly timeline: The chat frequency for a given
month is shown in this graph.
 The daily timeline: the number of messages during
the day is shown on this graph.
 Activity Map: provides a monthly breakdown of your Figure 4 -Monthly Timeline
busiest days and lowest workdays.
 Weekly Activity Map: Shows the most active time in
chat.
 Words cloud: the word that's very common and
often used.
 Most Busy Users
 Analysis of emoji usage: The most frequently used
emojis.

Module 4 : Data Visualization

This analyzed data will be then displayed in on the screen in
the form of graph for e.g.: line graph, bar graph, heat graph &
so on.

4. RESULT & DISCUSSION

Following are the results obtained from experiment: Figure 5- Daily Timeline

This displays various metrics related to group messaging Users can view frequency of messages over time using line
activity charts that show monthly and daily timelines.

Figure 3 – Top Statistics

In Top Statistics, including the total number of messages,

words, media, and links shared.
Figure 6 – Activity Map

© 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 1107
 International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 10 Issue: 04 | Apr 2023 www.irjet.net p-ISSN: 2395-0072

An activity map provides insight into the busiest month and

day for messaging activity, displayed in bar chart format.

Figure 8 - Wordcloud
Figure 7 – Weekly Activity Map
This word cloud is used to visualize & highlight the most
A weekly activity map shows hourly usage trends across commonly used words in messages.
different days using a heat map.

Figure 8 – Most Busy Users

Users can identify the top five most active users in the group Figure 9 -Most Common Words
using this graph and list, which also displays each user's
percentage of overall group usage. A bar chart displays the top twenty most frequently used
words.

Figure – Emoji Analysis

© 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 1108
 International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 10 Issue: 04 | Apr 2023 www.irjet.net p-ISSN: 2395-0072

This pie chart is used to display the top five most frequently 2019]. [6] S. Patil, "WhatsApp Group Data Analysis with R,"
used emojis as a percentage of overall emoji usage. International Journal of Computer Applications, vol. Volume
154 , no. 4, p. 0975 – 8887, November 2016.
5. CONCLUSION
[10] D. Bouhnik and M. Deshen, "WhatsApp Goes to School:
In conclusion, a WhatsApp chat analyzer can be a powerful Mobile Instant Messaging Between Teachers and Students,"
tool for gaining insights into group conversations. By Journal of Information Technology Education: Research, vol.
analyzing the messages, we can gain information about the 13, pp. 217231, 25 August 2014.
frequency of communication, the topics that are most
commonly discussed, and the overall sentiment of the group.
With this information, we can identify patterns and trends
that can help us to better understand the dynamics of the
group, and to make more informed decisions about how to
communicate effectively.

REFERENCES

[1] S. Patil, "WhatsApp Group Data Analysis with R,"

International Journal of Computer Applications, vol. Volume
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[2] Available from:

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