WhatsApp Chat Analyzer

These days, the most popular and effective way to communicate is through the WhatsApp app. WhatsApp chats are made up of many types of group talks. There are several subjects covered in this talk. Numerous data points for cutting-edge technologies like machine learning may be found in this material....

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Veröffentlicht in:2024 1st International Conference on Advances in Computing, Communication and Networking (ICAC2N) S. 78 - 83
Hauptverfasser: Singh, Jitendra Nath, Kumar, Yogesh, Srivastava, Akshat, Baghel, Dushyant, Al-Attabi, Kassem
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 16.12.2024
Schlagworte:
Data analysis
Data models
Feeds
Flutter application etc
Freeware
Internet telephony
Libraries
Machine learning
matplotlib
Pandas
Python
Seaborn
Sentiment analysis
sentiment analyzer
System implementation
WhatsApp chat data
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Beschreibung
Zusammenfassung:These days, the most popular and effective way to communicate is through the WhatsApp app. WhatsApp chats are made up of many types of group talks. There are several subjects covered in this talk. Numerous data points for cutting-edge technologies like machine learning may be found in this material. For machine learning models, the most crucial factor is to deliver an appropriate educational encounter, which is influenced indirectly by the data we feed the model. The goal of this program is to offer a thorough study of the data that WhatsApp provides. Whatever the subject matter of the chat, you may use our produced code to gain a deeper comprehension of the data. The benefit of this tool is that it is implemented with ease utilizing simple Python tools such as sentiment analysis, seaborn, matplotlib, and pandas. These modules are used to create data frames and plot various graphs, and the results are then displayed in a flutter application. The algorithm used in this application is efficient and uses less resources, so it can be applied to even the largest datasets.
DOI:10.1109/ICAC2N63387.2024.10895439