Sentimental Analysis
on Mobile Phones
Abstract
Sentiment Analysis (Opinion Investigation) is a well-known field for examining and drawing insights from text data from various sources, including YouTube, Twitter, and Amazon. This project aims to gather data from a social media platform and use analytics to discover people's general feelings about a certain topic. The project utilizes text processing, data extraction, and sentiment analysis techniques to collect reliable data and provide written insights based on the analysis.
Index Terms: Sentiment Analysis, Machine Learning, Accuracy, Mobile, Text processing, Analysis
Aims and Objectives
The project aims to:
- Better analyze user responses to mobile features using social listening and provide timely feedback to the feature enhancement team.
- Quickly identify new topics of interest.
- Determine the reception of a feature through sentiment analysis.
- Conduct research and make business decisions that cater to the target audience's interests using independent guidance and sentiment analysis.
- Prioritize customers' expectations for advanced mobile phone utility.
Image Gallery
Left & Right
In this project, various sentiment analysis techniques are used to gather data from different social media platforms. The collected data is processed and analyzed using Python packages. The findings are visualized using Tableau, including category visualization to illustrate sentiments about different product attributes and time-based visualization to track changes in people's perceptions over time. The workflow diagram illustrates the steps involved in the project, such as learning the fundamentals, data collection, data preprocessing, sentiment analysis, and visualization.
Address
Nagpur,India