Tweet Pulse: Interactive Sentiment Dashboard with Advanced Analytics
DOI:
https://doi.org/10.48047/ysvrg712Keywords:
Sentiment analysis, Natural language processing, Social media analytics, Machine learning, Real-time analysis, Twitter data mining, Data visualization.Abstract
In today’s digital era, understanding public sentiment is crucial for businesses and organizations aiming to stay ahead in competitive markets. This paper aims to develop a real time sentimental analysis to analyze and interpret social media data streams. The primary application of the system is to monitor and analyze social media conversations, offering the businesses the ability to track brand perceptions and detect emerging trends and respond promptly to public opinion. However, the utility of this project extends far beyond the traditional brand management. It can be adapted to various applications including market research, crisis management and healthcare monitoring, customer engagement, financial market analysis.
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