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March 30, 20260 citationsOpen Access

Cloud-Native Big Data Streaming Framework for Real-Time Social Media Intelligence and Large-Scale Public Opinion Analytics

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SDSri Sai Nithin Chowdary DukkipatiUniversity of Missouri–Kansas City

Key Points

  • The research aims to develop a cloud-based framework for real-time analysis of social media posts to capture public opinion.
  • Developed a cloud-native system for immediate data collection and analysis of social media posts.
  • Designed the framework to sustain high performance during events with a large volume of data.
  • Implemented opinion tracking and summarization features for effective response.
  • The system successfully processes large amounts of social media data with minimal delay.
  • Real-time analysis aids in understanding public opinion more effectively during critical events.
  • Maintained high reliability even under heavy data loads or partial system failures.

Abstract

People share their opinions on social media every day. During big events like elections, disasters, or public announcements, these opinions can change very fast. Older systems usually store this information first and analyze it later. Because of this delay, it becomes difficult to understand what people think at the right time. This paper presents a cloud-based system that studies social media posts right after they are shared. The system collects many posts, finds common opinions as they appear, and creates clear summaries. These summaries help leaders and organizations respond more quickly. The system is designed to handle a large number of posts, stay steady during busy times, and continue working even if part of the system has problems. The system combines data collection, opinion tracking, and stable operation into one simple design. Test results show that it can process large amounts of data with very little delay while remaining reliable. This makes social media a useful source for understanding public opinion when fast action is needed most.

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Sri Sai Nithin Chowdary Dukkipati (2026) studied this question.

synapsesocial.com/papers/69c9c5c5f8fdd13afe0bdb20https://doi.org/10.5281/zenodo.19274668
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