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A Cloud-Based Dashboard for Time Series Analysis on Hot Topics from Social Media

  • Yunkai LiuEmail author
  • Weifeng Xu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1075)

Abstract

Social Media has increasingly acquired enormous storehouses of shared interactive ideas among people in virtual communities over the past decade. While considering hot topics in social media as the culture of today’s world, related analysis derived from its trend allows researchers and society understand public point of view regarding emerging topics through online social interactions. The ease of categorizing the trends of topics makes it beneficial to find how people react to a certain topic. In our research, the distributions of keywords from hot topics are studied. First of all, a private cloud system is set up to collect and to filter raw data from social network (Twitter). Then, a web-based dashboard is developed to demonstrate static numbers and related charts. Some experiments are performed based on the newly-developed system deployed. Distribution functions of keywords are studied based on 2016 data, and further applications are applied based on 2017 spring data. Further cross comparisons are deployed based on daily, weekly, and monthly frequencies from different locations.

Keywords

Time series analysis Social media Hot topics Trending topics Twitter Google Trends 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Gannon UniversityErieUSA
  2. 2.University of BaltimoreBaltimoreUSA

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