Main Reference PaperInterpreting the Public Sentiment Variations on Twitter, IEEE Transactions on Knowledge and Data Engineering, 2014.
  • Tracking and analyzing public sentiment can provide critical information for decision making in various domains. This paper proposes twoLatent Dirichlet Allocation based models that are Foreground and Background LDA Models, to solve the problem in analyzing public sentiment variations and finding possible reason causing this variation.

+ Description
  • Tracking and analyzing public sentiment can provide critical information for decision making in various domains. This paper proposes twoLatent Dirichlet Allocation based models that are Foreground and Background LDA Models, to solve the problem in analyzing public sentiment variations and finding possible reason causing this variation.

  • To solve the problem in public sentiment variation.

  • To find possible reasons for variation.

+ Aim & Objectives
  • To solve the problem in public sentiment variation.

  • To find possible reasons for variation.

  • This paper may contribute some techniques to improve performance of reason mining by finding possible reasons for variation in sentiment.

+ Contribution
  • This paper may contribute some techniques to improve performance of reason mining by finding possible reasons for variation in sentiment.

  • Java JDK 1.8, MySQL

  • Netbeans 8.0.1, J2EE.

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL

  • Netbeans 8.0.1, J2EE.

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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