Public Sentiment Interpretation on Social Web: Twitter
Journal: International Journal of Science and Research (IJSR) (Vol.4, No. 6)Publication Date: 2015-06-05
Authors : Devaki Ingule; Gyankamal Chhajed;
Page : 632-636
Keywords : Twitter; Public Sentiments; Sentiment analysis; Event tracking; Latent Dirichlet Allocation LDA; Foreground and Background LDA; Reason Candidate and Background LDA;
Abstract
Twitter platform is valuable to follow the public sentiments. Knowing users point of views and reasons behind them at various point is an important study to take certain decisions. Categorization of positive and negative opinions is a process of sentiment analysis. It is very useful for people to find sentiment about the person, product etc. before they actually make opinion about them. In this paper Latent Dirichlet Allocation (LDA) based models are defined. Where the first model that is Foreground and Background LDA (FB-LDA) can remove background topics and selects foreground topics from tweets and the second model that is Reason Candidate and Background LDA (RCB-LDA) which extract greatest representative tweets which is obtained from FB-LDA as reason candidates for interpretation of public sentiments.
Other Latest Articles
- Improved Steganographic Method for Hiding Secure Data Based on Efficient Keystream Generator
- Effect of Fuel Injection Pressure on Performance and Emission Characteristics of Diesel Engine Fueled with Cashew Nut Shell Biodiesel
- Global and Reactivity Descriptors Studies of Cyanuric Acid Tautomers in Different Solvents by using of Density Functional Theory (DFT)
- Predation and Competition of Two Predators (Pardosa pseudoannulata and Verania lineata) on Different Densities of Nilaparvata lugens in Laboratory
- An Application of SWOT Analysis in Development of Underutilized Plant Species in a Rural Hot Spur in Africa
Last modified: 2021-06-30 21:49:27