Data sparsity for twitter sentiment analysis in real-time from biased and noisy data

Abstract

Specializing in the analysis of strong emotions expressed in text, sentiment analysis is a scientific field. You may convey your thoughts and feelings about anything by expressing your opinion about it. This work explains the origins of sentiment analysis and how to configure sentiment evaluators. This paper showed comprehensive assessment of emotions will still be required. Analysis includes non-textual material. The use of visual media in social research is also useful. Without a doubt, I see the value of these links. This research uses a domain-specific seed list to categorize tweets. As much information as possible is preserved during tweet categorization. The algorithm categorizes tweets precisely and sentimentally to build a user interest profile. To test the method, 1 million tweets were used and up to 96% of them were correctly classified.

Subject Classification:

• Primary 93A30
• Secondary 49K15

Keywords:

• Mathematical modeling
• Ordinary differential equations
• A duopoly economy
• Market share