Sentiment Analyzer

A practical approach to calculate sentimental orientation of data

Transcript

1. A practical approach to calculate sentimental orientation of data Project Undertaken By - 
 Nitesh Oswal - 120240101031 Rohit Kumar - 120240101047 Priyaranjan Singh - 120240101038 Project Submitted To - 
 Mr. Pramod Mehra, Asst. Professor, Department of CSE
2. Introduction What is sentimental orientation?
3. Sentiment Analysis How do we calculate sentimental orientation? 1. Natural Language Processing 2. Text Analysis 3. Computation Linguistics Patterns & Information
4. Polarity Classification How do we do it? For classifying the polarity of a given text input Based on grading system
5. Proposed Applications Feedback Analyzer Popular Status Analyzer
6. Core APIs 1. Collection 2. Preprocessing 3. Synthesization 1. History Logging 2. Ngram Analysis Additional APIs Process (Do it all at once)
7. Collection
8. Preprocessing
9. Slang Words Special words morphed from their original to others
10. Stop Words Unnecessary literature..
11. Affinity Scores Weighted literature..
12. Synthesizing
13. The Final Math? D is the group of documents
 score(d) returns the score of single document d
 count(d) return the number of documents in d
14. Process API “fork()” it! Parent (App) Child (Worker) Child (Worker) Child (Worker) Request / Input
15. Application Demos!
16. Feedback Analyzer Demo!
17. Popular Status Analyser Demo!
18. Challenges 1. Twitter API Rate Limits 2. Storage Engine Read/Write Speeds 3. Amount of Affinity Words + Scores
19. Links Code: https://github.com/NiteshOswal/SentimentAnalyzerService
20. Thank you!