Sentence-Level Subjectivity Detection Using Neuro-Fuzzy Models

Samir Rustamov, Elshan Mustafayev, Mark Clements
2013 Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis  
In this work, we attempt to detect sentencelevel subjectivity by means of two supervised machine learning approaches: a Fuzzy Control System and Adaptive Neuro-Fuzzy Inference System. Even though these methods are popular in pattern recognition, they have not been thoroughly investigated for subjectivity analysis. We present a novel "Pruned ICF Weighting Coefficient," which improves the accuracy for subjectivity detection. Our feature extraction algorithm calculates a feature vector based on
more » ... statistical occurrences of words in a corpus without any lexical knowledge. For this reason, these machine learning models can be applied to any language; i.e., there is no lexical, grammatical, syntactical analysis used in the classification process.
dblp:conf/wassa/RustamovMC13 fatcat:k3b6gmjfgjftbhdueeoxuizg5q