@inproceedings{54ead7ebb8794d20bef7ac2a18260deb,
title = "Feature extraction and classification of movie reviews",
abstract = "Sentiment analysis identifies a user{\textquoteright}s attitude towards a service, a topic or an event and it is very useful for companies that receive many written reviews of their services.We investigate the effect of feature extraction techniques on supervised machine learning classifiers using four different performance metrics using a publicly available movie review dataset. Our objective is to explore different classification algorithms as well as utilizing diverse feature extractors and compare outcomes and finally select the trio of feature extraction technique, classification algorithm and performance metric with the best result for the movie review classification use case.",
keywords = "feature extraction, machine learning, sentiment analysis, Support Vector Machine (SVM), random forest",
author = "Nhamo Mtetwa and Awukam, {Awukam Ojang} and Mehdi Yousefi",
note = "Acceptance in SAN Changed to conf. proceedings from paper Exception email to author. ET 14/11/19 ",
year = "2019",
month = may,
day = "2",
doi = "10.1109/ISCMI.2018.8703235",
language = "English",
publisher = "IEEE",
pages = "67--71",
booktitle = "2018 5th International Conference on Soft Computing & Machine Intelligence (ISCMI)",
}