Abstract
Sentiment analysis is an important part of natural language processing (NLP). This study evaluated the sentiment of Romanized Sindhi Text (RST) using a hybrid approach and ground truth values. The methodology of sentiment analysis involves three major steps: input data, process on tool, analysis of data and evaluation of results. One hundred RST sentences were used in this study's sentiment analysis, which can be positive, neutral, or negative. The statements in the corpus of this study are simple to understand and are used in everyday life. This research used an online Python tool to process a text and get results in the form of outcomes. The results showed that 86% of the sentences have neutral sentiments, 9% of the total results of sentiment analysis have negative sentiments, and only 5% of sentences of Romanized Sindhi Text have positive sentiments. The accuracy of the RST was measured on an online calculator and the value was 87.02% on the basis of ground truth values. An error ratio of 12.98% was calculated on the basis accuracy found on the online calculator of confusion matrix.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal of Advanced Computer Science and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.