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All Journal International Journal of Advances in Data and Information Systems
Hassan Mourad
Department of Computer Engineering, Université Internationale de Casablanca
Computer Science & IT Electrical & Electronics Engineering

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Sentiment Analysis Approach for Analyzing iPhone Release using Support Vector Machine Wasim Bourequat; Hassan Mourad
International Journal of Advances in Data and Information Systems Vol. 2 No. 1 (2021): April 2021 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v2i1.1216

Abstract

Sentiment analysis is a process of understanding, extracting, and processing textual data automatically to get sentiment information contained in a comment sentence on Twitter. Sentiment analysis needs to be done because the use of social media in society is increasing so that it affects the development of public opinion. Therefore, it can be used to analyze public opinion by applying data science, one of which is Natural Language Processing (NLP) and Text Mining or also known as text analytics. The stages of the overall method used in this study are to do text mining on the Twitter site regarding iPhone Release with methods of scraping, labeling, preprocessing (case folding, tokenization, filtering), TF-IDF, and classification of sentiments using the Support Vector Machine. The Support Vector Machine is widely used as a baseline in text-related tasks with satisfactory results, on several evaluation matrices such as accuracy, precision, recall, and F1 score yielding 89.21%, 92.43%, 95.53%, and 93.95, respectively.
Co-Authors Wasim Bourequat