Asmoro, Feizal Badri and Purnama, James and Erwin, Alva (2013) Sentiment Analysis Using Automatic Classification On Online Media Article. Bachelor thesis, Swiss German University.

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Abstract

The increasing demand for an automatic sentiment measurement is becoming critical in this era. Therefore, this topic is becoming one of the most encountered reseraches in data mining and NLP. Sentiment analysis is a process of classifying articles as a positive or negative. This kind of approach is lacking of multiple assessor’s valuation. In order to do so, a more humanly semantic classification is needed. There are various researches on developing an algorithm for sentiment analysis by using classification, such as research by Turney (2010) and Pang (2008). The main purpose of this research is to design and implement a system that can analyze sentiment of text in Bahasa Indonesia. The article will be categorized into one of two sentiments: positive or negative. The text is an online digital media streaming article. Sentiment analysis will use automatic classification to analyze the sentiment.

Item Type:	Thesis (Bachelor)
Uncontrolled Keywords:	Sentiment; Natural Language Processing; Wordnet; Automatic Classification
Subjects:	H Social Sciences > HM Sociology > HM742 Online social networks Q Science > QA Mathematics > QA76 Computer software > > QA76.91 Data mining T Technology > T Technology (General) > T58.5 Information technology
Divisions:	Faculty of Engineering and Information Technology > Department of Information Technology
Depositing User:	Astuti Kusumaningrum
Date Deposited:	09 Jan 2022 06:08
Last Modified:	09 Jan 2022 06:08
URI:	http://repository.sgu.ac.id/id/eprint/1289

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