Abstract
Growing of social media usage present a new set of opportunities and challenges in the way of information is retrieved and searched. Opinions on social media has become an important factor in influencing people choices on purchasing a product and service. Hence, sentiment analysis has become the most crucial tool in tracking people feedbacks on products and services. For Malay language there is limited sources available for this language. Thus, in this paper we present the method of extracting opinion on online Malay text. The traditional method using POS extraction is not adequate. Thus, rule based method is integrated with POS extraction method to improve opinion words extraction. Most of the existing tools are able to retrieve opinion at sentence and document level. More detail analysis is acquired to have detail information and summarization of a product. This is where feature level sentiment analysis is needed. The process of identifying opinion of a particular feature in a sentence, can be quite tedious and troublesome. This is because opinion of the feature can be hidden and scattered in the sentence. Therefore, opinion mapping is employed for opinion extraction at feature level in this paper. A set of tweets from telecommunication domain is used to evaluate the proposed framework. From the experiment, the accuracy of the extraction performed is 88%. The detail description of the feature level opinion extraction steps is discussed in this paper.
Highlights
Social media has seen a steady increase of its usage over the past few years
People use social media as a platform to share their feedbacks and opinions, many of which are viewed by the public
Many sentiment tools available are not capable of processing Malay online text and in addition to it, majority of the tools are developed for document and sentence level but none for feature level
Summary
People use social media as a platform to share their feedbacks and opinions, many of which are viewed by the public. This has inadvertently generated a gigantic amount of data online. Online customers depend on these reviews and feedbacks before deciding to purchase a product These valuable opinions are able to influence the decision of potential customers. With all these opinion data generated online, businesses too have realized the importance of gathering a customer’s feedback database which would prove useful for businesses to plan their marketing and product development
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