aspect based opinion mining

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Aspect Based Opinion Mining Name Institution Aspect Based Opinion Mining A majority of the consumers rely on user information posted on social media sites and blogs. Particularly, the business world has immensely benefitted from the growth of social media platforms. Today’s entrepreneurs do not blindly enter into business without conducting researches regarding the perception of the consumer on a particular product or service in the market. Social media platforms have emerged to be ideal platforms upon which customer reviews are posted. The data collected is instrumental in providing business owners with relevant avenues upon which they can enhance their products or services (Bauman, Liu & Tuzhilin, 2016). The reviews are also instrumental in informing entrepreneurs of the right decisions to undertake that would enable them respond to the concerns of the consumers. However, the processes involved in gathering of customer opinions tends to be a complicated process (Santosh, Babu, Prasad & Vivekananda, 2016). It is imperative that the information gathered be meaningful and helpful to the business owner. Opinion based mining has been identified as one of the most ideal methodologies to gather customer reviews and opinions. Aspect-Based Opinion Mining (ABOM) has been identified as the most ideal methodology of onion mining to gather data. The method examines every feature of a review including the feature levels of a sentence. ABOM ensures that it analyzes all the multi-expressions of a code and its relationships with specific word constructs to give the best combinations of what a review entails. Valencia-García, Colomo-Palacios and Alor-Hernández

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