MMO: Multiply-Minus-One Rule for Detecting & Ranking Positive and Negative Opinion
نویسندگان
چکیده
Hit and hot issue about reviews of any product is sentiment classification. Not only manufacturing company of the reviewed product takes decision about its quality, but the customers’ purchase of the product is also based on the reviews. Instead of reading all the reviews one by one, different works have been done to classify them as negative or positive with preprocessing. Suppose from 1000 reviews, there are 300 negative and 700 are positive. As a whole it is positive. Company and customer may not be satisfied with this sentiment orientation. For companies, negative reviews should be separated with respect to different aspects and features, so companies can enhance the features of the product. There is also a lot of work on aspect extraction, and then aspect based sentiment analysis. While on the other hand, users want the most positive reviews and the most negative reviews, then they can decide purchasing a certain product. To consider the issue from users’ perspective, authors suggest a method Multiply-Minus-One (MMO) which can evaluate each review and find scores based on positive, negative, intensifiers and negation words using WordNet Dictionary. Experiments on 4 types of datasets of product reviews show that this method can achieve 86%, 83%, 83% and 85% precision performance. Keywords—Sentiment Classification; Preprocessing; Text Mining; Sentiment Orientation
منابع مشابه
Does the normal four steps weight-bearing rule predict the need for radiography in cases of blunt ankle trauma?
Background: Ankle injuries are one of the most common complaints of patients presenting to emergency departments (ED). The Ottawa ankle rules (OAR) was introduced to help physicians to decide who may require x-ray for blunt injuries. The present study aimed at validating the four steps weight-bearing rule of OAR as a sole criterion. Methods: This prospective observational study wa...
متن کاملA new parametric method for ranking fuzzy numbers based on positive and negative ideal solutions
متن کامل
Analysis of Users’ Opinions about Reasons for Divorce
One of the most important issues related to knowledge discovery is the field of comment mining. Opinion mining is a tool through which the opinions of people who comment about a specific issue can be evaluated in order to achieve some interesting results. This is a subset of data mining. Opinion mining can be improved using the data mining algorithms. One of the important parts of opinion minin...
متن کاملUIC at TREC 2007 Blog Track
In TREC 2007 Blog Track, we developed a three-step algorithm for the opinion retrieval task. An information retrieval step retrieves the query-relevant documents. A following opinion identification step identifies the opinionative texts in these documents. A ranking step identifies the query-related opinions in the documents and ranks them by calculating their opinion similarity scores. For the...
متن کاملIncorporating Negative Values in AHP Using Rule- Based Scoring Methodology for Ranking of Sustainable Chemical Process Design Options
Adopting Analytical Hierarchy Process (AHP) for selection and ranking of sustainable chemical process design that considers the trade-off between economic feasibility, environmental friendliness and social advantages offers good decision methodology for multi criteria problem. Typical AHP problem however are limited to handle only positive preferences. The introduction of negative preferences i...
متن کامل