Feature Extraction from Micro-blogs for Comparison of Products and Services

Social networks are a popular place for people to express their opinions about products and services. One question would be that for two similar products (e.g., two different brands of mobile phones), can we make them comparable to each other? In this paper, we show our system namely OpinionAnalyzer, a novel social network analyser designed to collect opinions from Twitter micro-blogs about two given similar products for an effective comparison between them. The system outcome is a structure of features for the given products that people have expressed opinions about. Then the corresponding sentiment analysis on those features is performed. Our system can be used to understand user’s preference to a certain product and show the reasons why users prefer this product. The experiments are evaluated based on accuracy, precision/recall, and F-score. Our experimental results show that the system is effective and efficient.