Aspect Extraction in Domain Lexicon Generation: A New Frequency-Based Approach

Abstract

Domain sentimental lexicon building become an attractive field in recent years. This is due to the increased number of users’ generated data through the internet besides the different sentiments of opinion words in different contexts. Domain lexicons mainly consist of opinion pairs and their associated sentiment. Any opinion pair is formed by a domain word and one of its associated opinion words. Therefore, to generate a domain lexicon from a domain corpus, domain word extraction is needed with their associated opinion words. One of the traditional approaches is frequency-based approaches. However, the ambiguity problem is a big concern of these approaches. This paper introduced a frequency-based equation that considers the context of the words for domain word extraction. The equation was tested on five Amazon reviews datasets and it proved its efficiency over other used frequency-based equations in terms of recall and precision. Therefore, more related lexicons to the domains were generated.

Keywords

• Aspect
• domain lexicon
• frequency-based
• sentiment analysis
• statistical
• word extraction