Implicit aspect-based opinion mining and analysis of airline industry based on user generated reviews

Mining opinions from reviews has been a field of ever-growing research. These include mining opinions on document level, sentence-level, and even aspect level of a review. While explicitly mentioned aspects in a review have been widely researched, very little work has been done in gathering opinions on aspects that are implied and not explicitly mentioned. E.g. “the flight was spacious and there was plenty of legroom”. This gives an opinion on the entities of the cabin and seat of an airline. Words like “spacious” and phrases like “plenty of legroom” help identify these implied entities and the opinions attached to them. Not much research has been done for gathering such implicit aspects and opinions for airline reviews. The present dataset is a manually annotated domain-specific aspect-based corpus that helps a study to extract and analyze opinions about such implied aspects and entities of airlines.