| dc.description.abstract | Sentiment analysis is an effective method for
identifying text data and extracting the
sentiment component. Every day, customers'
reviews, opinions, suggestions, and tweets
generate a high amount of unstructured data on
shopping websites. Retailers can use aspect level
analysis of this data to gain a better knowledge
of their customers' expectations and then
modify their policies accordingly. A innovative
approach based on aspect level sentiment
detection, which focuses on the item's features,
is provided in this research. The work was
implemented and validated on Amazon
customer reviews (crawled data), where each
review's aspect phrases were determined
initially. | en_US |
