ARES: A Retrieval Engine Based on Sentiments
This paper introduces a system enriching the standard web search engine interface with sentiment information. Additionally, it exploits such annotations to diversify the result list based on the different sentiments expressed by retrieved web pages. Thanks to the annotations, the end user is aware of which opinions the search engine is showing her and, thanks to the diversification, she can see an overview of the different opinions expressed about the requested topic. We describe the methods used for computing sentiment scores of web search results and for re-ranking them in order to cover different sentiment classes. The proposed system, built on top of commercial search engine APIs, is available on-line.
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