Distinguishing the Popularity between Topics: A System for Up-to-Date Opinion Retrieval and Mining in the Web
| Autor: | Efstathios Stamatatos, Nikolaos Pappas, Georgios Katsimpras |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Focus (computing)
Information retrieval Text Mining business.industry Computer science Sentiment analysis Crawling computer.software_genre Popularity Field (computer science) World Wide Web Information extraction Text mining Web mining Information Retrieval Web page Sentiment Analysis Utility-Based Agents business Information Extraction computer |
| Zdroj: | Computational Linguistics and Intelligent Text Processing ISBN: 9783642372551 CICLing (2) |
| DOI: | 10.1007/978-3-642-37256-8_17 |
| Popis: | The constantly increasing amount of opinionated texts found in the Web had a significant impact in the development of sentiment analysis. So far, the majority of the comparative studies in this field focus on analyzing fixed (offline) collections from certain domains, genres, or topics. In this paper, we present an online system for opinion mining and retrieval that is able to discover up-to-date web pages on given topics using focused crawling agents, extract opinionated textual parts from web pages, and estimate their polarity using opinion mining agents. The evaluation of the system on real-world case studies, demonstrates that is appropriate for opinion comparison between topics, since it provides useful indications on the popularity based on a relatively small amount of web pages. Moreover, it can produce genre-aware results of opinion retrieval, a valuable option for decision-makers. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|