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| Content Provider | ACM Digital Library |
|---|---|
| Author | Karagoz, Pinar Vural, A. Gural Cambazoglu, B. Barla |
| Copyright Year | 2014 |
| Abstract | Sentiments and opinions expressed in Web pages towards objects, entities, and products constitute an important portion of the textual content available in the Web. In the last decade, the analysis of such content has gained importance due to its high potential for monetization. Despite the vast interest in sentiment analysis, somewhat surprisingly, the discovery of sentimental or opinionated Web content is mostly ignored. This work aims to fill this gap and addresses the problem of quickly discovering and fetching the sentimental content present in the Web. To this end, we design a sentiment-focused Web crawling framework. In particular, we propose different sentiment-focused Web crawling strategies that prioritize discovered URLs based on their predicted sentiment scores. Through simulations, these strategies are shown to achieve considerable performance improvement over general-purpose Web crawling strategies in discovery of sentimental Web content. |
| Starting Page | 1 |
| Ending Page | 21 |
| Page Count | 21 |
| File Format | |
| ISSN | 15591131 |
| e-ISSN | 1559114X |
| DOI | 10.1145/2644821 |
| Volume Number | 8 |
| Issue Number | 4 |
| Journal | ACM Transactions on the Web (TWEB) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-11-06 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Sentiment analysis Focused web crawling |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Networks and Communications |
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