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2018 | OriginalPaper | Chapter

Automated Credibility Assessment of Web Page Based on Genre

Authors : Shriyansh Agrawal, S. Lalit Mohan, Y. Raghu Reddy

Published in: Big Data Analytics

Publisher: Springer International Publishing

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Abstract

With more than a billion web sites, volume and variety of content available for consumption is huge. However, credibility, an important quality characteristic of web pages is questionable in many cases and tends to be non-uniform. Credibility can increase or reduce the importance of web page leading to potential gain or loss of user base. Credibility without factoring genre of content (for example, Help, Article, Discussion, etc.) can lead to incorrect assessment. Depending on the genre, the importance of features such as web page date time modified, grammar, image to text ratio, in and out links, and other web page features differ. We propose a genre credibility assessment based on web page surface features and their importance in a genre. Further, we built a WEBCred framework to assess GCS (Genre based Credibility Score) with flexibility to add/modify genres, its features and their importance. We validated our approach on 10,429 ‘Information Security’ related web pages; the assessed score correlated 35% with crowd sourced Web Of Trust (WOT) score and 39% with Alexa ranking.

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previous chapter Design of the Cogno Web Observatory for Characterizing Online Social Cognition

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Title: Automated Credibility Assessment of Web Page Based on Genre
Authors: Shriyansh Agrawal
S. Lalit Mohan
Y. Raghu Reddy
Publisher: Springer International Publishing
Book: Big Data Analytics
Print ISBN: 978-3-030-04779-5

Electronic ISBN: 978-3-030-04780-1

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-030-04780-1_11

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