Blog credibility ranking by exploiting verified content

Juffinger, Andreas; Granitzer, Michael; Lex, Elisabeth

doi:10.1145/1526993.1527005

Cited by 37 publications

(23 citation statements)

References 11 publications

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“…They found that there is a correlation between the length of posts in a blog and the popularity of that blog. Mishne and de Rijke (2006)'s observation that bloggers often report on news events is the basis for the credibility assessment in Juffinger et al (2009). The authors compare blog posts to news articles about the same topic, and assign a credibility level based on the similarity between the two.…”

Section: Credibility In Social Mediamentioning

confidence: 99%

Credibility-inspired ranking for blog post retrieval

Weerkamp

Rijke

2012

Inf Retrieval

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Credibility of information refers to its believability or the believability of its sources. We explore the impact of credibility-inspired indicators on the task of blog post retrieval, following the intuition that more credible blog posts are preferred by searchers. Based on a previously introduced credibility framework for blogs, we define several credibility indicators, and divide them into post-level (e.g., spelling, timeliness, document length) and blog-level (e.g., regularity, expertise, comments) indicators. The retrieval task at hand is precision-oriented, and we hypothesize that the use of credibility-inspired indicators will positively impact precision. We propose to use ideas from the credibility framework in a reranking approach to the blog post retrieval problem: We introduce two simple ways of reranking the top n of an initial run. The first approach, Credibility-inspired reranking, simply reranks the top n of a baseline based on the credibility-inspired score. The second approach, Combined reranking, multiplies the credibility-inspired score of the top n results by their retrieval score, and reranks based on this score. Results show that Credibility-inspired reranking leads to larger improvements over the baseline than Combined reranking, but both approaches are capable of improving over an already strong baseline. For Credibility-inspired reranking the best performance is achieved using a combination of all post-level indicators. Combined reranking works best using the postlevel indicators combined with comments and pronouns. The blog-level indicators expertise, regularity, and coherence do not contribute positively to the performance, although analysis shows that they can be useful for certain topics. Additional analysis shows that a relative small value of n (15-25) leads to the best results, and that posts that 123Inf Retrieval (2012) 15:243-277 DOI 10.1007 move up the ranking due to the integration of reranking based on credibility-inspired indicators do indeed appear to be more credible than the ones that go down.

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Section: Credibility In Social Mediamentioning

confidence: 99%

Credibility-inspired ranking for blog post retrieval

Weerkamp

Rijke

2012

Inf Retrieval

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“…The most common objective measures proposed so far are strongly based on trust and reputation and citation networks [8], and also credibility rankings that take into account mainly the source of information [9] and content [10].…”

Section: Related Workmentioning

confidence: 99%

Assessing documents' credibility with genetic programming

Palotti

Salles

Pappa

et al. 2011

2011 IEEE Congress of Evolutionary Computation (CEC)

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The concept of example credibility evaluates how much a classifier can trust an example when building a classification model. It is given by a credibility function, which is application dependent and estimated according to a series of factors that influence the credibility of the examples. Here we deal with automatic document classification and study the credibility of a document according to three factors: content, authorship and citations. We propose a genetic programming algorithm to estimate the credibility of training examples, and then add this estimation to a credibility-aware classifier. For that, we model the authorship and citation data as a complex network, and select a set of structural metrics that can be used to estimate credibility. These metrics are then merged with other content-related ones, and used as terminals for the GP. The GP was tested in a subset of the ACM-DL, and results showed that the credibility-aware classifier obtained results of micro and macroF 1 from 5% to 8% better than the traditional classifiers.

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“…With an opposite objective, BarYossef et al [1] employed link-structure analysis on the web for identifying decayed web sites. Juffinger et al [4] proposed calculating the coverage of news in blogs and the level of their synchronization as a measure of blog credibility. However, to the best of our knowledge none of the related works proposed verifying information coverage and currency in web pages using news articles.…”

Section: Related Workmentioning

confidence: 99%

Estimating News Coverage of Web Search Results

Jatowt

Kawai

Tanaka

2010

2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology

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Abstract-The abundance of content on the web and the lack of quality control require more refined approaches in analyzing online information. In this paper, we propose evaluating the extent to which web search results cover important and recent news related to real-world objects. Our method allows for identifying search results that provide comprehensive overviews of major events related to user queries or that contain most recent information.

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Blog credibility ranking by exploiting verified content

Cited by 37 publications

References 11 publications

Credibility-inspired ranking for blog post retrieval

Credibility-inspired ranking for blog post retrieval

Assessing documents' credibility with genetic programming

Estimating News Coverage of Web Search Results

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