Trustworthiness Analysis of Web Search Results

Nakamura, Satoshi; Shinji, Konishi; Jatowt, Adam; Ohshima, Hiroaki; Kondo, Hiroyuki; Tezuka, Taro; Oyama, Satoshi; Tanaka, Katsumi

doi:10.1007/978-3-540-74851-9_4

Cited by 55 publications

(35 citation statements)

References 7 publications

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“…Closer to our work, several approaches have been proposed for enhancing the search results with page credibility information [13,17,18]. Nakamura et al [13] developed a system prototype augmenting the search results for each page with three attributes, namely topic majority (i.e.…”

Section: Related Workmentioning

confidence: 98%

“…According to [13], many people tend to believe that a higher ranking in the search results means a higher credibility, which is not always true. Even worse, spammers exploiting this belief, have targeted the ranking mechanisms of popular search engines with relative success [2,6].…”

Section: Search-ranking Componentmentioning

confidence: 99%

“…A number of them deal with defining web credibility and the main features involved in its assessment [12,4,13,17,18]. Kapoun in [12] perceived credibility as a journalism quality depending on accuracy of information, authority of the source, objectivity, currency and topic coverage.…”

Section: Related Workmentioning

confidence: 99%

“…[13,18], have been proposed that combine different page content features to assess credibility with limited effectiveness. Since many users perceive high ranking position of a page in the search results as high credibility, reordering the search results based on page credibility would greatly facilitate people's access to credible information.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A decentralized recommender system for effective web credibility assessment

Papaioannou

Ranvier

Olteanu

et al. 2012

Proceedings of the 21st ACM International Conference on Information and Knowledge Management

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An overwhelming and growing amount of data is available online. The problem of untrustworthy online information is augmented by its high economic potential and its dynamic nature, e.g. transient domain names, dynamic content, etc. In this paper, we address the problem of assessing the credibility of web pages by a decentralized social recommender system. Specifically, we concurrently employ i) item-based collaborative filtering (CF) based on specific web page features, ii) user-based CF based on friend ratings and iii) the ranking of the page in search results. These factors are appropriately combined into a single assessment based on adaptive weights that depend on their effectiveness for different topics and different fractions of malicious ratings. Simulation experiments with real traces of web page credibility evaluations suggest that our hybrid approach outperforms both its constituent components and classical content-based classification approaches.

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Section: Related Workmentioning

confidence: 98%

Section: Search-ranking Componentmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A decentralized recommender system for effective web credibility assessment

Papaioannou

Ranvier

Olteanu

et al. 2012

Proceedings of the 21st ACM International Conference on Information and Knowledge Management

View full text Add to dashboard Cite

show abstract

“…It is almost impossible to find necessary information from such a huge web space without search engines. Since approximately a half of search engine users look at no more than the first five results in the list [2], web sites need to get high rankings to attract visitors and yield profits. Given this situation, it is not surprising that web spammers appeared who try to boost the rankings of their sites using unfair ways.…”

Section: Introductionmentioning

confidence: 99%

Detecting Hijacked Sites by Web Spammer Using Link-Based Algorithms

Chung

Toyoda

2010

IEICE Trans. Inf. & Syst.

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Young-joo CHUNG†a) , Masashi TOYODA †b) , Nonmembers, and Masaru KITSUREGAWA †c) , Member SUMMARYIn this paper, we propose a method for finding web sites whose links are hijacked by web spammers. A hijacked site is a trustworthy site that points to untrustworthy sites. To detect hijacked sites, we evaluate the trustworthiness of web sites, and examine how trustworthy sites are hijacked by untrustworthy sites in their out-neighbors. The trustworthiness is evaluated based on the difference between the white and spam scores that calculated by two modified versions of PageRank. We define two hijacked scores that measure how likely a trustworthy site is to be hijacked based on the distribution of the trustworthiness in its out-neighbors. The performance of those hijacked scores are compared using our largescale Japanese Web archive. The results show that a better performance is obtained by the score that considers both trustworthy and untrustworthy out-neighbors, compared with the one that only considers untrustworthy out-neighbors. key words: link analysis, web spam, information retrieval, link hijacking

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The effects of credibility cues on the selection of search engine results

Unkel

Haas

2017

Asso for Info Science & Tech

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Web search engines act as gatekeepers when people search for information online. Research has shown that search engine users seem to trust the search engines' ranking uncritically and mostly select top-ranked results. This study further examines search engine users' selection behavior. Drawing from the credibility and information research literature, we test whether the presence or absence of certain credibility cues influences the selection probability of search engine results. In an observational study, participants (N 5 247) completed two information research tasks on preset search engine results pages, on which three credibility cues (source reputation, message neutrality, and social recommendations) as well as the search result ranking were systematically varied. The results of our study confirm the significance of the ranking. Of the three credibility cues, only reputation had an additional effect on selection probabilities. Personal characteristics (prior knowledge about the researched issues, search engine usage patterns, etc.) did not influence the preference for search results linked with certain credibility cues. These findings are discussed in light of situational and contextual characteristics (e.g., involvement, low-cost scenarios).

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Trustworthiness Analysis of Web Search Results

Cited by 55 publications

References 7 publications

A decentralized recommender system for effective web credibility assessment

A decentralized recommender system for effective web credibility assessment

Detecting Hijacked Sites by Web Spammer Using Link-Based Algorithms

The effects of credibility cues on the selection of search engine results

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