Fuzzy clustering and relevance ranking of web search results with differentiating cluster label generation

2010 ◽  
Author(s):  
Takazumi Matsumoto ◽  
Edward Hung
Keyword(s):  
Fuzzy Clustering ◽  
Web Search ◽  
Relevance Ranking ◽  
Search Results ◽  
Cluster Label

scholarly journals The Matter of Chance: Auditing Web Search Results Related to the 2020 U.S. Presidential Primary Elections Across Six Search Engines

2021 ◽  
pp. 089443932110068
Author(s):  
Aleksandra Urman ◽  
Mykola Makhortykh ◽  
Roberto Ulloa
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Large Scale ◽  
Web Search ◽  
Primary Elections ◽  
Virtual Agents ◽  
Search Results ◽  
Presidential Primary ◽  
Large Scale Analysis ◽  
Algorithmic Information

We examine how six search engines filter and rank information in relation to the queries on the U.S. 2020 presidential primary elections under the default—that is nonpersonalized—conditions. For that, we utilize an algorithmic auditing methodology that uses virtual agents to conduct large-scale analysis of algorithmic information curation in a controlled environment. Specifically, we look at the text search results for “us elections,” “donald trump,” “joe biden,” “bernie sanders” queries on Google, Baidu, Bing, DuckDuckGo, Yahoo, and Yandex, during the 2020 primaries. Our findings indicate substantial differences in the search results between search engines and multiple discrepancies within the results generated for different agents using the same search engine. It highlights that whether users see certain information is decided by chance due to the inherent randomization of search results. We also find that some search engines prioritize different categories of information sources with respect to specific candidates. These observations demonstrate that algorithmic curation of political information can create information inequalities between the search engine users even under nonpersonalized conditions. Such inequalities are particularly troubling considering that search results are highly trusted by the public and can shift the opinions of undecided voters as demonstrated by previous research.

Overlap Between Google and Bing Web Search Results!

2015 ◽  
Author(s):  
Rakesh Agrawal ◽  
Behzad Golshan ◽  
Evangelos Papalexakis
Keyword(s):  
Web Search ◽  
Search Results

Relationship and Causality between Cryptocurrencies, Commodities, Currencies, Indexes and Web Search Results During and Prior to Covid-19 Pandemic

2021 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Deni Memic ◽  
Selma Skaljic Memic ◽  
Mohamed Noor Saifuddin Mohamed Noor Saif Almehairi
Keyword(s):  
Web Search ◽  
Search Results

Web Search Relevance Ranking

2016 ◽  
pp. 1-5
Author(s):  
Hugo Zaragoza ◽  
Marc Najork
Keyword(s):  
Web Search ◽  
Relevance Ranking
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