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The Good, the Bad, and the Random: An Eye-Tracking Study of Ad Quality in Web Search
"... We investigate how people interact with Web search engine result pages using eye-tracking. While previous research has focused on the visual attention devoted to the 10 organic search results, this paper examines other components of contemporary search engines, such as ads and related searches. We s ..."
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We investigate how people interact with Web search engine result pages using eye-tracking. While previous research has focused on the visual attention devoted to the 10 organic search results, this paper examines other components of contemporary search engines, such as ads and related searches. We systematically varied the type of task (informational or navigational), the quality of the ads (relevant or irrelevant to the query), and the sequence in which ads of different quality were presented. We measured the effects of these variables on the distribution of visual attention and on task performance. Our results show significant effects of each variable. The amount of visual attention that people devote to organic results depends on both task type and ad quality. The amount of visual attention that people devote to ads depends on their quality, but not the type of task. Interestingly, the sequence and predictability of ad quality is also an important factor in determining how much people attend to ads. When the quality of ads varied randomly from task to task, people paid little attention to the ads, even when they were good. These results further our understanding of how attention devoted to search results is influenced by other page elements, and how previous search experiences influence how people attend to the current page.
Ranking of wikipedia articles in search engines revisited: Fair ranking for reasonable quality
- Journal of the American Society for Information Science and Technology
, 2011
"... This paper aims to review the fiercely discussed question of whether the ranking of Wikipedia articles in search engines is justified by the quality of the articles. After an overview of current research on information quality in Wikipedia, a summary of the extended discussion on the quality of ency ..."
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This paper aims to review the fiercely discussed question of whether the ranking of Wikipedia articles in search engines is justified by the quality of the articles. After an overview of current research on information quality in Wikipedia, a summary of the extended discussion on the quality of encyclopedic entries in general is given. On this basis, a heuristic method for evaluating Wikipedia entries is developed and applied to Wikipedia articles that scored highly in a search engine retrieval effectiveness test and compared with the relevance judgment of jurors. In all search engines tested, Wikipedia results are unanimously judged better by the jurors than other results on the corresponding results position. Relevance judgments often roughly correspond with the results from the heuristic evaluation. Cases in which high relevance judgments are not in accordance with the comparatively low score from the heuristic evaluation are interpreted as an indicator of a high degree of trust in Wikipedia. One of the systemic shortcomings of Wikipedia lies in its necessarily incoherent user model. A further tuning of the suggested criteria catalogue, for instance the different weighing of the supplied criteria, could serve as a starting point for a user model differentiated evaluation of Wikipedia articles. Approved methods of quality evaluation of reference works are applied to Wikipedia articles and integrated with the question of search engine evaluation. Keywords—Search engines, Wikipedia, lexicographical quality, retrieval effectiveness "Utility ought to be the principal intention of every publication. Wherever this intention does not plainly appear, neither the books nor their authors have the smallest claim to the approbation of mankind. " (William Smellie: Preface of the 1st edition of the Encyclopedia Britannica 1768) 1.
New perspectives on Web search engine research
"... Purpose – The purpose of this chapter is to give an overview of the context of Web search and search engine-‐related research, as well as to introduce the reader to the sections and chapters of the book. Methodology/approach – We review literature dealing with various aspects of search engines, with ..."
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Purpose – The purpose of this chapter is to give an overview of the context of Web search and search engine-‐related research, as well as to introduce the reader to the sections and chapters of the book. Methodology/approach – We review literature dealing with various aspects of search engines, with special emphasis on emerging areas of Web searching, search engine evaluation going beyond traditional methods, and new perspectives on Web searching. Findings – The approaches to studying Web search engines are manifold. Given the importance of Web search engines for knowledge acquisition, research from different perspectives needs to be integrated into a more cohesive perspective. Research limitations/implications – The chapter suggests a basis for research in the field and also introduces further research directions. Originality/value of paper – The chapter gives a concise overview of the topics dealt within the book and also shows directions for researchers interested in Web search engines.
Google Web Searches and Wikipedia Results: a Measurement Study
"... Abstract. How are users exposed to Wikipedia results, in return to their web searches? Where are such results positioned on the screen? In this study, we experimentally measure the ranking of Wikipedia pages on Google Italia. ..."
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Abstract. How are users exposed to Wikipedia results, in return to their web searches? Where are such results positioned on the screen? In this study, we experimentally measure the ranking of Wikipedia pages on Google Italia.
Deriving Query Intents from Web Search Engine Queries
, 2012
"... The purpose of this paper is to test the reliability of query intents derived from queries, either by the user who entered the query or by another juror. We report the findings of three studies: First, we conducted a large-scale classification study (approximately 50,000 queries) using a crowdsourci ..."
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The purpose of this paper is to test the reliability of query intents derived from queries, either by the user who entered the query or by another juror. We report the findings of three studies: First, we conducted a large-scale classification study (approximately 50,000 queries) using a crowdsourcing approach. Then, we used click-through data from a search engine log and validated the judgments given by the jurors from the crowdsourcing study. Finally, we conducted an online survey on a commercial search engine’s portal. Since we used the same queries for all three studies, we were able to compare the results and the effectiveness of the different approaches, as well. We found that neither the crowdsourcing approach using jurors who classified queries originating from other users, nor the questionnaire approach using searchers who were asked about their own query that they just entered into a web search engine, lead to satisfying results. This leads us to conclude that there is little understanding of the classification tasks, even though both groups of jurors were given detailed instructions. While we used manual classification, our research has important implications for automatic classification, as well. We must question the success of approaches using automatic classification and comparing its performance to a baseline from human jurors.
The influence of commercial intent of search . . .
, 2011
"... We carried out a retrieval effectiveness test on the three major web search engines (i.e., Google, Microsoft and Yahoo). In addition to relevance judgments, we classified the results according to their commercial intent and whether or not they carried any advertising. We found that all search engine ..."
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We carried out a retrieval effectiveness test on the three major web search engines (i.e., Google, Microsoft and Yahoo). In addition to relevance judgments, we classified the results according to their commercial intent and whether or not they carried any advertising. We found that all search engines provide a large number of results with a commercial intent. Google provides significantly more commercial results than the other search engines do. However, the commercial intent of a result did not influence jurors in their relevance judgments.
Credibility in Web Search Engines
"... Web search engines apply a variety of ranking signals to achieve user satisfaction, i.e., results pages that provide the best-possible results to the user. While these ranking signals implicitly consider credibility (e.g., by measuring popularity), explicit measures of credibility are not applied. I ..."
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Web search engines apply a variety of ranking signals to achieve user satisfaction, i.e., results pages that provide the best-possible results to the user. While these ranking signals implicitly consider credibility (e.g., by measuring popularity), explicit measures of credibility are not applied. In this chapter, credibility in Web search engines is discussed in a broad context: credibility as a measure for including documents in a search engine’s index, credibility as a ranking signal, credibility in the context of universal search results, and the possibility of using credibility as an explicit measure for ranking purposes. It is found that while search engines—at least to a certain extent—show credible results to their users, there is no fully integrated credibility framework for Web search engines.
RESEARCH ARTICLE l e
"... hr Schizophrenia is a chronic, severe, debilitating mental disorder [1,2], which ranks third in global burden among unwillingness to adhere to treatment [11], consequent relapse [12] and readmissions [8,13]. Athanasopoulou et al. BMC Medical Informatics and Decision Making 2013, 13:98 ..."
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hr Schizophrenia is a chronic, severe, debilitating mental disorder [1,2], which ranks third in global burden among unwillingness to adhere to treatment [11], consequent relapse [12] and readmissions [8,13]. Athanasopoulou et al. BMC Medical Informatics and Decision Making 2013, 13:98
