scholarly journals Characterizing the Influence of Confirmation Bias on Web Search Behavior

2021 ◽  
Vol 12 ◽  
Author(s):  
Masaki Suzuki ◽  
Yusuke Yamamoto

In this study, we analyzed the relationship between confirmation bias, which causes people to preferentially view information that supports their opinions and beliefs, and web search behavior. In an online user study, we controlled confirmation bias by presenting prior information to participants that manipulated their impressions of health search topics and analyzed their behavioral logs during web search tasks. We found that web search users with poor health literacy and negative prior beliefs about the health search topic did not spend time examining the list of web search results, and these users demonstrated bias in webpage selection. In contrast, web search users with high health literacy and negative prior beliefs about the search topic spent more time examining the list of web search results. In addition, these users attempted to browse webpages that present different opinions. No significant difference in web search behavior was observed between users with positive prior beliefs about the search topic and those with neutral belief.

Author(s):  
Aboubakr Aqle ◽  
Dena Al-Thani ◽  
Ali Jaoua

AbstractThere are limited studies that are addressing the challenges of visually impaired (VI) users when viewing search results on a search engine interface by using a screen reader. This study investigates the effect of providing an overview of search results to VI users. We present a novel interactive search engine interface called InteractSE to support VI users during the results exploration stage in order to improve their interactive experience and web search efficiency. An overview of the search results is generated using an unsupervised machine learning approach to present the discovered concepts via a formal concept analysis that is domain-independent. These concepts are arranged in a multi-level tree following a hierarchical order and covering all retrieved documents that share maximal features. The InteractSE interface was evaluated by 16 legally blind users and compared with the Google search engine interface for complex search tasks. The evaluation results were obtained based on both quantitative (as task completion time) and qualitative (as participants’ feedback) measures. These results are promising and indicate that InteractSE enhances the search efficiency and consequently advances user experience. Our observations and analysis of the user interactions and feedback yielded design suggestions to support VI users when exploring and interacting with search results.


Author(s):  
Martin Feuz ◽  
Matthew Fuller ◽  
Felix Stalder

Web search engines have become indispensable tools for finding information online effectively. As the range of information, context and users of Internet searches has grown, the relationship between the search query, search interest and user has become more tenuous. Not all users are seeking the same information, even if they use the same query term. Thus, the quality of search results has, at least potentially, been decreasing. Search engines have begun to respond to this problem by trying to personalise search in order to deliver more relevant results to the users. A query is now evaluated in the context of a user’s search history and other data compiled into a personal profile and associated with statistical groups. This, at least, is the promise stated by the search engines themselves. This paper tries to assess the current reality of the personalisation of search results. We analyse the mechanisms of personalisation in the case of Google web search by empirically testing three commonly held assumptions about what personalisation does. To do this, we developed new digital methods which are explained here. The findings suggest that Google personal search does not fully provide the much-touted benefits for its search users. More likely, it seems to serve the interest of advertisers in providing more relevant audiences to them.


Author(s):  
Anselm Spoerri

This paper analyzes which pages and topics are the most popular on Wikipedia and why. For the period of September 2006 to January 2007, the 100 most visited Wikipedia pages in a month are identified and categorized in terms of the major topics of interest. The observed topics are compared with search behavior on the Web. Search queries, which are identical to the titles of the most popular Wikipedia pages, are submitted to major search engines and the positions of popular Wikipedia pages in the top 10 search results are determined. The presented data helps to explain how search engines, and Google in particular, fuel the growth and shape what is popular on Wikipedia.


Author(s):  
Veronica Maidel ◽  
Dmitry Epstein

Web search has become an integral part of everyday online activity. Existing research on search behavior offers an extensive and detailed account of what searchers do when they encounter the search results pages. Yet, there is limited inquiry into what drives the particular search decisions that are being made and what contextual factors drive this behavior. This study provides a user-centric inquiry focused on in-depth detailed investigation of search-related decision-making processes. It builds on data collected through analysis of structured observations of young adults performing searches on their personal laptops. It focuses explicitly on the decisions the users make after completing a query and facing a list of search results. The study reveals a pattern of sophisticated use of a variety of explicit cues, tacit and contextual knowledge, as well as employment of an incremental search strategy.


2021 ◽  
Author(s):  
Ozgur Turetken ◽  
Ramesh Sharda

The result of a typical web search is often overwhelming. It is very difficult to explore the textual listing of the resulting documents, which may be in the thousands. In order to improve the utility of the search experience, we explore presenting search results through clustering and a zoomable two-dimensional map (zoomable treemap). Furthermore, we apply the fisheye view technique to this map of web search clusters to provide details in context. In this study, we report on our evaluation of these presentation features. The particular interfaces evaluated were: (1) a textual list, (2) a zoomable two-dimensional map of the clustered results, and (3) a fisheye version of the zoomable two dimensional map where the results were clustered. We found that subjects completed search tasks faster with the visual interfaces than with the textual interface, and faster with the fisheye interface than just the zoomable interface. Based on the findings, we conclude that there is promise in the use of clustering and visualization with a fisheye zooming capability in the exploration of web search results.


2021 ◽  
Author(s):  
Ozgur Turetken ◽  
Ramesh Sharda

The result of a typical web search is often overwhelming. It is very difficult to explore the textual listing of the resulting documents, which may be in the thousands. In order to improve the utility of the search experience, we explore presenting search results through clustering and a zoomable two-dimensional map (zoomable treemap). Furthermore, we apply the fisheye view technique to this map of web search clusters to provide details in context. In this study, we report on our evaluation of these presentation features. The particular interfaces evaluated were: (1) a textual list, (2) a zoomable two-dimensional map of the clustered results, and (3) a fisheye version of the zoomable two dimensional map where the results were clustered. We found that subjects completed search tasks faster with the visual interfaces than with the textual interface, and faster with the fisheye interface than just the zoomable interface. Based on the findings, we conclude that there is promise in the use of clustering and visualization with a fisheye zooming capability in the exploration of web search results.


2019 ◽  
Vol 71 (3) ◽  
pp. 368-391 ◽  
Author(s):  
Markus Kattenbeck ◽  
David Elsweiler

Purpose It is well known that information behaviour can be biased in countless ways and that users of web search engines have difficulty in assessing the credibility of results. Yet, little is known about how search engine result page (SERP) listings are used to judge credibility and in which if any way such judgements are biased. The paper aims to discuss these issues. Design/methodology/approach Two studies are presented. The first collects data by means of a controlled, web-based user study (N=105). Studying judgements for three controversial topics, the paper examines the extent to which users agree on credibility, the extent to which judgements relate to those applied by objective assessors and to what extent judgements can be predicted by the users’ position on and prior knowledge of the topic. A second, qualitative study (N=9) utilises the same setup; however, transcribed think-aloud protocols provide an understanding of the cues participants use to estimate credibility. Findings The first study reveals that users are very uncertain when assessing credibility and their impressions often diverge from objective judges who have fact checked the sources. Little evidence is found indicating that judgements are biased by prior beliefs or knowledge, but differences are observed in the accuracy of judgements across topics. Qualitatively analysing think-aloud transcripts from participants think-aloud reveals ten categories of cues, which participants used to determine the credibility of results. Despite short listings, participants utilised diverse cues for the same listings. Even when the same cues were identified and utilised, different participants often interpreted these differently. Example transcripts show how participants reach varying conclusions, illustrate common mistakes made and highlight problems with existing SERP listings. Originality/value This study offers a novel perspective on how the credibility of SERP listings is interpreted when assessing search results. Especially striking is how the same short snippets provide diverse informational cues and how these cues can be interpreted differently depending on the user and his or her background. This finding is significant in terms of how search engine results should be presented and opens up the new challenge of discovering technological solutions, which allow users to better judge the credibility of information sources on the web.


2008 ◽  
Vol 2008 ◽  
pp. 1-14 ◽  
Author(s):  
Tomi Heimonen

Designing an effective mobile search user interface is challenging, as interacting with the results is often complicated by the lack of available screen space and limited interaction methods. We present Mobile Findex, a mobile search user interface that uses automatically computed result clusters to provide the user with an overview of the result set. In addition, it utilizes a focus-plus-context result list presentation combined with an intuitive browsing method to aid the user in the evaluation of results. A user study with 16 participants was carried out to evaluate Mobile Findex. Subjective evaluations show that Mobile Findex was clearly preferred by the participants over the traditional ranked result list in terms of ease of finding relevant results, suitability to tasks, and perceived efficiency. While the use of categories resulted in a lower rate of nonrelevant result selections and better precision in some tasks, an overall significant difference in search performance was not observed.


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