Search (28 results, page 1 of 2)

  • × year_i:[2010 TO 2020}
  • × theme_ss:"Benutzerstudien"
  1. Willson, R.; Given, L.M.: ¬The effect of spelling and retrieval system familiarity on search behavior in online public access catalogs : a mixed methods study (2010) 0.03
    0.028375676 = product of:
      0.085127026 = sum of:
        0.04816959 = weight(_text_:wide in 4042) [ClassicSimilarity], result of:
          0.04816959 = score(doc=4042,freq=2.0), product of:
            0.19679762 = queryWeight, product of:
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.044416238 = queryNorm
            0.24476713 = fieldWeight in 4042, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.4307585 = idf(docFreq=1430, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4042)
        0.036957435 = weight(_text_:web in 4042) [ClassicSimilarity], result of:
          0.036957435 = score(doc=4042,freq=4.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.25496176 = fieldWeight in 4042, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4042)
      0.33333334 = coord(2/6)
    
    Abstract
    Although technology can often correct spelling errors, the complex tasks of information searching and retrieval in an online public access catalog (OPAC) are made more difficult by these errors in users' input and bibliographic records. This study examines the search behaviors of 38 university students, divided into groups with either easy-to-spell or difficult-to-spell search terms, who were asked to find items in the OPAC with these search terms. Search behaviors and strategy use in the OPAC and on the World Wide Web (WWW) were examined. In general, students used familiar Web resources to check their spelling or discover more about the assigned topic. Students with difficult-to-spell search terms checked spelling more often, changed search strategies to look for the general topic and had fewer successful searches. Students unable to find the correct spelling of a search term were unable to complete their search. Students tended to search the OPAC as they would search a search engine, with few search terms or complex search strategies. The results of this study have implications for spell checking, user-focused OPAC design, and cataloging. Students' search behaviors are discussed by expanding Thatcher's (2006) Information-Seeking Process and Tactics for the WWW model to include OPACs.
  2. Spink, A.; Danby, S.; Mallan, K.; Butler, C.: Exploring young children's web searching and technoliteracy (2010) 0.02
    0.015087811 = product of:
      0.090526864 = sum of:
        0.090526864 = weight(_text_:web in 3623) [ClassicSimilarity], result of:
          0.090526864 = score(doc=3623,freq=24.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.6245262 = fieldWeight in 3623, product of:
              4.8989797 = tf(freq=24.0), with freq of:
                24.0 = termFreq=24.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3623)
      0.16666667 = coord(1/6)
    
    Abstract
    Purpose - This paper aims to report findings from an exploratory study investigating the web interactions and technoliteracy of children in the early childhood years. Previous research has studied aspects of older children's technoliteracy and web searching; however, few studies have analyzed web search data from children younger than six years of age. Design/methodology/approach - The study explored the Google web searching and technoliteracy of young children who are enrolled in a "preparatory classroom" or kindergarten (the year before young children begin compulsory schooling in Queensland, Australia). Young children were video- and audio-taped while conducting Google web searches in the classroom. The data were qualitatively analysed to understand the young children's web search behaviour. Findings - The findings show that young children engage in complex web searches, including keyword searching and browsing, query formulation and reformulation, relevance judgments, successive searches, information multitasking and collaborative behaviours. The study results provide significant initial insights into young children's web searching and technoliteracy. Practical implications - The use of web search engines by young children is an important research area with implications for educators and web technologies developers. Originality/value - This is the first study of young children's interaction with a web search engine.
  3. Spink, A.; Du, J.T.: Toward a Web search model : integrating multitasking, cognitive coordination, and cognitive shifts (2011) 0.01
    0.012319146 = product of:
      0.07391487 = sum of:
        0.07391487 = weight(_text_:web in 4624) [ClassicSimilarity], result of:
          0.07391487 = score(doc=4624,freq=16.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.5099235 = fieldWeight in 4624, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4624)
      0.16666667 = coord(1/6)
    
    Abstract
    Limited research has investigated the role of multitasking, cognitive coordination, and cognitive shifts during web search. Understanding these three behaviors is crucial to web search model development. This study aims to explore characteristics of multitasking behavior, types of cognitive shifts, and levels of cognitive coordination as well as the relationship between them during web search. Data collection included pre- and postquestionnaires, think-aloud protocols, web search logs, observations, and interviews with 42 graduate students who conducted 315 web search sessions with 221 information problems. Results show that web search is a dynamic interaction including the ordering of multiple information problems and the generation of evolving information problems, including task switching, multitasking, explicit task and implicit mental coordination, and cognitive shifting. Findings show that explicit task-level coordination is closely linked to multitasking, and implicit cognitive-level coordination is related to the task-coordination process; including information problem development and task switching. Coordination mechanisms directly result in cognitive state shifts including strategy, evaluation, and view states that affect users' holistic shifts in information problem understanding and knowledge contribution. A web search model integrating multitasking, cognitive coordination, and cognitive shifts (MCC model) is presented. Implications and further research also are discussed.
  4. Huvila, I.: Mining qualitative data on human information behaviour from the Web (2010) 0.01
    0.010561468 = product of:
      0.063368805 = sum of:
        0.063368805 = weight(_text_:web in 4676) [ClassicSimilarity], result of:
          0.063368805 = score(doc=4676,freq=6.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.43716836 = fieldWeight in 4676, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4676)
      0.16666667 = coord(1/6)
    
    Abstract
    This paper discusses an approach of collecting qualitative data on human information behaviour that is based on mining web data using search engines. The approach is technically the same that has been used for some time in webometric research to make statistical inferences on web data, but the present paper shows how the same tools and data collecting methods can be used to gather data for qualitative data analysis on human information behaviour.
  5. Choi, Y.: Effects of contextual factors on image searching on the Web (2010) 0.01
    0.009052687 = product of:
      0.054316122 = sum of:
        0.054316122 = weight(_text_:web in 3995) [ClassicSimilarity], result of:
          0.054316122 = score(doc=3995,freq=6.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.37471575 = fieldWeight in 3995, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=3995)
      0.16666667 = coord(1/6)
    
    Abstract
    This research examined college students' image searching processes on the Web. The study's objective was to collect empirical data on students' search needs and identify what contextual factors had a significant influence on their image searching tactics. While confirming common search behaviors such as Google-dominant use, short queries, rare use of advanced search options, and checking few search result pages, the findings also revealed a significantly different effect of contextual factors on the tactics of querying and navigating, performance, and relevance judgment. In particular, interaction activities were differentiated by task goals, level of searching expertise, and work task stages. The results suggested that context-sensitive services and interface features would better suit Web users' actual needs and enhance their searching experience.
  6. Xie, I.; Joo, S.: Transitions in search tactics during the Web-based search process (2010) 0.01
    0.0075439056 = product of:
      0.045263432 = sum of:
        0.045263432 = weight(_text_:web in 4097) [ClassicSimilarity], result of:
          0.045263432 = score(doc=4097,freq=6.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.3122631 = fieldWeight in 4097, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4097)
      0.16666667 = coord(1/6)
    
    Abstract
    Although many studies have identified search tactics, few studies have explored tactic transitions. This study investigated the transitions of search tactics during the Web-based search process. Bringing their own 60 search tasks, 31 participants, representing the general public with different demographic characteristics, participated in the study. Data collected from search logs and verbal protocols were analyzed by applying both qualitative and quantitative methods. The findings of this study show that participants exhibited some unique Web search tactics. They overwhelmingly employed accessing and evaluating tactics; they used fewer tactics related to modifying search statements, monitoring the search process, organizing search results, and learning system features. The contributing factors behind applying most and least frequently employed search tactics are in relation to users' efforts, trust in information retrieval (IR) systems, preference, experience, and knowledge as well as limitation of the system design. A matrix of search-tactic transitions was created to show the probabilities of transitions from one tactic to another. By applying fifth-order Markov chain, the results also presented the most common search strategies representing patterns of tactic transition occurring at the beginning, middle, and ending phases within one search session. The results of this study generated detailed and useful guidance for IR system design to support the most frequently applied tactics and transitions, to reduce unnecessary transitions, and support transitions at different phases.
  7. Kim, J.; Thomas, P.; Sankaranarayana, R.; Gedeon, T.; Yoon, H.-J.: Eye-tracking analysis of user behavior and performance in web search on large and small screens (2015) 0.01
    0.0075439056 = product of:
      0.045263432 = sum of:
        0.045263432 = weight(_text_:web in 1666) [ClassicSimilarity], result of:
          0.045263432 = score(doc=1666,freq=6.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.3122631 = fieldWeight in 1666, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1666)
      0.16666667 = coord(1/6)
    
    Abstract
    In recent years, searching the web on mobile devices has become enormously popular. Because mobile devices have relatively small screens and show fewer search results, search behavior with mobile devices may be different from that with desktops or laptops. Therefore, examining these differences may suggest better, more efficient designs for mobile search engines. In this experiment, we use eye tracking to explore user behavior and performance. We analyze web searches with 2 task types on 2 differently sized screens: one for a desktop and the other for a mobile device. In addition, we examine the relationships between search performance and several search behaviors to allow further investigation of the differences engendered by the screens. We found that users have more difficulty extracting information from search results pages on the smaller screens, although they exhibit less eye movement as a result of an infrequent use of the scroll function. However, in terms of search performance, our findings suggest that there is no significant difference between the 2 screens in time spent on search results pages and the accuracy of finding answers. This suggests several possible ideas for the presentation design of search results pages on small devices.
  8. Huurnink, B.; Hollink, L.; Heuvel, W. van den; Rijke, M. de: Search behavior of media professionals at an audiovisual archive : a transaction log analysis (2010) 0.01
    0.006871327 = product of:
      0.04122796 = sum of:
        0.04122796 = product of:
          0.08245592 = sum of:
            0.08245592 = weight(_text_:programs in 3468) [ClassicSimilarity], result of:
              0.08245592 = score(doc=3468,freq=2.0), product of:
                0.25748047 = queryWeight, product of:
                  5.79699 = idf(docFreq=364, maxDocs=44218)
                  0.044416238 = queryNorm
                0.32024145 = fieldWeight in 3468, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  5.79699 = idf(docFreq=364, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3468)
          0.5 = coord(1/2)
      0.16666667 = coord(1/6)
    
    Abstract
    Finding audiovisual material for reuse in new programs is an important activity for news producers, documentary makers, and other media professionals. Such professionals are typically served by an audiovisual broadcast archive. We report on a study of the transaction logs of one such archive. The analysis includes an investigation of commercial orders made by the media professionals and a characterization of sessions, queries, and the content of terms recorded in the logs. One of our key findings is that there is a strong demand for short pieces of audiovisual material in the archive. In addition, while searchers are generally able to quickly navigate to a usable audiovisual broadcast, it takes them longer to place an order when purchasing a subsection of a broadcast than when purchasing an entire broadcast. Another key finding is that queries predominantly consist of (parts of) broadcast titles and of proper names. Our observations imply that it may be beneficial to increase support for fine-grained access to audiovisual material, for example, through manual segmentation or content-based analysis.
  9. Foss, E.; Druin, A.; Yip, J.; Ford, W.; Golub, E.; Hutchinson, H.: Adolescent search roles (2013) 0.01
    0.0065539777 = product of:
      0.039323866 = sum of:
        0.039323866 = weight(_text_:computer in 536) [ClassicSimilarity], result of:
          0.039323866 = score(doc=536,freq=2.0), product of:
            0.16231956 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.044416238 = queryNorm
            0.24226204 = fieldWeight in 536, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.046875 = fieldNorm(doc=536)
      0.16666667 = coord(1/6)
    
    Abstract
    In this article, we present an in-home observation and in-context research study investigating how 38 adolescents aged 14-17 search on the Internet. We present the search trends adolescents display and develop a framework of search roles that these trends help define. We compare these trends and roles to similar trends and roles found in prior work with children ages 7, 9, and 11. We use these comparisons to make recommendations to adult stakeholders such as researchers, designers, and information literacy educators about the best ways to design search tools for children and adolescents, as well as how to use the framework of searching roles to find better methods of educating youth searchers. Major findings include the seven roles of adolescent searchers, and evidence that adolescents are social in their computer use, have a greater knowledge of sources than younger children, and that adolescents are less frustrated by searching tasks than younger children.
  10. Gwizdka, J.: Distribution of cognitive load in Web search (2010) 0.01
    0.006159573 = product of:
      0.036957435 = sum of:
        0.036957435 = weight(_text_:web in 4095) [ClassicSimilarity], result of:
          0.036957435 = score(doc=4095,freq=4.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.25496176 = fieldWeight in 4095, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4095)
      0.16666667 = coord(1/6)
    
    Abstract
    The search task and the system both affect the demand on cognitive resources during information search. In some situations the demands may become too high for a person. This article has a three-fold goal. First, it presents and critiques methods to measure cognitive load. Second, it explores the distribution of load across search task stages. Finally, it seeks to improve our understanding of factors affecting cognitive load levels in information search. To this end, a controlled Web search experiment with 48 participants was conducted. Interaction logs were used to segment search tasks semiautomatically into task stages. Cognitive load was assessed using a new variant of the dual-task method. Average cognitive load was found to vary by search task stages. It was significantly higher during query formulation and user description of a relevant document as compared to examining search results and viewing individual documents. Semantic information shown next to the search results lists in one of the studied interfaces was found to decrease mental demands during query formulation and examination of the search results list. These findings demonstrate that changes in dynamic cognitive load can be detected within search tasks. Dynamic assessment of cognitive load is of core interest to information science because it enriches our understanding of cognitive demands imposed on people engaged in the search process by a task and the interactive information retrieval system employed.
  11. Zhang, Y.: Dimensions and elements of people's mental models of an information-rich Web space (2010) 0.01
    0.006159573 = product of:
      0.036957435 = sum of:
        0.036957435 = weight(_text_:web in 4098) [ClassicSimilarity], result of:
          0.036957435 = score(doc=4098,freq=4.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.25496176 = fieldWeight in 4098, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4098)
      0.16666667 = coord(1/6)
    
    Abstract
    Although considered proxies for people to interact with a system, mental models have produced limited practical implications for system design. This might be due to the lack of exploration of the elements of mental models resulting from the methodological challenge of measuring mental models. This study employed a new method, concept listing, to elicit people's mental models of an information-rich space, MedlinePlus, after they interacted with the system for 5 minutes. Thirty-eight undergraduate students participated in the study. The results showed that, in this short period of time, participants perceived MedlinePlus from many different aspects in relation to four components: the system as a whole, its content, information organization, and interface. Meanwhile, participants expressed evaluations of or emotions about the four components. In terms of the procedural knowledge, an integral part of people's mental models, only one participant identified a strategy more aligned to the capabilities of MedlinePlus to solve a hypothetical task; the rest planned to use general search and browse strategies. The composition of participants' mental models of MedlinePlus was consistent with that of their models of information-rich Web spaces in general.
  12. Balatsoukas, P.; Ruthven, I.: ¬An eye-tracking approach to the analysis of relevance judgments on the Web : the case of Google search engine (2012) 0.01
    0.006159573 = product of:
      0.036957435 = sum of:
        0.036957435 = weight(_text_:web in 379) [ClassicSimilarity], result of:
          0.036957435 = score(doc=379,freq=4.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.25496176 = fieldWeight in 379, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=379)
      0.16666667 = coord(1/6)
    
    Abstract
    Eye movement data can provide an in-depth view of human reasoning and the decision-making process, and modern information retrieval (IR) research can benefit from the analysis of this type of data. The aim of this research was to examine the relationship between relevance criteria use and visual behavior in the context of predictive relevance judgments. To address this objective, a multimethod research design was employed that involved observation of participants' eye movements, talk-aloud protocols, and postsearch interviews. Specifically, the results reported in this article came from the analysis of 281 predictive relevance judgments made by 24 participants using the Google search engine. We present a novel stepwise methodological framework for the analysis of relevance judgments and eye movements on the Web and show new patterns of relevance criteria use during predictive relevance judgment. For example, the findings showed an effect of ranking order and surrogate components (Title, Summary, and URL) on the use of relevance criteria. Also, differences were observed in the cognitive effort spent between very relevant and not relevant judgments. We conclude with the implications of this study for IR research.
  13. Vuong, T.; Saastamoinen, M.; Jacucci, G.; Ruotsalo, T.: Understanding user behavior in naturalistic information search tasks (2019) 0.01
    0.005461648 = product of:
      0.03276989 = sum of:
        0.03276989 = weight(_text_:computer in 5419) [ClassicSimilarity], result of:
          0.03276989 = score(doc=5419,freq=2.0), product of:
            0.16231956 = queryWeight, product of:
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.044416238 = queryNorm
            0.20188503 = fieldWeight in 5419, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.6545093 = idf(docFreq=3109, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5419)
      0.16666667 = coord(1/6)
    
    Abstract
    Understanding users' search behavior has largely relied on the information available from search engine logs, which provide limited information about the contextual factors affecting users' behavior. Consequently, questions such as how users' intentions, task goals, and substances of the users' tasks affect search behavior, as well as what triggers information needs, remain largely unanswered. We report an experiment in which naturalistic information search behavior was captured by analyzing 24/7 continuous recordings of information on participants' computer screens. Written task diaries describing the participants' tasks were collected and used as real-life task contexts for further categorization. All search tasks were extracted and classified under various task categories according to users' intentions, task goals, and substances of the tasks. We investigated the effect of different task categories on three behavioral factors: search efforts, content-triggers, and application context. Our results suggest four findings: (i) Search activity is integrally associated with the users' creative processes. The content users have seen prior to searching more often triggers search, and is used as a query, within creative tasks. (ii) Searching within intellectual and creative tasks is more time-intensive, while search activity occurring as a part of daily routine tasks is associated with more frequent searching within a search task. (iii) Searching is more often induced from utility applications in tasks demanding a degree of intellectual effort. (iv) Users' leisure information-seeking activity is occurring inherently within social media services or comes from social communication platforms. The implications of our findings for information access and management systems are discussed.
  14. Clewley, N.; Chen, S.Y.; Liu, X.: Cognitive styles and search engine preferences : field dependence/independence vs holism/serialism (2010) 0.00
    0.004355476 = product of:
      0.026132854 = sum of:
        0.026132854 = weight(_text_:web in 3961) [ClassicSimilarity], result of:
          0.026132854 = score(doc=3961,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.18028519 = fieldWeight in 3961, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3961)
      0.16666667 = coord(1/6)
    
    Abstract
    Purpose - Cognitive style has been identified to be significantly influential in deciding users' preferences of search engines. In particular, Witkin's field dependence/independence has been widely studied in the area of web searching. It has been suggested that this cognitive style has conceptual links with the holism/serialism. This study aims to investigate the differences between the field dependence/independence and holism/serialism. Design/methodology/approach - An empirical study was conducted with 120 students from a UK university. Riding's cognitive style analysis (CSA) and Ford's study preference questionnaire (SPQ) were used to identify the students' cognitive styles. A questionnaire was designed to identify users' preferences for the design of search engines. Data mining techniques were applied to analyse the data obtained from the empirical study. Findings - The results highlight three findings. First, a fundamental link is confirmed between the two cognitive styles. Second, the relationship between field dependent users and holists is suggested to be more prominent than that of field independent users and serialists. Third, the interface design preferences of field dependent and field independent users can be split more clearly than those of holists and serialists. Originality/value - The contributions of this study include a deeper understanding of the similarities and differences between field dependence/independence and holists/serialists as well as proposing a novel methodology for data analyses.
  15. Kules, B.; Capra, R.: Influence of training and stage of search on gaze behavior in a library catalog faceted search interface (2012) 0.00
    0.004355476 = product of:
      0.026132854 = sum of:
        0.026132854 = weight(_text_:web in 4129) [ClassicSimilarity], result of:
          0.026132854 = score(doc=4129,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.18028519 = fieldWeight in 4129, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4129)
      0.16666667 = coord(1/6)
    
    Abstract
    This study examined how searchers interact with a web-based, faceted library catalog when conducting exploratory searches. It applied multiple methods, including eye tracking and stimulated recall interviews, to investigate important aspects of faceted search interface use, specifically: (a) searcher gaze behavior-what components of the interface searchers look at; (b) how gaze behavior differs when training is and is not provided; (c) how gaze behavior changes as searchers become familiar with the interface; and (d) how gaze behavior differs depending on the stage of the search process. The results confirm previous findings that facets account for approximately 10-30% of interface use. They show that providing a 60-second video demonstration increased searcher use of facets. However, searcher use of the facets did not evolve during the study session, which suggests that searchers may not, on their own, rapidly apply the faceted interfaces. The findings also suggest that searcher use of interface elements varied by the stage of their search during the session, with higher use of facets during decision-making stages. These findings will be of interest to librarians and interface designers who wish to maximize the value of faceted searching for patrons, as well as to researchers who study search behavior.
  16. Nicholas, D.; Clark, D.; Rowlands, I.; Jamali, H.R.: Information on the go : a case study of Europeana mobile users (2013) 0.00
    0.004355476 = product of:
      0.026132854 = sum of:
        0.026132854 = weight(_text_:web in 961) [ClassicSimilarity], result of:
          0.026132854 = score(doc=961,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.18028519 = fieldWeight in 961, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=961)
      0.16666667 = coord(1/6)
    
    Abstract
    According to estimates the mobile device will soon be the main platform for searching the web, and yet our knowledge of how mobile consumers use information, and how that differs from desktops/laptops users, is imperfect. The paper sets out to correct this through an analysis of the logs of a major cultural website, Europeana. The behavior of nearly 70,000 mobile users was examined over a period of more than a year and compared with that for PC users of the same site and for the same period. The analyses conducted include: size and growth of use, time patterns of use; geographical location of users, digital collections used; comparative information-seeking behavior using dashboard metrics, clustering of users according to their information seeking, and user satisfaction. The main findings were that mobile users were the fastest-growing group and will rise rapidly to a million by December 2012 and that their visits were very different in the aggregate from those arising from fixed platforms. Mobile visits could be described as being information "lite": typically shorter, less interactive, and less content viewed per visit. Use took a social rather than office pattern, with mobile use peaking at nights and weekends. The variation between different mobile devices was large, with information seeking on the iPad similar to that for PCs and laptops and that for smartphones very different indeed. The research further confirms that information-seeking behavior is platform-specific and the latest platforms are changing it all again. Websites will have to adapt.
  17. White, R.W.: Belief dynamics in web search (2014) 0.00
    0.004355476 = product of:
      0.026132854 = sum of:
        0.026132854 = weight(_text_:web in 1523) [ClassicSimilarity], result of:
          0.026132854 = score(doc=1523,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.18028519 = fieldWeight in 1523, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1523)
      0.16666667 = coord(1/6)
    
  18. Williams, P.; Hennig, C.: Effect of web page menu orientation on retrieving information by people with learning disabilities (2015) 0.00
    0.004355476 = product of:
      0.026132854 = sum of:
        0.026132854 = weight(_text_:web in 1723) [ClassicSimilarity], result of:
          0.026132854 = score(doc=1723,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.18028519 = fieldWeight in 1723, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1723)
      0.16666667 = coord(1/6)
    
  19. Zhitomirsky-Geffet, M.; Bar-Ilan, J.; Levene, M.: Analysis of change in users' assessment of search results over time (2017) 0.00
    0.004355476 = product of:
      0.026132854 = sum of:
        0.026132854 = weight(_text_:web in 3593) [ClassicSimilarity], result of:
          0.026132854 = score(doc=3593,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.18028519 = fieldWeight in 3593, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3593)
      0.16666667 = coord(1/6)
    
    Abstract
    We present the first systematic study of the influence of time on user judgements for rankings and relevance grades of web search engine results. The goal of this study is to evaluate the change in user assessment of search results and explore how users' judgements change. To this end, we conducted a large-scale user study with 86 participants who evaluated 2 different queries and 4 diverse result sets twice with an interval of 2 months. To analyze the results we investigate whether 2 types of patterns of user behavior from the theory of categorical thinking hold for the case of evaluation of search results: (a) coarseness and (b) locality. To quantify these patterns we devised 2 new measures of change in user judgements and distinguish between local (when users swap between close ranks and relevance values) and nonlocal changes. Two types of judgements were considered in this study: (a) relevance on a 4-point scale, and (b) ranking on a 10-point scale without ties. We found that users tend to change their judgements of the results over time in about 50% of cases for relevance and in 85% of cases for ranking. However, the majority of these changes were local.
  20. Unkel, J.; Haas, A.: ¬The effects of credibility cues on the selection of search engine results (2017) 0.00
    0.004355476 = product of:
      0.026132854 = sum of:
        0.026132854 = weight(_text_:web in 3752) [ClassicSimilarity], result of:
          0.026132854 = score(doc=3752,freq=2.0), product of:
            0.14495286 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.044416238 = queryNorm
            0.18028519 = fieldWeight in 3752, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3752)
      0.16666667 = coord(1/6)
    
    Abstract
    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?=?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).