Search (668 results, page 2 of 34)

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Abstract

Inferring the gender of named entities present in a text has several practical applications in information sciences. Existing approaches toward name gender identification rely exclusively on using the gender distributions from labeled data. In the absence of such labeled data, these methods fail. In this article, we propose a two-stage model that is able to infer the gender of names present in text without requiring explicit name-gender labels. We use coreference resolution as the backbone for our proposed model. To aid coreference resolution where the existing contextual information does not suffice, we use a retrieval-assisted context aggregation framework. We demonstrate that state-of-the-art name gender inference is possible without supervision. Our proposed method matches or outperforms several supervised approaches and commercially used methods on five English language datasets from different domains.

Date

22. 3.2023 12:00:14

Source

Journal of the Association for Information Science and Technology. 74(2023) no.4, S.461-475

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Abstract

Collaboration is encouraged because it is believed to improve academic research, supported by indirect evidence in the form of more coauthored articles being more cited. Nevertheless, this might not reflect quality but increased self-citations or the "audience effect": citations from increased awareness through multiple author networks. We address this with the first science wide investigation into whether author numbers associate with journal article quality, using expert peer quality judgments for 122,331 articles from the 2014-20 UK national assessment. Spearman correlations between author numbers and quality scores show moderately strong positive associations (0.2-0.4) in the health, life, and physical sciences, but weak or no positive associations in engineering and social sciences, with weak negative/positive or no associations in various arts and humanities, and a possible negative association for decision sciences. This gives the first systematic evidence that greater numbers of authors associates with higher quality journal articles in the majority of academia outside the arts and humanities, at least for the UK. Positive associations between team size and citation counts in areas with little association between team size and quality also show that audience effects or other nonquality factors account for the higher citation rates of coauthored articles in some fields.

Date

22. 6.2023 18:11:50

Source

Journal of the Association for Information Science and Technology. 74(2023) no.7, S.791-810

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Abstract

Linked Open Data (LOD) are a set of principles for publishing structured, connected data available for reuse under an open license. The objective of this paper is to analyze the publishing of bibliographic data such as LOD, having as a product the elaboration of theoretical-methodological recommendations for the publication of these data, in an approach based on the ten best practices for publishing LOD, from the World Wide Web Consortium. The starting point was the conduction of a Systematic Review of Literature, where initiatives to publish bibliographic data such as LOD were identified. An empirical study of these institutions was also conducted. As a result, theoretical-methodological recommendations were obtained for the process of publishing bibliographic data such as LOD.

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Abstract

In this article we report on an experiment that tested how useful library-based guidelines are for measuring the integrity of information in the era of fake news. We found that the usefulness of these guidelines depends on at least three factors: weighting indicators (criteria), clear instructions, and context-specificity.

Source

Bibliothek: Forschung und Praxis. 44(2020) H.1, S.34-53

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Abstract

Purpose This paper aims to explore the information needs and information-seeking behaviours of the new generation of engineering designers. A survey study is used to approach what their information needs are, how these needs change during an engineering design project and how their information-seeking behaviours have been influenced by the newly developed information technologies (ITs). Through an in-depth analysis of the survey results, the key functions have been identified for the next-generation management systems. Design/methodology/approach The paper first proposed four hypotheses on the information needs and information-seeking behaviours of young engineers. Then, a survey study was undertaken to understand their information usage in terms of the information needs and information-seeking behaviours during a complete engineering design process. Through analysing the survey results, several findings were obtained and on this basis, further comparisons were made to discuss and evaluate the hypotheses. Findings The paper has revealed that the engineering designers' information needs will evolve throughout the engineering design project; thus, they should be assisted at several different levels. Although they intend to search information and knowledge on know-what and know-how, what they really require is the know-why knowledge in order to help them complete design tasks. Also, the paper has shown how the newly developed ITs and web-based applications have influenced the engineers' information-seeking practices. Research limitations/implications The research subjects chosen in this study are engineering students in universities who, although not as experienced as engineers in companies, do go through a complete design process with the tasks similar to industrial scenarios. In addition, the focus of this study is to understand the information-seeking behaviours of a new generation of design engineers, so that the development of next-generation information and knowledge management systems can be well informed. In this sense, the results obtained do reveal some new knowledge about the information-seeking behaviours during a general design process. Practical implications This paper first identifies the information needs and information-seeking behaviours of the new generation of engineering designers. On this basis, the varied ways to meet these needs and behaviours are discussed and elaborated. This intends to provide the key characteristics for the development of the next-generation knowledge management system for engineering design projects. Originality/value This paper proposes a novel means of exploring the future engineers' information needs and information-seeking behaviours in a collaborative working environment. It also characterises the key features and functions for the next generation of knowledge management systems for engineering design.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 72(2020) no.6, S.853-868

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Abstract

Purpose This study continues a long history of author co-citation analysis of the intellectual structure of information science into the time period of 2011-2020. It also examines changes in this structure from 2006-2010 through 2011-2015 to 2016-2020. Results will contribute to a better understanding of the information science research field. Design/methodology/approach The well-established procedures and techniques for author co-citation analysis were followed. Full records of research articles in core information science journals published during 2011-2020 were retrieved and downloaded from the Web of Science database. About 150 most highly cited authors in each of the two five-year time periods were selected from this dataset to represent this field, and their co-citation counts were calculated. Each co-citation matrix was input into SPSS for factor analysis, and results were visualized in Pajek. Factors were interpreted as specialties and labeled upon an examination of articles written by authors who load primarily on each factor. Findings The two-camp structure of information science continued to be present clearly. Bibliometric indicators for research evaluation dominated the Knowledge Domain Analysis camp during both fivr-year time periods, whereas interactive information retrieval (IR) dominated the IR camp during 2011-2015 but shared dominance with information behavior during 2016-2020. Bridging between the two camps became increasingly weaker and was only provided by the scholarly communication specialty during 2016-2020. The IR systems specialty drifted further away from the IR camp. The information behavior specialty experienced a deep slump during 2011-2020 in its evolution process. Altmetrics grew to dominate the Webometrics specialty and brought it to a sharp increase during 2016-2020. Originality/value Author co-citation analysis (ACA) is effective in revealing intellectual structures of research fields. Most related studies used term-based methods to identify individual research topics but did not examine the interrelationships between these topics or the overall structure of the field. The few studies that did discuss the overall structure paid little attention to the effect of changes to the source journals on the results. The present study does not have these problems and continues the long history of benchmark contributions to a better understanding of the information science field using ACA.

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Abstract

This paper reviews a large number of research achievements relevant to user privacy protection in an untrusted network environment, and then analyzes and evaluates their application limitations in personalized information retrieval, to establish the conditional constraints that an effective approach for user preference privacy protection in personalized information retrieval should meet, thus providing a basic reference for the solution of this problem. First, based on the basic framework of a personalized information retrieval platform, we establish a complete set of constraints for user preference privacy protection in terms of security, usability, efficiency, and accuracy. Then, we comprehensively review the technical features for all kinds of popular methods for user privacy protection, and analyze their application limitations in personalized information retrieval, according to the constraints of preference privacy protection. The results show that personalized information retrieval has higher requirements for users' privacy protection, i.e., it is required to comprehensively improve the security of users' preference privacy on the untrusted server-side, under the precondition of not changing the platform, algorithm, efficiency, and accuracy of personalized information retrieval. However, all kinds of existing privacy methods still cannot meet the above requirements. This paper is an important study attempt to the problem of user preference privacy protection of personalized information retrieval, which can provide a basic reference and direction for the further study of the problem.

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Abstract

Purpose This paper investigates how school teachers look for informational texts for their classrooms. Access to current, varied and authentic informational texts improves learning outcomes for K-12 students, but many teachers lack resources to expand and update readings. The Web offers freely available resources, but finding suitable ones is time-consuming. This research lays the groundwork for building tools to ease that burden. Design/methodology/approach This paper reports qualitative findings from a study in two stages: (1) a set of semistructured interviews, based on the critical incident technique, eliciting teachers' information-seeking practices and challenges; and (2) observations of teachers using a prototype teaching-oriented news search tool under a think-aloud protocol. Findings Teachers articulated different objectives and ways of using readings in their classrooms, goals and self-reported practices varied by experience level. Teachers struggled to formulate queries that are likely to return readings on specific course topics, instead searching directly for abstract topics. Experience differences did not translate into observable differences in search skill or success in the lab study. Originality/value There is limited work on teachers' information-seeking practices, particularly on how teachers look for texts for classroom use. This paper describes how teachers look for information in this context, setting the stage for future development and research on how to support this use case. Understanding and supporting teachers looking for information is a rich area for future research, due to the complexity of the information need and the fact that teachers are not looking for information for themselves.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 72(2020) no.5, S.725-744

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Abstract

We present an overview of the NTCIR Math Tasks organized during NTCIR-10, 11, and 12. These tasks are primarily dedicated to techniques for searching mathematical content with formula expressions. In this chapter, we first summarize the task design and introduce test collections generated in the tasks. We also describe the features and main challenges of mathematical information retrieval systems and discuss future perspectives in the field.

Series

¬The Information retrieval series, vol 43

Source

Evaluating information retrieval and access tasks. Eds.: Sakai, T., Oard, D., Kando, N. [https://doi.org/10.1007/978-981-15-5554-1_12]

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Abstract

In this article we report on an experiment that tested how useful library-based guidelines are for measuring the integrity of information in the era of fake news. We found that the usefulness of these guidelines depends on at least three factors: weighting indicators (criteria), clear instructions, and context-specificity.

Source

Bibliothek: Forschung und Praxis. 44(2020) H.1, S.255-261

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Abstract

The information schools, also referred to as iField schools, are leaders in data science education. This study aims to develop a data science graduate curriculum model from an information science perspective to support iField schools in developing data science graduate education. In June 2020, information about 96 data science graduate programs from iField schools worldwide was collected and analyzed using a mixed research method based on inductive content analysis. A wide range of data science competencies and skills development and 12 knowledge topics covered by the curriculum were obtained. The humanistic model is further taken as the theoretical and methodological basis for course model construction, and 12 course knowledge topics are reconstructed into 4 course modules, including (a) data-driven methods and techniques; (b) domain knowledge; (c) legal, moral, and ethical aspects of data; and (d) shaping and developing personal traits, and human-centered data science graduate curriculum model is formed. At the end of the study, the wide application prospect of this model is discussed.

Source

Journal of the Association for Information Science and Technology. 74(2023) no.6, S.623-640

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Abstract

For laypeople, searching online health information resources can be challenging due to topic complexity and the large number of online sources with differing quality. The goal of this article is to examine, among all the available online sources, which online sources laypeople select to address their health-related information needs, and whether or how much the severity of a health condition influences their selection. Twenty-four participants were recruited individually, and each was asked (using a retrieval system called HIS) to search for information regarding a severe health condition and a mild health condition, respectively. The selected online health information sources were automatically captured by the HIS system and classified at both the website and webpage levels. Participants' selection behavior patterns were then plotted across the whole information-seeking process. Our results demonstrate that laypeople's source selection fluctuates during the health information-seeking process, and also varies by the severity of health conditions. This study reveals laypeople's real usage of different types of online health information sources, and engenders implications to the design of search engines, as well as the development of health literacy programs.

Date

12.11.2020 13:22:09

Source

Journal of the Association for Information Science and Technology. 71(2020) no.12, S.1484-1499

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Abstract

Web ad effect evaluation is a challenging problem in web marketing research. Although the analysis of web ad effectiveness has achieved excellent results, there are still some deficiencies. First, there is a lack of an in-depth study of the relevance between advertisements and web content. Second, there is not a thorough analysis of the impacts of users and advertising features on user browsing behaviors. And last, the evaluation index of the web advertisement effect is not adequate. Given the above problems, we conducted our work by studying the observer's behavioral pattern based on multimodal features. First, we analyze the correlation between ads and links with different searching results and further assess the influence of relevance on the observer's attention to web ads using eye-movement features. Then we investigate the user's behavioral sequence and propose the directional frequent-browsing pattern algorithm for mining the user's most commonly used browsing patterns. Finally, we offer the novel use of "memory" as a new measure of advertising effectiveness and further build an advertising memory model with integrated multimodal features for predicting the efficacy of web ads. A large number of experiments have proved the superiority of our method.

Source

Journal of the Association for Information Science and Technology. 71(2020) no.1, S.16-28

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Abstract

Credibility assessment is a crucial component in the process of people's health information seeking, especially in the web context. Finding "credible" health information from a plethora of information on the web may be more challenging for older adults, who have relatively less experience with the Internet. This article reports on the findings of an exploratory study of older adults' credibility assessments of online health information. The data collected through semistructured interviews with 21 older adult Internet users in the United States were analyzed based on the extended typology of web credibility (Choi & Stvilia, 2015, Journal of the Association for Information Science and Technology, 66, 2399-2414). The findings of the study revealed that older adults paid closer attention to operator-related credibility cues and heuristics when judging the credibility of health information on the web, followed by content- and design-related ones. Also, the findings suggest that participants who were younger and used the Internet more frequently employed a wider variety of cues and heuristics to evaluate the credibility of online health information. Based on these findings, both theoretical and practical implications of the research and future research directions are discussed.

Source

Journal of the Association for Information Science and Technology. 71(2020) no.11, S.1295-1307

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Abstract

Knowledge Architectures reviews traditional approaches to managing information and explains why they need to adapt to support 21st-century information management and discovery. Exploring the rapidly changing environment in which information is being managed and accessed, the book considers how to use knowledge architectures, the basic structures and designs that underlie all of the parts of an effective information system, to best advantage. Drawing on 40 years of work with a variety of organizations, Bedford explains that failure to understand the structure behind any given system can be the difference between an effective solution and a significant and costly failure. Demonstrating that the information user environment has shifted significantly in the past 20 years, the book explains that end users now expect designs and behaviors that are much closer to the way they think, work, and act. Acknowledging how important it is that those responsible for developing an information or knowledge management system understand knowledge structures, the book goes beyond a traditional library science perspective and uses case studies to help translate the abstract and theoretical to the practical and concrete. Explaining the structures in a simple and intuitive way and providing examples that clearly illustrate the challenges faced by a range of different organizations, Knowledge Architectures is essential reading for those studying and working in library and information science, data science, systems development, database design, and search system architecture and engineering.

Content

Section 1 Context and purpose of knowledge architecture -- 1 Making the case for knowledge architecture -- 2 The landscape of knowledge assets -- 3 Knowledge architecture and design -- 4 Knowledge architecture reference model -- 5 Knowledge architecture segments -- Section 2 Designing for availability -- 6 Knowledge object modeling -- 7 Knowledge structures for encoding, formatting, and packaging -- 8 Functional architecture for identification and distinction -- 9 Functional architectures for knowledge asset disposition and destruction -- 10 Functional architecture designs for knowledge preservation and conservation -- Section 3 Designing for accessibility -- 11 Functional architectures for knowledge seeking and discovery -- 12 Functional architecture for knowledge search -- 13 Functional architecture for knowledge categorization -- 14 Functional architectures for indexing and keywording -- 15 Functional architecture for knowledge semantics -- 16 Functional architecture for knowledge abstraction and surrogation -- Section 4 Functional architectures to support knowledge consumption -- 17 Functional architecture for knowledge augmentation, derivation, and synthesis -- 18 Functional architecture to manage risk and harm -- 19 Functional architectures for knowledge authentication and provenance -- 20 Functional architectures for securing knowledge assets -- 21 Functional architectures for authorization and asset management -- Section 5 Pulling it all together - the big picture knowledge architecture -- 22 Functional architecture for knowledge metadata and metainformation -- 23 The whole knowledge architecture - pulling it all together

LCSH

Information science
Information storage and retrieval systems / Management

Subject

Information science
Information storage and retrieval systems / Management

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Abstract

Evaluating the quality of online health information (OHI) is a major challenge facing consumers. We designed PageGraph, an interface that displays quality indicators and associated values for a webpage, based on credibility evaluation models, the nudge theory, and existing empirical research concerning professionals' and consumers' evaluation of OHI quality. A qualitative evaluation of the interface with 16 participants revealed that PageGraph rendered the information and presentation nudges as intended. It provided the participants with easier access to quality indicators, encouraged fresh angles to assess information credibility, provided an evaluation framework, and encouraged validation of initial judgments. We then conducted a quantitative evaluation of the interface involving 60 participants using a between-subject experimental design. The control group used a regular web browser and evaluated the credibility of 12 preselected webpages, whereas the experimental group evaluated the same webpages with the assistance of PageGraph. PageGraph did not significantly influence participants' evaluation results. The results may be attributed to the insufficiency of the saliency and structure of the nudges implemented and the webpage stimuli's lack of sensitivity to the intervention. Future directions for applying nudges to support OHI evaluation were discussed.

Date

22. 6.2023 18:18:34

Source

Journal of the Association for Information Science and Technology. 74(2023) no.7, S.828-845

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Abstract

Ensuring Wikipedia cites scholarly publications based on quality and relevancy without biases is critical to credible and fair knowledge dissemination. We investigate gender- and country-based biases in Wikipedia citation practices using linked data from the Web of Science and a Wikipedia citation dataset. Using coarsened exact matching, we show that publications by women are cited less by Wikipedia than expected, and publications by women are less likely to be cited than those by men. Scholarly publications by authors affiliated with non-Anglosphere countries are also disadvantaged in getting cited by Wikipedia, compared with those by authors affiliated with Anglosphere countries. The level of gender- or country-based inequalities varies by research field, and the gender-country intersectional bias is prominent in math-intensive STEM fields. To ensure the credibility and equality of knowledge presentation, Wikipedia should consider strategies and guidelines to cite scholarly publications independent of the gender and country of authors.

Date

22. 1.2023 18:53:32

Source

Journal of the Association for Information Science and Technology. 74(2023) no.2, S.219-233

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Abstract

Purpose Public attitudes towards COVID-19 and social distancing are critical in reducing its spread. It is therefore important to understand public reactions and information dissemination in all major forms, including on social media. This article investigates important issues reflected on Twitter in the early stages of the public reaction to COVID-19. Design/methodology/approach A thematic analysis of the most retweeted English-language tweets mentioning COVID-19 during March 10-29, 2020. Findings The main themes identified for the 87 qualifying tweets accounting for 14 million retweets were: lockdown life; attitude towards social restrictions; politics; safety messages; people with COVID-19; support for key workers; work; and COVID-19 facts/news. Research limitations/implications Twitter played many positive roles, mainly through unofficial tweets. Users shared social distancing information, helped build support for social distancing, criticised government responses, expressed support for key workers and helped each other cope with social isolation. A few popular tweets not supporting social distancing show that government messages sometimes failed. Practical implications Public health campaigns in future may consider encouraging grass roots social web activity to support campaign goals. At a methodological level, analysing retweet counts emphasised politics and ignored practical implementation issues. Originality/value This is the first qualitative analysis of general COVID-19-related retweeting.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 72(2020) no.6, S.945-962

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Abstract

Purpose To provide a close, detailed analysis of the frequency, nature, and depth of visible use of Michel Foucault's works by library and information science/studies (LIS) scholars. Design/methodology/approach The study conducted extensive full-text searches in a large number of electronically available LIS journal databases to find citations of Foucault's works, then examined each cited article to evaluate the nature and depth of use. Findings Most uses of Foucault are brief or in passing. In-depth explorations of Foucault's works are comparatively rare and relatively little-used by other LIS scholars. Yet the relatively brief uses of Foucault encompass a wide array of different topics spread across a wide spectrum of LIS journal literature. Research limitations/implications The study was limited to articles from particular relatively prominent LIS journals. Results might vary if different journals or non-journal literature were studied. More sophisticated bibliometric techniques might reveal different relative performance among journals and might better test, confirm, or reject various patterns and relationships found here. Other research approaches, such as discourse analysis, social network analysis, or scholar interviews, might reveal patterns of use and influence not visible in this literature sample. Originality/value This intensive study of both quality and quantity of citations may challenge some existing assumptions regarding citation analysis, plus illuminating Foucault scholarship. It also indicates possible problems for future application of artificial intelligence (AI) approaches to similar depth-of-use studies.

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Abstract

The initial dimensions extracted by latent semantic analysis (LSA) of a document-term matrixhave been shown to mainly display marginal effects, which are irrelevant for informationretrieval. To improve the performance of LSA, usually the elements of the raw document-term matrix are weighted and the weighting exponent of singular values can be adjusted.An alternative information retrieval technique that ignores the marginal effects is correspon-dence analysis (CA). In this paper, the information retrieval performance of LSA and CA isempirically compared. Moreover, it is explored whether the two weightings also improve theperformance of CA. The results for four empirical datasets show that CA always performsbetter than LSA. Weighting the elements of the raw data matrix can improve CA; however,it is data dependent and the improvement is small. Adjusting the singular value weightingexponent often improves the performance of CA; however, the extent of the improvementdepends on the dataset and the number of dimensions. (PDF) Improving information retrieval through correspondence analysis instead of latent semantic analysis.

Source

Journal of intelligent information systems [https://doi.org/10.1007/s10844-023-00815-y]