-
Noever, D.; Ciolino, M.: ¬The Turing deception (2022)
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- Abstract
- This research revisits the classic Turing test and compares recent large language models such as ChatGPT for their abilities to reproduce human-level comprehension and compelling text generation. Two task challenges- summary and question answering- prompt ChatGPT to produce original content (98-99%) from a single text entry and sequential questions initially posed by Turing in 1950. We score the original and generated content against the OpenAI GPT-2 Output Detector from 2019, and establish multiple cases where the generated content proves original and undetectable (98%). The question of a machine fooling a human judge recedes in this work relative to the question of "how would one prove it?" The original contribution of the work presents a metric and simple grammatical set for understanding the writing mechanics of chatbots in evaluating their readability and statistical clarity, engagement, delivery, overall quality, and plagiarism risks. While Turing's original prose scores at least 14% below the machine-generated output, whether an algorithm displays hints of Turing's true initial thoughts (the "Lovelace 2.0" test) remains unanswerable.
- Source
- https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
-
Gabler, S.: Vergabe von DDC-Sachgruppen mittels eines Schlagwort-Thesaurus (2021)
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- Content
- Master thesis Master of Science (Library and Information Studies) (MSc), Universität Wien. Advisor: Christoph Steiner. Vgl.: https://www.researchgate.net/publication/371680244_Vergabe_von_DDC-Sachgruppen_mittels_eines_Schlagwort-Thesaurus. DOI: 10.25365/thesis.70030. Vgl. dazu die Präsentation unter: https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=web&cd=&ved=0CAIQw7AJahcKEwjwoZzzytz_AhUAAAAAHQAAAAAQAg&url=https%3A%2F%2Fwiki.dnb.de%2Fdownload%2Fattachments%2F252121510%2FDA3%2520Workshop-Gabler.pdf%3Fversion%3D1%26modificationDate%3D1671093170000%26api%3Dv2&psig=AOvVaw0szwENK1or3HevgvIDOfjx&ust=1687719410889597&opi=89978449.
-
Das, S.; Paik, J.H.: Gender tagging of named entities using retrieval-assisted multi-context aggregation : an unsupervised approach (2023)
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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
-
Tramullas, J.; Garrido-Picazo, P.; Sánchez-Casabón, A.I.: Use of Wikipedia categories on information retrieval research : a brief review (2020)
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- Abstract
- Wikipedia categories, a classification scheme built for organizing and describing Wikpedia articles, are being applied in computer science research. This paper adopts a systematic literature review approach, in order to identify different approaches and uses of Wikipedia categories in information retrieval research. Several types of work are identified, depending on the intrinsic study of the categories structure, or its use as a tool for the processing and analysis of other documentary corpus different to Wikipedia. Information retrieval is identified as one of the major areas of use, in particular its application in the refinement and improvement of search expressions, and the construction of textual corpus. However, the set of available works shows that in many cases research approaches applied and results obtained can be integrated into a comprehensive and inclusive concept of information retrieval.
-
MacFarlane, A.; Missaoui, S.; Frankowska-Takhari, S.: On machine learning and knowledge organization in multimedia information retrieval (2020)
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- Abstract
- Recent technological developments have increased the use of machine learning to solve many problems, including many in information retrieval. Multimedia information retrieval as a problem represents a significant challenge to machine learning as a technological solution, but some problems can still be addressed by using appropriate AI techniques. We review the technological developments and provide a perspective on the use of machine learning in conjunction with knowledge organization to address multimedia IR needs. The semantic gap in multimedia IR remains a significant problem in the field, and solutions to them are many years off. However, new technological developments allow the use of knowledge organization and machine learning in multimedia search systems and services. Specifically, we argue that, the improvement of detection of some classes of lowlevel features in images music and video can be used in conjunction with knowledge organization to tag or label multimedia content for better retrieval performance. We provide an overview of the use of knowledge organization schemes in machine learning and make recommendations to information professionals on the use of this technology with knowledge organization techniques to solve multimedia IR problems. We introduce a five-step process model that extracts features from multimedia objects (Step 1) from both knowledge organization (Step 1a) and machine learning (Step 1b), merging them together (Step 2) to create an index of those multimedia objects (Step 3). We also overview further steps in creating an application to utilize the multimedia objects (Step 4) and maintaining and updating the database of features on those objects (Step 5).
-
Zaitseva, E.M.: Developing linguistic tools of thematic search in library information systems (2023)
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- Abstract
- Within the R&D program "Information support of research by scientists and specialists on the basis of RNPLS&T Open Archive - the system of scientific knowledge aggregation", the RNPLS&T analyzes the use of linguistic tools of thematic search in the modern library information systems and the prospects for their development. The author defines the key common characteristics of e-catalogs of the largest Russian libraries revealed at the first stage of the analysis. Based on the specified common characteristics and detailed comparison analysis, the author outlines and substantiates the vectors for enhancing search inter faces of e-catalogs. The focus is made on linguistic tools of thematic search in library information systems; the key vectors are suggested: use of thematic search at different search levels with the clear-cut level differentiation; use of combined functionality within thematic search system; implementation of classification search in all e-catalogs; hierarchical representation of classifications; use of the matching systems for classification information retrieval languages, and in the long term classification and verbal information retrieval languages, and various verbal information retrieval languages. The author formulates practical recommendations to improve thematic search in library information systems.
-
Gladun, A.; Rogushina, J.: Development of domain thesaurus as a set of ontology concepts with use of semantic similarity and elements of combinatorial optimization (2021)
0.06
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- Abstract
- We consider use of ontological background knowledge in intelligent information systems and analyze directions of their reduction in compliance with specifics of particular user task. Such reduction is aimed at simplification of knowledge processing without loss of significant information. We propose methods of generation of task thesauri based on domain ontology that contain such subset of ontological concepts and relations that can be used in task solving. Combinatorial optimization is used for minimization of task thesaurus. In this approach, semantic similarity estimates are used for determination of concept significance for user task. Some practical examples of optimized thesauri application for semantic retrieval and competence analysis demonstrate efficiency of proposed approach.
-
Lima, G.A. de; Castro, I.R.: Uso da classificacao decimal universal para a recuperacao da informacao em ambientes digitas : uma revisao sistematica da literatura (2021)
0.05
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- Abstract
- Knowledge Organization Systems, even traditional ones, such as the Universal Decimal Classification, have been studied to improve the retrieval of information online, although the potential of using knowledge structures in the user interface has not yet been widespread. Objective: This study presents a mapping of scientific production on information retrieval methodologies, which make use of the Universal Decimal Classification. Methodology: Systematic Literature Review, conducted in two stages, with a selection of 44 publications, resulting in the time interval from 1964 to 2017, whose categories analyzed were: most productive authors, languages of publications, types of document, year of publication, most cited work, major impact journal, and thematic categories covered in the publications. Results: A total of nine more productive authors and co-authors were found; predominance of the English language (42 publications); works published in the format of journal articles (33); and highlight to the year 2007 (eight publications). In addition, it was identified that the most cited work was by Mcilwaine (1997), with 61 citations, and the journal Extensions & Corrections to the UDC was the one with the largest number of publications, in addition to the incidence of the theme Universal Automation linked to a thesaurus for information retrieval, present in 19 works. Conclusions: Shortage of studies that explore the potential of the Decimal Classification, especially in Brazilian literature, which highlights the need for further study on the topic, involving research at the national and international levels.
- Footnote
- Englischer Titel: Use of the Universal Decimal Classification for the recoery of information in digital environments: a systematic review of literature.
- Theme
- Klassifikationssysteme im Online-Retrieval
-
Bergman, O.; Israeli, T.; Whittaker, S.: Factors hindering shared files retrieval (2020)
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- Abstract
- Purpose Personal information management (PIM) is an activity in which people store information items in order to retrieve them later. The purpose of this paper is to test and quantify the effect of factors related to collection size, file properties and workload on file retrieval success and efficiency. Design/methodology/approach In the study, 289 participants retrieved 1,557 of their shared files in a naturalistic setting. The study used specially developed software designed to collect shared files' names and present them as targets for the retrieval task. The dependent variables were retrieval success, retrieval time and misstep/s. Findings Various factors compromise shared files retrieval including: collection size (large number of files), file properties (multiple versions, size of team sharing the file, time since most recent retrieval and folder depth) and workload (daily e-mails sent and received). The authors discuss theoretical reasons for these negative effects and suggest possible ways to overcome them. Originality/value Retrieval is the main reason people manage personal information. It is essential for retrieval to be successful and efficient, as information cannot be used unless it can be re-accessed. Prior PIM research has assumed that factors related to collection size, file properties and workload affect file retrieval. However, this is the first study to systematically quantify the negative effects of these factors. As each of these factors is expected to be exacerbated in the future, this study is a necessary first step toward addressing these problems.
- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 72(2020) no.1, S.130-147
-
Huvila, I.: Making and taking information (2022)
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- Abstract
- Information behavior theory covers different aspects of the totality of information-related human behavior rather unevenly. The transitions or trading zones between different types of information activities have remained perhaps especially under-theorized. This article interrogates and expands a conceptual apparatus of information making and information taking as a pair of substantial concepts for explaining, in part, the mobility of information in terms of doing that unfolds as a process of becoming rather than of being, and in part, what is happening when information comes into being and when something is taken up for use as information. Besides providing an apparatus to describe the nexus of information provision and acquisition, a closer consideration of the parallel doings opens opportunities to enrich the inquiry of the conditions and practice of information seeking, appropriation, discovery, and retrieval as modes taking, and learning and information use as its posterities.
- Series
- JASIS&Tspecial issue on information behavior and information practices theory
- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.4, S.528-541
-
Wiggers, G.; Verberne, S.; Loon, W. van; Zwenne, G.-J.: Bibliometric-enhanced legal information retrieval : combining usage and citations as flavors of impact relevance (2023)
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- Abstract
- Bibliometric-enhanced information retrieval uses bibliometrics (e.g., citations) to improve ranking algorithms. Using a data-driven approach, this article describes the development of a bibliometric-enhanced ranking algorithm for legal information retrieval, and the evaluation thereof. We statistically analyze the correlation between usage of documents and citations over time, using data from a commercial legal search engine. We then propose a bibliometric boost function that combines usage of documents with citation counts. The core of this function is an impact variable based on usage and citations that increases in influence as citations and usage counts become more reliable over time. We evaluate our ranking function by comparing search sessions before and after the introduction of the new ranking in the search engine. Using a cost model applied to 129,571 sessions before and 143,864 sessions after the intervention, we show that our bibliometric-enhanced ranking algorithm reduces the time of a search session of legal professionals by 2 to 3% on average for use cases other than known-item retrieval or updating behavior. Given the high hourly tariff of legal professionals and the limited time they can spend on research, this is expected to lead to increased efficiency, especially for users with extremely long search sessions.
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.8, S.1010-1025
-
Zhou, Q.; Lee, C.S.; Sin, S.-C.J.; Lin, S.; Hu, H.; Ismail, M.F.F. Bin: Understanding the use of YouTube as a learning resource : a social cognitive perspective (2020)
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- Abstract
- Drawing from social cognitive theory, the purpose of this study is to examine how personal, environmental and behavioral factors can interplay to influence people's use of YouTube as a learning resource. Design/methodology/approach This study proposed a conceptual model, which was then tested with data collected from a survey with 150 participants who had the experience of using YouTube for learning. The bootstrap method was employed to test the direct and mediation hypotheses in the model. Findings The results revealed that personal factors, i.e. learning outcome expectations and attitude, had direct effects on using YouTube as a learning resource (person ? behavior). The environmental factor, i.e. the sociability of YouTube, influenced the attitude (environment ? person), while the behavioral factor, i.e. prior experience of learning on YouTube, affected learning outcome expectations (behavior ? person). Moreover, the two personal factors fully mediated the influences of sociability and prior experience on YouTube usage for learning. Practical implications The factors and their relationships identified in this study provide important implications for individual learners, platform designers, educators and other stakeholders who encourage the use of YouTube as a learning resource. Originality/value This study draws on a comprehensive theoretical perspective (i.e. social cognitive theory) to investigate the interplay of critical components (i.e. individual, environment and behavior) in YouTube's learning ecosystem. Personal factors not only directly influenced the extent to which people use YouTube as a learning resource but also mediated the effects of environmental and behavioral factors on the usage behavior.
- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 72(2020) no.3, S.339-359
-
Guo, T.; Bai, X.; Zhen, S.; Abid, S.; Xia, F.: Lost at starting line : predicting maladaptation of university freshmen based on educational big data (2023)
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- Abstract
- The transition from secondary education to higher education could be challenging for most freshmen. For students who fail to adjust to university life smoothly, their status may worsen if the university cannot offer timely and proper guidance. Helping students adapt to university life is a long-term goal for any academic institution. Therefore, understanding the nature of the maladaptation phenomenon and the early prediction of "at-risk" students are crucial tasks that urgently need to be tackled effectively. This article aims to analyze the relevant factors that affect the maladaptation phenomenon and predict this phenomenon in advance. We develop a prediction framework (MAladaptive STudEnt pRediction, MASTER) for the early prediction of students with maladaptation. First, our framework uses the SMOTE (Synthetic Minority Oversampling Technique) algorithm to solve the data label imbalance issue. Moreover, a novel ensemble algorithm, priority forest, is proposed for outputting ranks instead of binary results, which enables us to perform proactive interventions in a prioritized manner where limited education resources are available. Experimental results on real-world education datasets demonstrate that the MASTER framework outperforms other state-of-art methods.
- Date
- 27.12.2022 18:34:22
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.1, S.17-32
-
Bedford, D.: Knowledge architectures : structures and semantics (2021)
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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 storage and retrieval systems / Management
- Subject
- Information storage and retrieval systems / Management
-
Golub, K.; Ziolkowski, P.M.; Zlodi, G.: Organizing subject access to cultural heritage in Swedish online museums (2022)
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- Abstract
- Purpose The study aims to paint a representative picture of the current state of search interfaces of Swedish online museum collections, focussing on search functionalities with particular reference to subject searching, as well as the use of controlled vocabularies, with the purpose of identifying which improvements of the search interfaces are needed to ensure high-quality information retrieval for the end user. Design/methodology/approach In the first step, a set of 21 search interface criteria was identified, based on related research and current standards in the domain of cultural heritage knowledge organization. Secondly, a complete set of Swedish museums that provide online access to their collections was identified, comprising nine cross-search services and 91 individual museums' websites. These 100 websites were each evaluated against the 21 criteria, between 1 July and 31 August 2020. Findings Although many standards and guidelines are in place to ensure quality-controlled subject indexing, which in turn support information retrieval of relevant resources (as individual or full search results), the study shows that they are not broadly implemented, resulting in information retrieval failures for the end user. The study also demonstrates a strong need for the implementation of controlled vocabularies in these museums. Originality/value This study is a rare piece of research which examines subject searching in online museums; the 21 search criteria and their use in the analysis of the complete set of online collections of a country represents a considerable and unique contribution to the fields of knowledge organization and information retrieval of cultural heritage. Its particular value lies in showing how the needs of end users, many of which are documented and reflected in international standards and guidelines, should be taken into account in designing search tools for these museums; especially so in subject searching, which is the most complex and yet the most common type of search. Much effort has been invested into digitizing cultural heritage collections, but access to them is hindered by poor search functionality. This study identifies which are the most important aspects to improve.
- Source
- Journal of documentation. 78(2022) no.7, S.211-247
-
Campos, L.M.: Princípios teóricos usados na elaboracao de ontologias e sua influência na recuperacao da informacao com uso de de inferências [Theoretical principles used in ontology building and their influence on information retrieval using inferences] (2021)
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- Abstract
- Several instruments of knowledge organization will reflect different possibilities for information retrieval. In this context, ontologies have a different potential because they allow knowledge discovery, which can be used to retrieve information in a more flexible way. However, this potential can be affected by the theoretical principles adopted in ontology building. The aim of this paper is to discuss, in an introductory way, how a (not exhaustive) set of theoretical principles can influence an aspect of ontologies: their use to obtain inferences. In this context, the role of Ingetraut Dahlberg's Theory of Concept is discussed. The methodology is exploratory, qualitative, and from the technical point of view it uses bibliographic research supported by the content analysis method. It also presents a small example of application as a proof of concept. As results, a discussion about the influence of conceptual definition on subsumption inferences is presented, theoretical contributions are suggested that should be used to guide the formation of hierarchical structures on which such inferences are supported, and examples are provided of how the absence of such contributions can lead to erroneous inferences
-
Ilhan, A.; Fietkiewicz, K.J.: Data privacy-related behavior and concerns of activity tracking technology users from Germany and the USA (2021)
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- Abstract
- Purpose This investigation aims to examine the differences and similarities between activity tracking technology users from two regions (the USA and Germany) in their intended privacy-related behavior. The focus lies on data handling after hypothetical discontinuance of use, data protection and privacy policy seeking, and privacy concerns. Design/methodology/approach The data was collected through an online survey in 2019. In order to identify significant differences between participants from Germany and the USA, the chi-squared test and the Mann-Whitney U test were applied. Findings The intensity of several privacy-related concerns was significantly different between the two groups. The majority of the participants did not inform themselves about the respective data privacy policies or terms and conditions before installing an activity tracking application. The majority of the German participants knew that they could request the deletion of all their collected data. In contrast, only 35% out of 68 participants from the US knew about this option. Research limitations/implications This study intends to raise awareness about managing the collected health and fitness data after stopping to use activity tracking technologies. Furthermore, to reduce privacy and security concerns, the involvement of the government, companies and users is necessary to handle and share data more considerably and in a sustainable way. Originality/value This study sheds light on users of activity tracking technologies from a broad perspective (here, participants from the USA and Germany). It incorporates not only concerns and the privacy paradox but (intended) user behavior, including seeking information on data protection and privacy policy and handling data after hypothetical discontinuance of use of the technology.
- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 73(2021) no.2, S.180-200
-
Nakash, M.; Bouhnik, D.: ¬The effects of COVID-19 on information management in remote and hybrid work environments (2023)
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- Abstract
- This empirical research examines the effects of the COVID-19 pandemic on information management (IM) in remote or hybrid work. We present an in-depth statistical analysis of 716 responses to questionnaires received from employees and managers of four Israeli government ministries. The participants were asked to report characteristics such as accessibility, retrieval speed, ease of locating, and relevance of information, in order to assess the quality of organizational IM before and during COVID-19. The findings reveal that IM quality was maintained even when organizations were forced to quickly adapt to working remotely during the pandemic. Regardless of work location, differences in perception of IM were found among organizations of different sizes: large, medium, and small. The majority of respondents who reported not using IM systems (IMS) before COVID-19 also stated that even after the pandemic's onset, they still did not use them. A lower frequency of IMS use has been associated with a decline in IM quality. Given the far-reaching changes in IM induced by the pandemic, many of which have the potential to be long-lasting, these findings serve as an opening for valuable future research.
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.9, S.1067-1080
-
Nori, R.: Web searching and navigation : age, intelligence, and familiarity (2020)
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- Abstract
- In using the Internet to solve everyday problems, older adults tend to find fewer correct answers compared to younger adults. Some authors have argued that these differences could be explained by age-related decline. The present study aimed to analyze the relationship between web-searching navigation and users' age, considering the Intelligence Quotient (IQ) and frequency of Internet and personal computer use. The intent was to identify differences due to age and not to other variables (that is, cognitive decline, expertise with the tool). Eighteen students (18-30?years) and 18 older adults (60-75?years) took part in the experiment. Inclusion criteria were the frequent use of computers and a web-searching activity; the older adults performed the Mini-Mental State Examination to exclude cognitive impairment. Participants were requested to perform the Kaufman Brief Intelligence Test 2nd ed. to measure their IQ level, and nine everyday web-searching tasks of differing complexity. The results showed that older participants spent more time on solving tasks than younger participants, but with the same accuracy as young people. Furthermore, nonverbal IQ improved performance in terms of time among the older participants. Age did not influence web-searching behavior in users with normal expertise and intelligence.
- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.8, S.902-915
-
Luhmann, J.; Burghardt, M.: Digital humanities - A discipline in its own right? : an analysis of the role and position of digital humanities in the academic landscape (2022)
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- Abstract
- Although digital humanities (DH) has received a lot of attention in recent years, its status as "a discipline in its own right" (Schreibman et al., A companion to digital humanities (pp. xxiii-xxvii). Blackwell; 2004) and its position in the overall academic landscape are still being negotiated. While there are countless essays and opinion pieces that debate the status of DH, little research has been dedicated to exploring the field in a systematic and empirical way (Poole, Journal of Documentation; 2017:73). This study aims to contribute to the existing research gap by comparing articles published over the past three decades in three established English-language DH journals (Computers and the Humanities, Literary and Linguistic Computing, Digital Humanities Quarterly) with research articles from journals in 15 other academic disciplines (corpus size: 34,041 articles; 299 million tokens). As a method of analysis, we use latent Dirichlet allocation topic modeling, combined with recent approaches that aggregate topic models by means of hierarchical agglomerative clustering. Our findings indicate that DH is simultaneously a discipline in its own right and a highly interdisciplinary field, with many connecting factors to neighboring disciplines-first and foremost, computational linguistics, and information science. Detailed descriptive analyses shed some light on the diachronic development of DH and also highlight topics that are characteristic for DH.
- Series
- JASIST special issue on digital humanities (DH): A. Landscapes of DH
- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.2, S.148-171
