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  • × year_i:[2020 TO 2030}
  1. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.07
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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
    Type
    a
  2. Ibrahim, G.M.; Taylor, M.: Krebszellen manipulieren Neurone : Gliome (2023) 0.06
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    Source
    Spektrum der Wissenschaft. 2023, H.10, S.22-24
    Type
    a
  3. Geras, A.; Siudem, G.; Gagolewski, M.: Should we introduce a dislike button for academic articles? (2020) 0.03
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    Abstract
    There is a mutual resemblance between the behavior of users of the Stack Exchange and the dynamics of the citations accumulation process in the scientific community, which enabled us to tackle the outwardly intractable problem of assessing the impact of introducing "negative" citations. Although the most frequent reason to cite an article is to highlight the connection between the 2 publications, researchers sometimes mention an earlier work to cast a negative light. While computing citation-based scores, for instance, the h-index, information about the reason why an article was mentioned is neglected. Therefore, it can be questioned whether these indices describe scientific achievements accurately. In this article we shed insight into the problem of "negative" citations, analyzing data from Stack Exchange and, to draw more universal conclusions, we derive an approximation of citations scores. Here we show that the quantified influence of introducing negative citations is of lesser importance and that they could be used as an indicator of where the attention of the scientific community is allocated.
    Date
    6. 1.2020 18:10:22
    Type
    a
  4. ¬Der Student aus dem Computer (2023) 0.03
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    Date
    27. 1.2023 16:22:55
    Type
    a
  5. Hertzum, M.: Information seeking by experimentation : trying something out to discover what happens (2023) 0.03
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    Abstract
    Experimentation is the process of trying something out to discover what happens. It is a widespread information practice, yet often bypassed in information-behavior research. This article argues that experimentation complements prior knowledge, documents, and people as an important fourth class of information sources. Relative to the other classes, the distinguishing characteristics of experimentation are that it is a personal-as opposed to interpersonal-source and that it provides "backtalk." When the information seeker tries something out and then attends to the resulting situation, it is as though the materials of the situation talk back: They provide the information seeker with a situated and direct experience of the consequences of the tried-out options. In this way, experimentation involves obtaining information by creating it. It also involves turning material and behavioral processes into information interactions. Thereby, information seeking by experimentation is important to practical information literacy and extends information-behavior research with new insights on the interrelations between creating and seeking information.
    Date
    21. 3.2023 19:22:29
    Type
    a
  6. Thelwall, M.; Kousha, K.; Abdoli, M.; Stuart, E.; Makita, M.; Wilson, P.; Levitt, J.: Why are coauthored academic articles more cited : higher quality or larger audience? (2023) 0.03
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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
    Type
    a
  7. Hoeber, O.; Harvey, M.; Dewan Sagar, S.A.; Pointon, M.: ¬The effects of simulated interruptions on mobile search tasks (2022) 0.03
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    Abstract
    While it is clear that using a mobile device can interrupt real-world activities such as walking or driving, the effects of interruptions on mobile device use have been under-studied. We are particularly interested in how the ambient distraction of walking while using a mobile device, combined with the occurrence of simulated interruptions of different levels of cognitive complexity, affect web search activities. We have established an experimental design to study how the degree of cognitive complexity of simulated interruptions influences both objective and subjective search task performance. In a controlled laboratory study (n = 27), quantitative and qualitative data were collected on mobile search performance, perceptions of the interruptions, and how participants reacted to the interruptions, using a custom mobile eye-tracking app, a questionnaire, and observations. As expected, more cognitively complex interruptions resulted in increased overall task completion times and higher perceived impacts. Interestingly, the effect on the resumption lag or the actual search performance was not significant, showing the resiliency of people to resume their tasks after an interruption. Implications from this study enhance our understanding of how interruptions objectively and subjectively affect search task performance, motivating the need for providing explicit mobile search support to enable recovery from interruptions.
    Date
    3. 5.2022 13:22:33
    Type
    a
  8. Scheven, E.: Qualitätssicherung in der GND (2021) 0.03
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    Date
    23. 9.2021 19:12:22
    Source
    Qualität in der Inhaltserschließung. Hrsg.: M. Franke-Maier, u.a
    Type
    a
  9. Zhang, L.; Lu, W.; Yang, J.: LAGOS-AND : a large gold standard dataset for scholarly author name disambiguation (2023) 0.03
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    Abstract
    In this article, we present a method to automatically build large labeled datasets for the author ambiguity problem in the academic world by leveraging the authoritative academic resources, ORCID and DOI. Using the method, we built LAGOS-AND, two large, gold-standard sub-datasets for author name disambiguation (AND), of which LAGOS-AND-BLOCK is created for clustering-based AND research and LAGOS-AND-PAIRWISE is created for classification-based AND research. Our LAGOS-AND datasets are substantially different from the existing ones. The initial versions of the datasets (v1.0, released in February 2021) include 7.5 M citations authored by 798 K unique authors (LAGOS-AND-BLOCK) and close to 1 M instances (LAGOS-AND-PAIRWISE). And both datasets show close similarities to the whole Microsoft Academic Graph (MAG) across validations of six facets. In building the datasets, we reveal the variation degrees of last names in three literature databases, PubMed, MAG, and Semantic Scholar, by comparing author names hosted to the authors' official last names shown on the ORCID pages. Furthermore, we evaluate several baseline disambiguation methods as well as the MAG's author IDs system on our datasets, and the evaluation helps identify several interesting findings. We hope the datasets and findings will bring new insights for future studies. The code and datasets are publicly available.
    Date
    22. 1.2023 18:40:36
    Type
    a
  10. Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023) 0.03
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    Abstract
    Predicting a researcher's knowledge trajectories beyond their current foci can leverage potential inter-/cross-/multi-disciplinary interactions to achieve exploratory innovation. In this study, we present a method of diffusion-based network analytics for knowledge trajectory recommendation. The method begins by constructing a heterogeneous bibliometric network consisting of a co-topic layer and a co-authorship layer. A novel link prediction approach with a diffusion strategy is then used to capture the interactions between social elements (e.g., collaboration) and knowledge elements (e.g., technological similarity) in the process of exploratory innovation. This diffusion strategy differentiates the interactions occurring among homogeneous and heterogeneous nodes in the heterogeneous bibliometric network and weights the strengths of these interactions. Two sets of experiments-one with a local dataset and the other with a global dataset-demonstrate that the proposed method is prior to 10 selected baselines in link prediction, recommender systems, and upstream graph representation learning. A case study recommending knowledge trajectories of information scientists with topical hierarchy and explainable mediators reveals the proposed method's reliability and potential practical uses in broad scenarios.
    Date
    22. 6.2023 18:07:12
    Type
    a
  11. Jaeger, L.: Wissenschaftler versus Wissenschaft (2020) 0.03
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    Date
    2. 3.2020 14:08:22
    Type
    a
  12. Shahbazi, M.; Bunker, D.; Sorrell, T.C.: Communicating shared situational awareness in times of chaos : social media and the COVID-19 pandemic (2023) 0.03
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    Abstract
    To effectively manage a crisis, most decisions made by governments, organizations, communities, and individuals are based on "shared situational awareness" (SSA) derived from multiple information sources. Developing SSA depends on the alignment of mental models, which "represent our shared version of truth and reality on which we can act." Social media has facilitated public sensemaking during a crisis; however, it has also encouraged mental model dissonance, resulting in the digital destruction of mental models and undermining adequate SSA. The study is concerned with the challenges of creating SSA during the COVID-19 pandemic in Australia. This paper documents a netnography of Australian public health agencies' Facebook communication, exploring the initial impact of COVID-19 on SSA creation. Chaos theory is used as a theoretical lens to examine information perception, meaning, and assumptions relating to SSA from pre to post-pandemic periods. Our study highlights how the initial COVID-19 "butterfly effect" swamped the public health communication channel, leaving little space for other important health issues. This research contributes to information systems, information science, and communications by illustrating how the emergence of a crisis impacts social media communication, the creation of SSA, and what this means for social media adoption for crisis communication purposes.
    Date
    22. 9.2023 16:02:26
    Type
    a
  13. Kang, M.: Dual paths to continuous online knowledge sharing : a repetitive behavior perspective (2020) 0.03
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    Abstract
    Purpose Continuous knowledge sharing by active users, who are highly active in answering questions, is crucial to the sustenance of social question-and-answer (Q&A) sites. The purpose of this paper is to examine such knowledge sharing considering reason-based elaborate decision and habit-based automated cognitive processes. Design/methodology/approach To verify the research hypotheses, survey data on subjective intentions and web-crawled data on objective behavior are utilized. The sample size is 337 with the response rate of 27.2 percent. Negative binomial and hierarchical linear regressions are used given the skewed distribution of the dependent variable (i.e. the number of answers). Findings Both elaborate decision (linking satisfaction, intentions and continuance behavior) and automated cognitive processes (linking past and continuance behavior) are significant and substitutable. Research limitations/implications By measuring both subjective intentions and objective behavior, it verifies a detailed mechanism linking continuance intentions, past behavior and continuous knowledge sharing. The significant influence of automated cognitive processes implies that online knowledge sharing is habitual for active users. Practical implications Understanding that online knowledge sharing is habitual is imperative to maintaining continuous knowledge sharing by active users. Knowledge sharing trends should be monitored to check if the frequency of sharing decreases. Social Q&A sites should intervene to restore knowledge sharing behavior through personalized incentives. Originality/value This is the first study utilizing both subjective intentions and objective behavior data in the context of online knowledge sharing. It also introduces habit-based automated cognitive processes to this context. This approach extends the current understanding of continuous online knowledge sharing behavior.
    Date
    20. 1.2015 18:30:22
    Type
    a
  14. Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020) 0.03
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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
    Type
    a
  15. Barité, M.; Parentelli, V.; Rodríguez Casaballe, N.; Suárez, M.V.: Interdisciplinarity and postgraduate teaching of knowledge organization (KO) : elements for a necessary dialogue (2023) 0.03
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    Abstract
    Interdisciplinarity implies the previous existence of disciplinary fields and not their dissolution. As a general objective, we propose to establish an initial approach to the emphasis given to interdisciplinarity in the teaching of KO, through the teaching staff responsible for postgraduate courses focused on -or related to the KO, in Ibero-American universities. For conducting the research, the framework and distribution of a survey addressed to teachers is proposed, based on four lines of action: 1. The way teachers manage the concept of interdisciplinarity. 2. The place that teachers give to interdisciplinarity in KO. 3. Assessment of interdisciplinary content that teachers incorporate into their postgraduate courses. 4. Set of teaching strategies and resources used by teachers to include interdisciplinarity in the teaching of KO. The study analyzed 22 responses. Preliminary results show that KO teachers recognize the influence of other disciplines in concepts, theories, methods, and applications, but no consensus has been reached regarding which disciplines and authors are the ones who build interdisciplinary bridges. Among other conclusions, the study strongly suggests that environmental and social tensions are reflected in subject representation, especially in the construction of friendly knowl­edge organization systems with interdisciplinary visions, and in the expressions through which information is sought.
    Type
    a
  16. Das, S.; Bagchi, M.; Hussey, P.: How to teach domain ontology-based knowledge graph construction? : an Irish experiment (2023) 0.03
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    Abstract
    Domains represent concepts which belong to specific parts of the world. The particularized meaning of words linguistically encoding such domain concepts are provided by domain specific resources. The explicit meaning of such words are increasingly captured computationally using domain-specific ontologies, which, even for the same reference domain, are most often than not semantically incompatible. As information systems that rely on domain ontologies expand, there is a growing need to not only design domain ontologies and domain ontology-grounded Knowl­edge Graphs (KGs) but also to align them to general standards and conventions for interoperability. This often presents an insurmountable challenge to domain experts who have to additionally learn the construction of domain ontologies and KGs. Until now, several research methodologies have been proposed by different research groups using different technical approaches and based on scenarios of different domains of application. However, no methodology has been proposed which not only facilitates designing conceptually well-founded ontologies, but is also, equally, grounded in the general pedagogical principles of knowl­edge organization and, thereby, flexible enough to teach, and reproduce vis-à-vis domain experts. The purpose of this paper is to provide such a general, pedagogically flexible semantic knowl­edge modelling methodology. We exemplify the methodology by examples and illustrations from a professional-level digital healthcare course, and conclude with an evaluation grounded in technological parameters as well as user experience design principles.
    Date
    20.11.2023 17:19:22
    Type
    a
  17. Wiesenmüller, H.: Verbale Erschließung in Katalogen und Discovery-Systemen : Überlegungen zur Qualität (2021) 0.03
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    Date
    24. 9.2021 12:22:02
    Source
    Qualität in der Inhaltserschließung. Hrsg.: M. Franke-Maier, u.a
    Type
    a
  18. Sokolow, A.: Es menschelt in der KI-Welt (2023) 0.02
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    Date
    27. 1.2023 16:22:55
    Type
    a
  19. Sokolow, A.: Chaostage bei ChatGPT (2023) 0.02
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    Date
    27. 1.2023 16:22:55
    Type
    a
  20. Koch, C.: Was ist Bewusstsein? (2020) 0.02
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    Date
    17. 1.2020 22:15:11
    Type
    a

Languages

  • e 821
  • d 419
  • pt 6
  • m 2
  • sp 1
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Types

  • a 1148
  • el 254
  • m 64
  • p 13
  • s 10
  • x 2
  • A 1
  • EL 1
  • r 1
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