-
Noever, D.; Ciolino, M.: ¬The Turing deception (2022)
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- Source
- https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
-
Cerda-Cosme, R.; Méndez, E.: Analysis of shared research data in Spanish scientific papers about COVID-19 : a first approach (2023)
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- Abstract
- During the coronavirus pandemic, changes in the way science is done and shared occurred, which motivates meta-research to help understand science communication in crises and improve its effectiveness. The objective is to study how many Spanish scientific papers on COVID-19 published during 2020 share their research data. Qualitative and descriptive study applying nine attributes: (a) availability, (b) accessibility, (c) format, (d) licensing, (e) linkage, (f) funding, (g) editorial policy, (h) content, and (i) statistics. We analyzed 1,340 papers, 1,173 (87.5%) did not have research data. A total of 12.5% share their research data of which 2.1% share their data in repositories, 5% share their data through a simple request, 0.2% do not have permission to share their data, and 5.2% share their data as supplementary material. There is a small percentage that shares their research data; however, it demonstrates the researchers' poor knowledge on how to properly share their research data and their lack of knowledge on what is research data.
- Date
- 21. 3.2023 19:22:02
-
Geras, A.; Siudem, G.; Gagolewski, M.: Should we introduce a dislike button for academic articles? (2020)
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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
-
Park, M.S.; Park, J.H.; Kim, H.; Lee, J.H.; Park, H.: Measuring the impacts of quantity and trustworthiness of information on COVID-19 vaccination intent (2023)
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- Date
- 22. 6.2023 18:20:47
-
Ma, L.: Information, platformized (2023)
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- Abstract
- Scholarly publications are often regarded as "information" by default. They are collected, organized, preserved, and made accessible as knowledge records. However, the instances of article retraction, misconduct and malpractices of researchers and the replication crisis have raised concerns about the informativeness and evidential qualities of information. Among many factors, knowledge production has moved away from "normal science" under the systemic influences of platformization involving the datafication and commodification of scholarly articles, research profiles and research activities. This article aims to understand the platformization of information by examining how research practices and knowledge production are steered by market and platform mechanisms in four ways: (a) ownership of information; (b) metrics for sale; (c) relevance by metrics, and (d) market-based competition. In conclusion, the article argues that information is platformized when platforms hold the dominating power in determining what kinds of information can be disseminated and rewarded and when informativeness is decoupled from the normative agreement or consensus co-constructed and co-determined in an open and public discourse.
- Date
- 22. 1.2023 19:01:47
-
Zhang, X.; Wang, D.; Tang, Y.; Xiao, Q.: How question type influences knowledge withholding in social Q&A community (2023)
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- Date
- 22. 9.2023 13:51:47
-
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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- Date
- 20. 1.2015 18:30:22
-
Hottenrott, H.; Rose, M.E.; Lawson, C.: ¬The rise of multiple institutional affiliations in academia (2021)
0.02
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- Abstract
- This study provides the first systematic, international, large-scale evidence on the extent and nature of multiple institutional affiliations on journal publications. Studying more than 15 million authors and 22 million articles from 40 countries we document that: In 2019, almost one in three articles was (co-)authored by authors with multiple affiliations and the share of authors with multiple affiliations increased from around 10% to 16% since 1996. The growth of multiple affiliations is prevalent in all fields and it is stronger in high impact journals. About 60% of multiple affiliations are between institutions from within the academic sector. International co-affiliations, which account for about a quarter of multiple affiliations, most often involve institutions from the United States, China, Germany and the United Kingdom, suggesting a core-periphery network. Network analysis also reveals a number communities of countries that are more likely to share affiliations. We discuss potential causes and show that the timing of the rise in multiple affiliations can be linked to the introduction of more competitive funding structures such as "excellence initiatives" in a number of countries. We discuss implications for science and science policy.
-
Oh, H.; Nam, S.; Zhu, Y.: Structured abstract summarization of scientific articles : summarization using full-text section information (2023)
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- Date
- 22. 1.2023 18:57:12
-
Yu, C.; Xue, H.; An, L.; Li, G.: ¬A lightweight semantic-enhanced interactive network for efficient short-text matching (2023)
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- Date
- 22. 1.2023 19:05:27
-
Moulaison-Sandy, H.; Adkins, D.; Bossaller, J.; Cho, H.: ¬An automated approach to describing fiction : a methodology to use book reviews to identify affect (2021)
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-
Qin, H.; Wang, H.; Johnson, A.: Understanding the information needs and information-seeking behaviours of new-generation engineering designers for effective knowledge management (2020)
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- Date
- 20. 1.2015 18:30:22
-
Chi, Y.; He, D.; Jeng, W.: Laypeople's source selection in online health information-seeking process (2020)
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- Date
- 12.11.2020 13:22:09
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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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Lee, D.J.; Stvilia, B.; Ha, S.; Hahn, D.: ¬The structure and priorities of researchers' scholarly profile maintenance activities : a case of institutional research information management system (2023)
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Rae, A.R.; Mork, J.G.; Demner-Fushman, D.: ¬The National Library of Medicine indexer assignment dataset : a new large-scale dataset for reviewer assignment research (2023)
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Belabbes, M.A.; Ruthven, I.; Moshfeghi, Y.; Rasmussen Pennington, D.: Information overload : a concept analysis (2023)
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Shahbazi, M.; Bunker, D.; Sorrell, T.C.: Communicating shared situational awareness in times of chaos : social media and the COVID-19 pandemic (2023)
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Li, Z.; He, L.; Gao, D.: Ontology construction and evaluation for Chinese traditional culture : towards digital humanity (2022)
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- Knowledge organization. 49(2022) no.1, S.22 - 39
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Gabler, S.: Thesauri - a Toolbox for Information Retrieval (2023)
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- Bibliothek: Forschung und Praxis. 47(2023) H.2, S.189-199
