Search (61 results, page 1 of 4)

  • × theme_ss:"Informetrie"
  • × year_i:[2020 TO 2030}
  1. 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) 0.02 
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    Date
    22. 6.2023 18:11:50
    Language
    e
  2. Vakkari, P.; Järvelin, K.; Chang, Y.-W.: ¬The association of disciplinary background with the evolution of topics and methods in Library and Information Science research 1995-2015 (2023) 0.02 
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    Date
    22. 6.2023 18:15:06
    Language
    e
  3. Yan, E.; Chen, Z.; Li, K.: Authors' status and the perceived quality of their work : measuring citation sentiment change in nobel articles (2020) 0.01 
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  4. Wu, C.; Yan, E.; Zhu, Y.; Li, K.: Gender imbalance in the productivity of funded projects : a study of the outputs of National Institutes of Health R01 grants (2021) 0.01 
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  5. Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020) 0.01 
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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
    Language
    e
  6. Thelwall, M.; Kousha, K.; Abdoli, M.; Stuart, E.; Makita, M.; Wilson, P.; Levitt, J.: Do altmetric scores reflect article quality? : evidence from the UK Research Excellence Framework 2021 (2023) 0.01 
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  7. Thelwall, M.; Kousha, K.; Stuart, E.; Makita, M.; Abdoli, M.; Wilson, P.; Levitt, J.: In which fields are citations indicators of research quality? (2023) 0.01 
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  8. Delgado-Quirós, L.; Aguillo, I.F.; Martín-Martín, A.; López-Cózar, E.D.; Orduña-Malea, E.; Ortega, J.L.: Why are these publications missing? : uncovering the reasons behind the exclusion of documents in free-access scholarly databases (2024) 0.01 
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    Abstract
    This study analyses the coverage of seven free-access bibliographic databases (Crossref, Dimensions-non-subscription version, Google Scholar, Lens, Microsoft Academic, Scilit, and Semantic Scholar) to identify the potential reasons that might cause the exclusion of scholarly documents and how they could influence coverage. To do this, 116 k randomly selected bibliographic records from Crossref were used as a baseline. API endpoints and web scraping were used to query each database. The results show that coverage differences are mainly caused by the way each service builds their databases. While classic bibliographic databases ingest almost the exact same content from Crossref (Lens and Scilit miss 0.1% and 0.2% of the records, respectively), academic search engines present lower coverage (Google Scholar does not find: 9.8%, Semantic Scholar: 10%, and Microsoft Academic: 12%). Coverage differences are mainly attributed to external factors, such as web accessibility and robot exclusion policies (39.2%-46%), and internal requirements that exclude secondary content (6.5%-11.6%). In the case of Dimensions, the only classic bibliographic database with the lowest coverage (7.6%), internal selection criteria such as the indexation of full books instead of book chapters (65%) and the exclusion of secondary content (15%) are the main motives of missing publications.
    Language
    e
  9. Ikae, C.; Savoy, J.: Gender identification on Twitter (2022) 0.01 
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    Abstract
    To determine the author of a text's gender, various feature types have been suggested (e.g., function words, n-gram of letters, etc.) leading to a huge number of stylistic markers. To determine the target category, different machine learning models have been suggested (e.g., logistic regression, decision tree, k nearest-neighbors, support vector machine, naïve Bayes, neural networks, and random forest). In this study, our first objective is to know whether or not the same model always proposes the best effectiveness when considering similar corpora under the same conditions. Thus, based on 7 CLEF-PAN collections, this study analyzes the effectiveness of 10 different classifiers. Our second aim is to propose a 2-stage feature selection to reduce the feature size to a few hundred terms without any significant change in the performance level compared to approaches using all the attributes (increase of around 5% after applying the proposed feature selection). Based on our experiments, neural network or random forest tend, on average, to produce the highest effectiveness. Moreover, empirical evidence indicates that reducing the feature set size to around 300 without penalizing the effectiveness is possible. Finally, based on such reduced feature sizes, an analysis reveals some of the specific terms that clearly discriminate between the 2 genders.
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  10. Järvelin, K.; Vakkari, P.: LIS research across 50 years: content analysis of journal articles : offering an information-centric conception of memes (2022) 0.01 
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  11. Zhou, H.; Dong, K.; Xia, Y.: Knowledge inheritance in disciplines : quantifying the successive and distant reuse of references (2023) 0.01 
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  12. Herb, U.; Geith, U.: Kriterien der qualitativen Bewertung wissenschaftlicher Publikationen : Befunde aus dem Projekt visOA (2020) 0.01 
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  13. Manley, S.: Letters to the editor and the race for publication metrics (2022) 0.01 
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    Date
    6. 4.2022 19:22:26
    Language
    e
  14. Cerda-Cosme, R.; Méndez, E.: Analysis of shared research data in Spanish scientific papers about COVID-19 : a first approach (2023) 0.00 
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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
    Language
    e
  15. Lorentzen, D.G.: Bridging polarised Twitter discussions : the interactions of the users in the middle (2021) 0.00 
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    Date
    20. 1.2015 18:30:22
    Language
    e
  16. Milard, B.; Pitarch, Y.: Egocentric cocitation networks and scientific papers destinies (2023) 0.00 
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    Date
    21. 3.2023 19:22:14
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    e
  17. Liu, M.; Bu, Y.; Chen, C.; Xu, J.; Li, D.; Leng, Y.; Freeman, R.B.; Meyer, E.T.; Yoon, W.; Sung, M.; Jeong, M.; Lee, J.; Kang, J.; Min, C.; Zhai, Y.; Song, M.; Ding, Y.: Pandemics are catalysts of scientific novelty : evidence from COVID-19 (2022) 0.00 
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    Abstract
    Scientific novelty drives the efforts to invent new vaccines and solutions during the pandemic. First-time collaboration and international collaboration are two pivotal channels to expand teams' search activities for a broader scope of resources required to address the global challenge, which might facilitate the generation of novel ideas. Our analysis of 98,981 coronavirus papers suggests that scientific novelty measured by the BioBERT model that is pretrained on 29 million PubMed articles, and first-time collaboration increased after the outbreak of COVID-19, and international collaboration witnessed a sudden decrease. During COVID-19, papers with more first-time collaboration were found to be more novel and international collaboration did not hamper novelty as it had done in the normal periods. The findings suggest the necessity of reaching out for distant resources and the importance of maintaining a collaborative scientific community beyond nationalism during a pandemic.
    Language
    e
  18. Jiao, H.; Qiu, Y.; Ma, X.; Yang, B.: Dissmination effect of data papers on scientific datasets (2024) 0.00 
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    Date
    7. 1.2024 18:24:29
    Language
    e
  19. Wang, S.; Ma, Y.; Mao, J.; Bai, Y.; Liang, Z.; Li, G.: Quantifying scientific breakthroughs by a novel disruption indicator based on knowledge entities : On the rise of scrape-and-report scholarship in online reviews research (2023) 0.00 
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    Date
    22. 1.2023 18:37:33
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  20. Asubiaro, T.V.; Onaolapo, S.: ¬A comparative study of the coverage of African journals in Web of Science, Scopus, and CrossRef (2023) 0.00 
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    Date
    22. 6.2023 14:09:06
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    e

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