-
Rotolo, D.; Rafols, I.; Hopkins, M.M.; Leydesdorff, L.: Strategic intelligence on emerging technologies : scientometric overlay mapping (2017)
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- Abstract
- This paper examines the use of scientometric overlay mapping as a tool of "strategic intelligence" to aid the governing of emerging technologies. We develop an integrative synthesis of different overlay mapping techniques and associated perspectives on technological emergence across geographical, social, and cognitive spaces. To do so, we longitudinally analyze (with publication and patent data) three case studies of emerging technologies in the medical domain. These are RNA interference (RNAi), human papillomavirus (HPV) testing technologies for cervical cancer, and thiopurine methyltransferase (TPMT) genetic testing. Given the flexibility (i.e., adaptability to different sources of data) and granularity (i.e., applicability across multiple levels of data aggregation) of overlay mapping techniques, we argue that these techniques can favor the integration and comparison of results from different contexts and cases, thus potentially functioning as a platform for "distributed" strategic intelligence for analysts and decision makers.
-
Rokach, L.; Kalech, M.; Blank, I.; Stern, R.: Who is going to win the next Association for the Advancement of Artificial Intelligence Fellowship Award? : evaluating researchers by mining bibliographic data (2011)
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- Abstract
- Accurately evaluating a researcher and the quality of his or her work is an important task when decision makers have to decide on such matters as promotions and awards. Publications and citations play a key role in this task, and many previous studies have proposed using measurements based on them for evaluating researchers. Machine learning techniques as a way of enhancing the evaluating process have been relatively unexplored. We propose using a machine learning approach for evaluating researchers. In particular, the proposed method combines the outputs of three learning techniques (logistics regression, decision trees, and artificial neural networks) to obtain a unified prediction with improved accuracy. We conducted several experiments to evaluate the model's ability to: (a) classify researchers in the field of artificial intelligence as Association for the Advancement of Artificial Intelligence (AAAI) fellows and (b) predict the next AAAI fellowship winners. We show that both our classification and prediction methods are more accurate than are previous measurement methods, and reach a precision rate of 96% and a recall of 92%.
-
Rokach, L.; Mitra, P.: Parsimonious citer-based measures : the artificial intelligence domain as a case study (2013)
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- Abstract
- This article presents a new Parsimonious Citer-Based Measure for assessing the quality of academic papers. This new measure is parsimonious as it looks for the smallest set of citing authors (citers) who have read a certain paper. The Parsimonious Citer-Based Measure aims to address potential distortion in the values of existing citer-based measures. These distortions occur because of various factors, such as the practice of hyperauthorship. This new measure is empirically compared with existing measures, such as the number of citers and the number of citations in the field of artificial intelligence (AI). The results show that the new measure is highly correlated with those two measures. However, the new measure is more robust against citation manipulations and better differentiates between prominent and nonprominent AI researchers than the above-mentioned measures.
-
Herb, U.: Überwachungskapitalismus und Wissenschaftssteuerung (2019)
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- Abstract
- Die Metamorphose des Wissenschaftsverlags Elsevier zum Research Intelligence Dienstleister ist paradigmatisch für die neuen Möglichkeiten der Protokollierung und Steuerung von Wissenschaft.
-
Leydesdorff, L.; Goldstone, R.L.: Interdisciplinarity at the journal and specialty level : the changing knowledge bases of the journal cognitive science (2014)
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- Abstract
- Using the referencing patterns in articles in Cognitive Science over three decades, we analyze the knowledge base of this literature in terms of its changing disciplinary composition. Three periods are distinguished: (A) construction of the interdisciplinary space in the 1980s, (B) development of an interdisciplinary orientation in the 1990s, and (C) reintegration into "cognitive psychology" in the 2000s. The fluidity and fuzziness of the interdisciplinary delineations in the different visualizations can be reduced and clarified using factor analysis. We also explore newly available routines ("CorText") to analyze this development in terms of "tubes" using an alluvial map and compare the results with an animation (using "Visone"). The historical specificity of this development can be compared with the development of "artificial intelligence" into an integrated specialty during this same period. Interdisciplinarity should be defined differently at the level of journals and of specialties.
-
Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- Date
- 18. 3.2014 19:13:22
-
Aledo, J.A.; Gámez, J.A.; Molina, D.; Rosete, A.: Consensus-based journal rankings : a complementary tool for bibliometric evaluation (2018)
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- Abstract
- Annual journal rankings are usually considered a tool for the evaluation of research and researchers. Although they are an objective resource for such evaluation, they also present drawbacks: (a) the uncertainty about the definite position of a target journal in the corresponding annual ranking when selecting a journal, and (b) in spite of the nonsignificant difference in score (for instance, impact factor) between consecutive journals in the ranking, the journals are strictly ranked and eventually placed in different terciles/quartiles, which may have a significant influence in the subsequent evaluation. In this article we present several proposals to obtain an aggregated consensus ranking as an alternative/complementary tool to standardize annual rankings. To illustrate the proposed methodology we use as a case study the Journal Citation Reports, and in particular the category of Computer Science: Artificial Intelligence (CS:AI). In the context of the consensus rankings obtained by the different methods, we discuss the convenience of using one or the other procedure according to the corresponding framework. In particular, our proposals allow us to obtain consensus rankings that avoid crisp frontiers between similarly ranked journals and consider the longitudinal/temporal evolution of the journals.
-
Scholarly metrics under the microscope : from citation analysis to academic auditing (2015)
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- Date
- 22. 1.2017 17:12:50
-
Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014)
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- Date
- 22. 8.2014 17:05:18
-
Ohly, P.: Dimensions of globality : a bibliometric analysis (2016)
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- Date
- 20. 1.2019 11:22:31
-
Crespo, J.A.; Herranz, N.; Li, Y.; Ruiz-Castillo, J.: ¬The effect on citation inequality of differences in citation practices at the web of science subject category level (2014)
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- Abstract
- This article studies the impact of differences in citation practices at the subfield, or Web of Science subject category level, using the model introduced in Crespo, Li, and Ruiz-Castillo (2013a), according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters data set of about 4.4 million articles used in Crespo et al. (2013a) to analyze 22 broad fields. The main results are the following: First, when the classification system goes from 22 fields to 219 subfields the effect on citation inequality of differences in citation practices increases from ?14% at the field level to 18% at the subfield level. Second, we estimate a set of exchange rates (ERs) over a wide [660, 978] citation quantile interval to express the citation counts of articles into the equivalent counts in the all-sciences case. In the fractional case, for example, we find that in 187 of 219 subfields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. Third, in the fractional case the normalization of the raw data using the ERs (or subfield mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourth, the results in the fractional case are essentially replicated when we adopt a multiplicative approach.
-
Yan, E.: Finding knowledge paths among scientific disciplines (2014)
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- Date
- 26.10.2014 20:22:22
-
Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015)
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- Date
- 20. 1.2015 18:30:22
17. 9.2018 18:22:23
-
Campanario, J.M.: Large increases and decreases in journal impact factors in only one year : the effect of journal self-citations (2011)
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- Date
- 22. 1.2011 12:53:00
-
Ding, Y.: Applying weighted PageRank to author citation networks (2011)
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- Date
- 22. 1.2011 13:02:21
-
Schlögl, C.: Internationale Sichtbarkeit der europäischen und insbesondere der deutschsprachigen Informationswissenschaft (2013)
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- Date
- 22. 3.2013 14:04:09
-
Vieira, E.S.; Cabral, J.A.S.; Gomes, J.A.N.F.: Definition of a model based on bibliometric indicators for assessing applicants to academic positions (2014)
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- Date
- 18. 3.2014 18:22:21
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Ajiferuke, I.; Lu, K.; Wolfram, D.: ¬A comparison of citer and citation-based measure outcomes for multiple disciplines (2010)
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- Date
- 28. 9.2010 12:54:22
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Albarrán, P.; Ruiz-Castillo, J.: References made and citations received by scientific articles (2011)
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- Abstract
- This article studies massive evidence about references made and citations received after a 5-year citation window by 3.7 million articles published in 1998 to 2002 in 22 scientific fields. We find that the distributions of references made and citations received share a number of basic features across sciences. Reference distributions are rather skewed to the right while citation distributions are even more highly skewed: The mean is about 20 percentage points to the right of the median, and articles with a remarkable or an outstanding number of citations represent about 9% of the total. Moreover, the existence of a power law representing the upper tail of citation distributions cannot be rejected in 17 fields whose articles represent 74.7% of the total. Contrary to the evidence in other contexts, the value of the scale parameter is above 3.5 in 13 of the 17 cases. Finally, power laws are typically small, but capture a considerable proportion of the total citations received.
-
D'Angelo, C.A.; Giuffrida, C.; Abramo, G.: ¬A heuristic approach to author name disambiguation in bibliometrics databases for large-scale research assessments (2011)
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- Date
- 22. 1.2011 13:06:52
