Using a compound approach based on elaborated neural network for Webometrics: An example issued from the EICSTES project

Lamirel, Jean–Charles; Shehabi, Shadi Al; François, Claire; Polanco, Xavier

doi:10.1023/b:scie.0000045119.88828.ce

Cited by 13 publications

(9 citation statements)

References 11 publications

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“…After the initial research, there was a period of methodological development in which Webometrics defined its key terminology (Björneborn & Ingwersen, 2004), developed specialist data collection and analysis software (Cothey, 2004; Heimeriks et al, 2003; Thelwall, 2001), assessed new methods for counting links (Thelwall, 2002), and introduced a range of visualisation techniques for presenting the results (Heimeriks et al, 2003; Heimeriks & van den Besselaar, 2006; Lamirel, Al Shehabi, Francois, & Polanco, 2004; Ortega et al, 2008; Prime, Bassecoulard, & Zitt, 2002; Vaughan, 2005, 2006).…”

Section: The Development Of Policy‐relevant Webometricsmentioning

confidence: 99%

Policy‐relevant Webometrics for individual scientific fields

Thelwall

Klitkou

Verbeek

et al. 2010

J. Am. Soc. Inf. Sci.

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Section: The Development Of Policy‐relevant Webometricsmentioning

confidence: 99%

Policy‐relevant Webometrics for individual scientific fields

Thelwall

Klitkou

Verbeek

et al. 2010

J. Am. Soc. Inf. Sci.

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“…BNs have been used to classify authors according to citation patterns (Lehmann et al 2008), to assess the impact of variables in the innovation collaboration process (Kim and Park 2008) and webometrics (Lamirel et al 2004). Leydesdorff (1992) proposed a Bayesian approach to science studies that can be understood as the analysis of the interaction between two dynamic principles: hypotheses and evidences.…”

Section: Introductionmentioning

confidence: 99%

Efficiency measurement of research groups using Data Envelopment Analysis and Bayesian networks

et al. 2009

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Applications of non-parametric frontier production methods such as Data Envelopment Analysis (DEA) have gained popularity and recognition in scientometrics. DEA seems to be a useful method to assess the efficiency of research units in different fields and disciplines. However, DEA results give only a synthetic measurement that does not expose the multiple relationships between scientific production variables by discipline. Although some papers mention the need for studies by discipline, they do not show how to take those differences into account in the analysis. Some studies tend to homogenize the behaviour of different practice communities. In this paper we propose a framework to make inferences about DEA efficiencies, recognizing the underlying relationships between production variables and efficiency by discipline, using Bayesian Network (BN) analysis. Two different DEA extensions are applied to calculate the efficiency of research groups: one called CCRO and the other Cross Efficiency (CE). A BN model is proposed as a method to analyze the results obtained from DEA. BNs allow us to recognize peculiarities of each discipline in terms of scientific production and the efficiency frontier. Besides, BNs provide the possibility for a manager to propose what-if scenarios based on the relations found.

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“…Yet, in addition to the owners of commercial search engines, they are increasingly used by a widening section of society including casual Web users, the creators of e‐mail spam lists, and others looking for information of commercial value. In addition, many new types of information science research rely upon Web crawlers or automatically downloading pages (e.g., Björneborn, 2004; Faba‐Perez, Guerrero‐Bote, & De Moya‐Anegon, 2003; Foot, Schneider, Dougherty, Xenos, & Larsen, 2003; Heimeriks, Hörlesberger, & van den Besselaar, 2003; Koehler, 2002; Lamirel, Al Shehabi, Francois, & Polanco, 2004; Leydesdorff, 2004; Rogers, 2004; Vaughan & Thelwall, 2003; Wilkinson, Harries, Thelwall, & Price, 2003; Wouters & de Vries, 2004). Web crawlers are potentially very powerful tools, with the ability to cause network problems and incur financial penalties to the owners of the Web sites crawled.…”

Section: Introductionmentioning

confidence: 99%

Science, society and sustainability: Education and empowerment for an uncertain world

Heimlich

2010

Science Education

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Ethical aspects of the employment of Web crawlers for information science research and other contexts are reviewed. The difference between legal and ethical uses of communications technologies is emphasized as well as the changing boundary between ethical and unethical conduct. A review of the potential impacts on Web site owners is used to underpin a new framework for ethical crawling, and it is argued that delicate human judgment is required for each individual case, with verdicts likely to change over time. Decisions can be based upon an approximate cost‐benefit analysis, but it is crucial that crawler owners find out about the technological issues affecting the owners of the sites being crawled in order to produce an informed assessment.

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Using a compound approach based on elaborated neural network for Webometrics: An example issued from the EICSTES project

Cited by 13 publications

References 11 publications

Policy‐relevant Webometrics for individual scientific fields

Policy‐relevant Webometrics for individual scientific fields

Efficiency measurement of research groups using Data Envelopment Analysis and Bayesian networks

Science, society and sustainability: Education and empowerment for an uncertain world

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