Data Mining and Text Mining for Science &amp; Technology Research

Leopold, Edda; May, Michael; Paaß, Gerhard

doi:10.1007/1-4020-2755-9_9

Cited by 16 publications

(8 citation statements)

References 23 publications

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“…In the second step, we applied a traditional data-mining technique, the bag of words method (Salton and McGill, 1983;Leopold et al, 2004). For each disciplinary field we built a complete set of words from the titles and abstracts of all the patents and publications, so that each document j (patent or publication) could be represented by a vector.…”

Section: Patent-publication Pairs: Methodologymentioning

confidence: 99%

Inventorship and authorship as attribution rights: An enquiry into the economics of scientific credit

Lissoni

Montobbio

Zirulia

2013

Journal of Economic Behavior & Organization

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a b s t r a c tAuthorship and inventorship are "attribution rights" upon which individual scientists build their reputation and career. Social and legal norms concerning their distribution within research teams are currently criticized for failing to inform third parties on individual contributions. We examine the case of teams engaged in the "double disclosure" of their research results through both publications and patents, and model the negotiation process taking place between junior or female team members and the senior (male) ones. We suggest that the former may give up inventorship in order to secure authorship, even when entitled to the both. Based on a sample of 680 "patent-publication pairs" (related sets of patents and publications) we show that, very frequently, one or more authors of a publication do not appear as inventors of a related patent. This is less likely to happen for first and last authors, which is in accordance both with our model and the prevailing legal norms on inventorship. However, the probability of exclusion from inventorship also declines with seniority, and increases for women, which is compatible with our model only.

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Section: Patent-publication Pairs: Methodologymentioning

confidence: 99%

Inventorship and authorship as attribution rights: An enquiry into the economics of scientific credit

Lissoni

Montobbio

Zirulia

2013

Journal of Economic Behavior & Organization

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“…We focus on Italian academic inventors from the Knowledge-Based Entrepreneurship: Innovation, Networks and Systems database (see Lissoni, .and Tarasconi 2006), from the four disciplinary fields with the highest share of academic inventors over the total number of professors in the field; namely chemical engineering (which includes technology of materials, such as macromolecular compounds), biology, pharmacology, and electronics and telecommunications, for a total of 308 academic inventors and 552 patents (see also Breschi, Lissoni, and Montobbio 2005, 2007). PPPs were then obtained by matching publication data from the ISI Science Citation Index for such academic inventors to their patents, on the basis of a comparison of the titles and abstracts of patents and publications through a variety of “coword analysis” techniques (Leopold, May, and Paaß 2004; Bassecoulard and Zitt 2004). Time restrictions were also applied, so that no publication was selected for the matching exercise, which appeared in a journal more than 2 years before or after the priority date of the patent.…”

Section: Inventorship Attribution In Academia: Recent Evidencementioning

confidence: 99%

Guest Authors or Ghost Inventors? Inventorship and Authorship Attribution in Academic Science

Lissoni

Montobbio

2014

Eval Rev

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“…Term mapping is one such method. Fortunately, advanced computational techniques from fields such as data mining, machine learning, statistics, and text mining may be used to take over certain tasks in bibliometric analysis that are traditionally performed by domain experts (for an overview of various computational techniques, see Leopold et al 2004). The research presented in this paper can be seen as an elaboration of this idea in the context of term mapping.…”

Section: Discussionmentioning

confidence: 99%

Automatic term identification for bibliometric mapping

et al. 2010

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A term map is a map that visualizes the structure of a scientific field by showing the relations between important terms in the field. The terms shown in a term map are usually selected manually with the help of domain experts. Manual term selection has the disadvantages of being subjective and labor-intensive. To overcome these disadvantages, we propose a methodology for automatic term identification and we use this methodology to select the terms to be included in a term map. To evaluate the proposed methodology, we use it to construct a term map of the field of operations research. The quality of the map is assessed by a number of operations research experts. It turns out that in general the proposed methodology performs quite well.

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Data Mining and Text Mining for Science & Technology Research

Cited by 16 publications

References 23 publications

Inventorship and authorship as attribution rights: An enquiry into the economics of scientific credit

Inventorship and authorship as attribution rights: An enquiry into the economics of scientific credit

Guest Authors or Ghost Inventors? Inventorship and Authorship Attribution in Academic Science

Automatic term identification for bibliometric mapping

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