Algorithmic identification of Ph.D. thesis-related publications: a proof-of-concept study

Donner, Paul

doi:10.1007/s11192-022-04480-w

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…Additionally, automatic, or alternative formal matching algorithms between publications and dissertations could be used to cover more research fields, languages or countries (e.g. Donner, 2022;Echeverria et al, 2015;Heinisch & Buenstorf, 2018). However, based on the results of the study, we can conclude that a policy that allows doctoral students to write cumulative dissertations permits them to strengthen their research output counted as papers published or cited.…”

Section: Discussionmentioning

confidence: 98%

Patterns of dissertation dissemination: publication-based outcomes of doctoral theses in the social sciences

Asanov,

Buenstorf

et al. 2024

Scientometrics

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Dissemination of knowledge through the publication of findings is a cornerstone of the academic research system. Doctoral dissertations document the findings made by early-stage researchers during their doctoral studies. However, prior research suggests that dissertations may not be effective in disseminating these findings to the broader community of researchers. We study how knowledge documented in doctoral dissertations is disseminated. Specifically, we investigate which dissertation characteristics and institutional factors are related to the number of journal publications based on these dissertations and the number of citations that these publications receive. Our analysis uses a random sample of doctoral dissertations from German universities in economics, political science, and sociology. We find that “cumulative” dissertations—dissertations consisting of a number of separate articles—are turned into three times more publications which receive three times more citations than monographic dissertations. We also find explorative evidence that dissertations written in English and empirical dissertations have higher publication-based outcomes. We conclude that a policy allowing doctoral candidates to write their dissertations in a cumulative format provides them with an opportunity to share the results of their research through publications in peer-reviewed journals.

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Section: Discussionmentioning

confidence: 98%

Patterns of dissertation dissemination: publication-based outcomes of doctoral theses in the social sciences

Asanov,

Buenstorf

et al. 2024

Scientometrics

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“…One of the more exciting recent developments in empirical social science research is the increasing availability of large administrative databases and the ability to link across them to generate new insights. Indeed linked datasets have allowed researchers working in descriptive, predictive, and causal modalities to generate systematic inferences about large numbers of individuals [1][2][3][4][5][6][7][8][9]. Unfortunately, most administrative datasets are not designed to be linked to others and thus have no common and reliable unique identifiers.…”

Section: Introductionmentioning

confidence: 99%

No ground truth? No problem: Improving administrative data linking using active learning and a little bit of guile

et al. 2023

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While linking records across large administrative datasets [“big data”] has the potential to revolutionize empirical social science research, many administrative data files do not have common identifiers and are thus not designed to be linked to others. To address this problem, researchers have developed probabilistic record linkage algorithms which use statistical patterns in identifying characteristics to perform linking tasks. Naturally, the accuracy of a candidate linking algorithm can be substantially improved when an algorithm has access to “ground-truth” examples—matches which can be validated using institutional knowledge or auxiliary data. Unfortunately, the cost of obtaining these examples is typically high, often requiring a researcher to manually review pairs of records in order to make an informed judgement about whether they are a match. When a pool of ground-truth information is unavailable, researchers can use “active learning” algorithms for linking, which ask the user to provide ground-truth information for select candidate pairs. In this paper, we investigate the value of providing ground-truth examples via active learning for linking performance. We confirm popular intuition that data linking can be dramatically improved with the availability of ground truth examples. But critically, in many real-world applications, only a relatively small number of tactically-selected ground-truth examples are needed to obtain most of the achievable gains. With a modest investment in ground truth, researchers can approximate the performance of a supervised learning algorithm that has access to a large database of ground truth examples using a readily available off-the-shelf tool.

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Algorithmic identification of Ph.D. thesis-related publications: a proof-of-concept study

Cited by 2 publications

References 12 publications

Patterns of dissertation dissemination: publication-based outcomes of doctoral theses in the social sciences

Patterns of dissertation dissemination: publication-based outcomes of doctoral theses in the social sciences

No ground truth? No problem: Improving administrative data linking using active learning and a little bit of guile

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