A framework for research assessment in social sciences through Big Data


  • Guadalupe Palacios-Núñez
  • Miguel Ángel Pérez-Angón
  • Pedro Simón Quiroz Armada

Palabras clave:

Social Sciences, Research Assessment, Science Policy, Big Data, Blockchain


The scarce public policy funds demand cost-effective outputs and more innovative forms to inform decision making. During the last years, there has been increasing use of Big Data for research and policymaking by international development institutions. For this reason, the main objective of the present work is to propose a framework to apply Big Data in a high-relevance program for science policy in Mexico, which assesses the researchers' performance. Social sciences are considered the most difficult area to assess, due to there is no theoretical-methodological consensus and the academic impact is difficult to determine because social sciences do not exhibit long term development. Instead, there are a plurality of paradigms or changing topics that do not have consensus among the academic community. In this regard, this work outlines a framework, which includes indicators of the social contribution of science since computational tools should have an orientation.


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2022-03-17 — Actualizado el 2022-08-05


Cómo citar

Palacios-Núñez, G. ., Pérez-Angón , M. Ángel ., & Quiroz Armada , P. S. . (2022). A framework for research assessment in social sciences through Big Data . INCEPTUM, 16(31), 55–75. Recuperado a partir de https://www.ininee.umich.mx/index.php/inceptum/article/view/410 (Original work published 17 de marzo de 2022)