CorTexT platform

@article{Mao2022,

title = {Can machine understand public administration literature? Applying text mining for systematic review},

author = {Hanjin Mao and Huafang Li},

url = {https://journals.sagepub.com/doi/abs/10.1177/15396754221109319},

doi = {10.1177/15396754221109319},

year  = {2022},

date = {2022-06-28},

journal = {Chinese Public Administration Review},

abstract = {Systematic reviews summarize the progress of studies and pave roads for future research in an academic field. However, conducting a systematic literature review can be burdensome and time-consuming. Computer-assisted methods such as text mining techniques have been increasingly applied to improve systematic reviews in public administration. To test the reliability of using text mining for systematic literature reviews, this study uses clustering, topic modeling, automatic multi-term extraction, and text network to systematically review articles published in Chinese Public Administration Review from 2002 to 2019. By comparing machine-produced topics with existing human-coded themes, findings show that applying text mining methods for systematic reviews can be reliable and effective with cautions. The study also offers practical suggestions for researchers to apply text mining methods for systematic literature reviews.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Milia2022,

title = {Local emergence, global expansion: understanding the structural evolution of a bi-lingual national research landscape},

author = {Matias Federico Milia and Ariadna Nebot Giralt and Rigas Arvanitis},

url = {https://link.springer.com/article/10.1007/s11192-022-04403-9},

doi = {10.1007/s11192-022-04403-9},

year  = {2022},

date = {2022-06-21},

urldate = {2022-06-21},

journal = {Scientometrics},

abstract = {Research institutions organize their scientific activities in an increasingly diverse landscape. In matters of global interest, research relies on an ever-more cross-disciplinary background, which reveals intriguing questions concerning the local dynamics vs. global audiences. This paper proposes new methodological tools to assess, from a strategic perspective, the evolution of a given research landscape. It relies on the Global Research Institute of Paris’ recent experience, a new interdisciplinary Institute focusing on globalization topics beyond the usual economic meaning. The Institute leans on a broad and diverse set of research units of the Université de Paris and relates to the broad landscape of social sciences in France. This article charts the evolution of French authors’ scientific publications on the Institute’s thematic interests in French and English. It focuses on the structural features of the debate, namely the volume, the underlying historical semantic structure, and its main thematic domains. The paper offers significant evidence to understand knowledge circulation dynamics and links that non-speaking countries’ scientific literature builds with the English one.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Franco2022,

title = {Producing and using artificial intelligence: What can Europe learn from Siemens’s experience?},

author = {Sebastián Fernández Franco and Juan M Graña and David Flacher and Cecilia Rikap},

url = {https://www.researchgate.net/profile/Juan-Grana-2/publication/360759657_Producing_and_using_artificial_intelligence_What_can_Europe_learn_from_Siemens's_experience/links/62a739f955273755ebe9963b/Producing-and-using-artificial-intelligence-What-can-Europe-learn-from-Siemenss-experience.pdf},

doi = {10.1177/10245294221097066},

year  = {2022},

date = {2022-06-10},

journal = {Competition & Change},

volume = {0},

pages = {1–30},

abstract = {This paper examines the innovation strategy of Siemens, a key player in Europe’s digital economy, by performing network and lexical analyses using data derived from Siemens’s patents and scientific publications since 1998. We observe that the company’s innovation efforts evolved from a broader attempt to develop internal information and communication technology (ICT) capabilities – alongside its historical industrial priorities – to a strategy focused on developing artificial intelligence (AI) for sector-specific and niche applications (such as life and medical sciences). As a result, it became dependent on tech giants’ clouds for accessing more general AI services and digital infrastructure. We build on the intellectual monopoly literature focusing on the effects of tech giants on other leading corporations, to analyse Siemens’s experience. By abandoning the development of general ICT and given the emergence of tech giants as digital economy intellectual monopolies, we show that Siemens is risking its technological autonomy towards these big tech companies. Our results provide clues to understand the challenges faced by Europe and its firms in relation to US and Chinese tech giants.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Crépel2022,

title = {Robots vs algorithmes. Prophétie et critique dans la représentation médiatique des controverses de l’IA.},

author = {Maxime Crépel and Dominique Cardon},

url = {https://www.cairn.info/revue-reseaux-2022-2-page-129.htm},

doi = {10.3917/res.232.0129},

year  = {2022},

date = {2022-06-02},

journal = {Réseaux},

volume = {2022/2-3},

issue = {232-233},

pages = {129-167},

abstract = {Signée par Elon Musk, Stephen Hawking, Steve Wozniak et Noam Chomsky, une lettre ouverte publiée en 2015 alerte sur les risques existentiels auxquels l’humanité doit faire face en raison des nouveaux développements de l’IA. Elle constitue un moment clé de la réactivation d’un ensemble de ressources narratives et normatives visant à porter sur la place publique un débat critique relatif aux progrès de l’IA. Par vagues successives, les promesses et les risques de l’intelligence artificielle sont venus occuper de façon spectaculaire la discussion publique. À partir de méthode de TAL appliquée à un large corpus de la presse anglo-saxonne, cet article montre que le thème des algorithmes et de l’IA occupe un espace croissant dans la sphère médiatique depuis 5 ans. Le corpus se structure autour de deux espaces sémantiques qui constituent deux régimes dominants de critique, l’un fondé sur les injustices produites par les algorithmes et l’autre sur les peurs de l’autonomie de l’IA et des robots. L’analyse comparée de ces espaces montre qu’ils mobilisent des agents technologiques et humains, des troubles et une temporalité distincts. En développant un discours critique sur les méfaits de ces technologies, la sphère médiatique contribue à forger l’opinion publique mais aussi à définir les formes d’acceptabilité de ces agents calculateurs.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}