A research infrastructure for the social sciences & humanities

@article{Víquez2025,

title = {Urban politics of ordinary digital participation - From risk management to environmental mobilization in San José, Costa Rica},

author = {Sofia Guevara Víquez and Baptiste Kotras},

url = {https://journals.openedition.org/netcom/9839},

doi = {/10.4000/1572p},

year  = {2025},

date = {2025-11-29},

journal = {Open edition journals},

volume = {39-1/2},

abstract = {Based on long-term ethnographic and “chatnographic” fieldwork (2015-2024), this article examines the ordinary uses of digital technologies in urban risk management in San José, Costa Rica, focusing on residents’ communication practices via WhatsApp and Facebook around flooding of the Ocloro River. It analyzes how inhabitants mobilize mainstream digital tools to organize collectively in the face of environmental risks and to redefine their relationship with territory and public institutions. Our paper combines interviews, participant observation, and qualitative and quantitative analysis of 4,479 messages exchanged in a WhatsApp group created and managed by residents. The results highlight three main dynamics: (1) the infrapolitical self-organization of residents during emergencies; (2) the accountability—and at times contestation—of public authorities, made possible through the circulation of images, data, and digital traces; and (3) the gradual politicization of environmental issues, leading to collective mobilization for the protection of the river basin, beyond the immediate concern of flooding.



The study thus reveals a process of digital placemaking, in which social media become instruments for producing knowledge and governing territory “from below.” WhatsApp and Facebook—everyday, mainstream applications—are used for the production, archiving, and mobilization of lay knowledge in legal and political action. In the Latin American context, these ordinary digital practices contribute to reconfiguring urban governance and transforming citizen participation into a locally grounded form of environmental action.



===========



Politiser l'espace urbain par la participation numérique ordinaire De la gestion de risque à la mobilisation environnementale à San José, Costa Rica



Fondé sur une enquête ethnographique et « chatnographique » de long terme (2015-2024), cet article examine les usages ordinaires des technologies numériques dans la gestion des risques urbains à San José (Costa Rica), en se concentrant sur les pratiques de communication via WhatsApp et Facebook des habitant·es, autour des inondations du fleuve Ocloro. Il analyse la manière dont les habitants mobilisent des outils numériques grand public pour s’organiser face aux risques environnementaux et redéfinir leurs rapports au territoire et aux institutions. L’article combine entretiens, observations participantes et analyse qualitative et quantitative de 4 479 messages échangés sur un groupe WhatsApp créé et animé par les habitant·es. Les résultats montrent que ces usages numériques soutiennent trois dynamiques principales : (1) une auto-organisation infra-politique des habitants face aux urgences ; (2) une mise en responsabilité voire une contestation des autorités publiques, rendue possible par la circulation d’images, de données et de traces numériques ; (3) une politisation progressive des enjeux environnementaux, donnant lieu à une mobilisation collective pour la protection du bassin versant, au-delà du seul risque d’inondation. L’étude met ainsi en évidence un processus de digital placemaking, où les médias sociaux deviennent des instruments de connaissance et de gouvernement du territoire « par le bas ». WhatsApp et Facebook, applications grand public et utilisées au quotidien, sont mobilisées pour la production de savoirs profanes sur les risques, leur archivage et leur mobilisation dans des actions juridiques et politiques. Dans le contexte latino-américain, ces pratiques ordinaires du numérique contribuent à reconfigurer la gouvernance urbaine et à transformer la participation citoyenne en une forme d’action environnementale localement située.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cricchio2025,

title = {Balancing openness and ownership: open innovation strategies for AI development},

author = {Jacopo Cricchio},

url = {https://doi.org/10.1108/EJIM-04-2024-0470},

doi = {10.1108/EJIM-04-2024-0470},

issn = {1460-1060},

year  = {2025},

date = {2025-09-23},

journal = {European Journal of Innovation Management},

address = {Pisa, Italy},

school = {Sant’Anna School of Advanced Studies, Institute of Management},

abstract = {This paper explores how firms configure open innovation (OI) strategies when integrating artificial intelligence (AI) into their innovation models. Through the case of Baidu, it examines how OI contributes to business model innovation, highlighting how firms navigate the tension between openness and ownership in AI development.Adopting an exploratory case study approach, the research employs big data analysis methods, including thematic network and collaboration cluster analyses. These methods are applied to a comprehensive dataset of granted patents and scientific publications spanning 2000 to 2023, sourced from Orbis intellectual property and Web of Science databases.The analysis reveals a dual OI configuration: Baidu engages openly in scientific collaborations to foster value creation, while relying on centralized patenting strategies to secure value capture. This modular approach reflects a dynamic governance of knowledge across research and patenting domains. Baidu structures its AI innovation through selective openness, enabling agile adaptation in a rapidly evolving technological landscape.This study contributes to research on AI, OI, business model innovation and dynamic capabilities by illustrating how hybrid openness strategies function as organizational mechanisms for sensing, seizing and transforming. It offers interpretive insights into the design tensions of OI and provides a grounded perspective on how firms strategically navigate collaboration, protection and innovation in data-intensive contexts.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Tollefson2025,

title = {Community Resilience Planning: What New Methods Reveal About the Formation and Transformation of a Field},

author = {Jonathan Tollefson and Scott Frickel and Christina Gore and Jennifer Helgeson},

url = {https://wires.onlinelibrary.wiley.com/doi/epdf/10.1002/wcc.70015

https://wires.onlinelibrary.wiley.com/doi/pdf/10.1002/wcc.70015

https://wires.onlinelibrary.wiley.com/doi/10.1002/wcc.70015

},

doi = {/10.1002/wcc.70015},

year  = {2025},

date = {2025-08-12},

urldate = {2025-08-12},

journal = {WIREs Climate Change},

volume = {16},

issue = {4},

abstract = {Community resilience planning (CRP) research encompasses diverse disciplinary foci, ranging from ecological and socio-political to engineering studies, and employs a range of analytic scales and methodologies. Despite the rise of integrative approaches to studying increasingly complex risks faced by communities—in particular, the growing, and often inequitable, impacts of climate and weather stressors and extremes—CRP remains a fragmented field of study and practice. This paper provides a broad map of the CRP field over the last 25 years, linking bibliometric methods with novel, network-based, multi-level approaches to computational text analysis. Despite trends toward interdisciplinary and transdisciplinary research, our analysis demonstrates that the CRP field consists of divergent bodies of research, characteristic of disciplinary siloing. At the same time, new approaches to computational text analysis provide innovative ways to understand the epistemic and social links across subfields, revealing patterns of connectivity that traditional citation-based bibliometric methods cannot access.

Results indicate that the development and maturation of CRP are characterized in part by a longitudinal transformation in research methods and by a shift in substantive questions that CRP researchers are asking. These findings suggest that thematic and credit-based structures operate in tandem to produce complex webs of interconnection across the disciplinary domains that have historically constituted the field.},

note = {The Sashimi method was used via the Python module. The Sashimi method has a modular architecture that allows it to be used independently of the Cortext Manager web application, which has not been used here.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Qi2025,

title = {Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait},

author = {Wenhao Qi and Shiying Shen and Chaoqun dong and Mengjiao Zhao and Shuaiqi Zang and Xiaohong Zhu and Jiaqi Li and Bin Wang and Yankai Shi and Yongze Dong and Huajuan Shen and Junling Kang and Xiaodong Lu and Guowei Jiang and Jingsong Du and Eryi Shu and Qingbo Zhou and Jinghua Wang and Shihua Cao},

url = {https://www.jmir.org/2025/1/e71560/

https://www.jmir.org/2025/1/e71560/PDF},

doi = {10.2196/71560},

year  = {2025},

date = {2025-05-20},

journal = {Journal of Medical Internet Research},

volume = {27},

abstract = {Background: With the rapid development of digital biomarkers in Parkinson disease (PD) research, it has become increasingly important to explore the current research trends and key areas of focus.



Objective: This study aimed to comprehensively evaluate the current status, hot spots, and future trends of global PD biomarker research, and provide a systematic review of deep learning models for freezing of gait (FOG) digital biomarkers.



Methods: This study used bibliometric analysis based on the Web of Science Core Collection database to conduct a comprehensive analysis of the multidimensional landscape of Parkinson digital biomarkers. After identifying research hot spots, the study also followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines for a scoping review of deep learning models for FOG from 5 databases: Web of Science, PubMed, IEEE Xplore, Embase, and Google Scholar.



Results: A total of 750 studies were included in the bibliometric analysis, and 40 studies were included in the scoping review. The analysis revealed a growing number of related publications, with 3700 researchers contributing. Neurology had the highest average annual participation rate (12.46/19, 66%). The United States contributed the most research (192/1171, 16.4%), with 210 participating institutions, which was the highest among all countries. In the study of deep learning models for FOG, the average accuracy of the models was 0.92, sensitivity was 0.88, specificity was 0.90, and area under the curve was 0.91. In addition, 31 (78%) studies indicated that the best models were primarily convolutional neural networks or convolutional neural networks–based architectures.



Conclusions: Research on digital biomarkers for PD is currently at a stable stage of development, with widespread global interest from countries, institutions, and researchers. However, challenges remain, including insufficient interdisciplinary and interinstitutional collaboration, as well as a lack of corporate funding for related projects. Current research trends primarily focus on motor-related studies, particularly FOG monitoring. However, deep learning models for FOG still lack external validation and standardized performance reporting. Future research will likely progress toward deeper applications of artificial intelligence, enhanced interinstitutional collaboration, comprehensive analysis of different data types, and the exploration of digital biomarkers for a broader range of Parkinson symptoms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}