Cortext platform

@conference{Huang2022,

title = {The research trend of open government data utilization: A systematic review},

author = {Ruhua Huang and Yuting Huang},

url = {https://hdl.handle.net/2142/113752

https://www.ideals.illinois.edu/items/123108},

year  = {2022},

date = {2022-06-06},

urldate = {2022-06-06},

publisher = {University of Illinois},

address = {China},

organization = {Wuhan University},

abstract = {The open government data (OGD) movement has stimulated the opening and sharing of government data significantly. Data use, reuse and distribution, as well as value creation, is the next vital step in the global OGD movement. Summarizing current research progress of OGD utilization (OGDU) would lay a foundation for follow-up research and provide theoretical support for future practice. This poster conducted a systematic review on OGDU research mainly based on research articles, while other document types (e.g., important scientific reports) were also considered to demonstrate a more holistic scenario. The research trends of OGDU were summarized and future research directions were proposed based on research results. This poster revealed three research tendencies in OGDU studies. First, previous OGDU study was driven by the supply side, while current study tends to motivated by the demand side. Second, previous OGDU study was normally conducted from a macro viewpoint, while fine-grained research is more preferred currently. Third, previous research paid more attention on data usage by government departments, while data usage by the public attracts an increasing amount of attention currently. Several research topics are worth researching in the further, i.e., the value of OGDU, diverse contexts for OGDU and solid support measures for OGDU.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Papazu2022,

title = {Controversy Mapping and the Care for Climate Commons: Re-assembling the Danish Climate Movement by Counter-Mapping Digital Network Maps},

author = {Irina Papazu and Adam Veng},

url = {https://pure.itu.dk/en/publications/controversy-mapping-and-the-care-for-climate-commons-re-assemblin

https://events.au.dk/dasts2022/about},

year  = {2022},

date = {2022-06-02},

organization = {DASTS},

school = {Aarhus University},

abstract = {The general electoral campaign in 2019 saw a unifying culmination of the climate activist movement in Denmark, assembling everything from green think tanks, school children and direct-action protest groups, succeeded in conglomerating a forceful public that was later congratulated by the newly elected PM for turning climate into the paramount political issue of the Danish 2019 election. The government has since signed the “most ambitious Climate Act in the world”, including the public engagement initiative of the Climate Citizen Assembly, a group of randomly selected citizens mandated to give recommendations for the parliament’s green politics, and a series of “Climate Partnerships”, cooperative collaborations developing frameworks for businesses to engage in the green transition. Despite these efforts, the climate movement, alongside several scientific experts, has expressed dissatisfaction with the government’s politics on the green agenda, while the government itself maintains that it is upholding an ambitious climate politics.

This paper is based on nine months of mixed-methods research, using the digital tools Hyphe, Gephi and CorText to map the relations between different public Danish actors (informal civil society groups, NGO’s, businesses etc.) and their “matters of concern” (cf. Latour 2004) in the controversy of the Danish green transition. Inspired by literature on counter-mapping data science (Dalton and Stallmann 2018), the study introduces an interventionist methodological experiment in using network maps made with digital methods tools as props for material participation (Marres & Lezeaun 2011) in a workshop setting. As such, the paper seeks to explore how critical discussions of network maps can become a ‘prototype for mobilization’ (cf. Jimenéz 2014) for mapped subjects and entities to collectively evaluate and re-invent both their position in a controversy and their means, methods, and tactics for obtaining public impact. This methodological experiment is framed through a discussion of the experience of participation (Kelty 2018) and ethical attunement and world-building among activists (Zigon 2018), and argues for the potentials for collaborative methods and interventionist use of digital cartography in the field of controversy mapping in relation to the green transition.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Rizzo2022,

title = {Is farming technology innovation locus dependent? Making-of an agricultural Fablab},

author = {Davide Rizzo and Anne Combaud and Nathalie Schnuriger and Fatma Fourati-Jamoussi and Simon Ritz and Valérie Leroux},

url = {http://ifsa.boku.ac.at/cms/fileadmin/IFSA2022/IFSA2022_Proceedings_Th5.pdf},

year  = {2022},

date = {2022-04-08},

urldate = {2022-04-08},

booktitle = {Digital book of proceedings, 14th European IFSA symposium},

issuetitle = {Farming systems facing climate change and resource challenges},

organization = {14th European IFSA symposium},

school = {University of ÉVORA, Portugal},

abstract = {Innovation has multiple targets – products, production processes, marketing, stakeholders’ organizations, etc. – whose nature depends upon the socio-technical framework that orients the match between inventions and market. Amid the wealth of options to facilitate innovation, fablabs are a specific example of the digitalisation era. Originally, a fablab is “the educational outreach component of MIT’s Center for Bits and Atoms” whose identity is defined by a charter that connects local labs to the

global network. Fablabs’ goal is to provide stimulus for local entrepreneurship as well as for learning and innovation by providing access to tools for digital fabrication. This paper aims at understanding the role of fablabs and other third places in the specific context of farming technology innovation. To this end, we propose a genetic-like analysis (i.e. genotype x environment x management practices), by addressing the historical identity and traits of FTI actors, the description of the main characteristics and dynamics of the place where they are based and the innovation governance put in practice to enhance

their interactions. The approach was applied at two levels: first, the main actors of the farming technology innovation in Europe, ending with a bibliometric analysis of the available literature about fablabs, makerspaces and living labs, with a focus on agriculture. Then, a case study from northern France to describe the making of AgriLab, a fablab dedicated to open innovation towards sustainable agriculture, spanning from equipment to digital tools. AgriLab is based in Beauvais (Hauts-de-France region), together with several other local and international actors of farming technology innovation. In conclusion, we question the role of third places and AgriLab as catalysts for the emergence of relevant farming technology innovations considering the influence from the local and wider context.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Luo2022,

title = {Topic Modeling of Political Dynamics with Shifted Cosine Similarity},

author = {Yifan Luo and Tao Wan and Zengchang Qin},

url = {https://link.springer.com/chapter/10.1007/978-3-030-98018-4_22},

doi = {10.1007/978-3-030-98018-4_22},

isbn = {978-3-030-98017-7},

year  = {2022},

date = {2022-03-04},

urldate = {2022-03-04},

booktitle = {Integrated Uncertainty in Knowledge Modelling and Decision Making},

volume = {13199},

publisher = {Springer, Cham},

abstract = {Topic modeling with community detection can be used to explore the latent semantic structure of documents, we can utilize a network, i.e., a graph to depict the semantic relation between words. In some network based topic models, in order to obtain a network with obvious community structure, the similarity between words (vertices) is essential. Word embeddings trained from a large corpus empirically perform as well as in rich semantic representation, thus this research is intended to construct a novel similarity in a network based topic model (NAM). In this paper, we first intuitively propose a similarity measure based on shifted cosine similarity between word embeddings. This similarity is exploited to replace the similarity based on typical point-wise mutual information (PMI). Secondly, based on different similarity measures, topics of corpus in a global period are induced by NAM. Finally, we use NAM to capture the dynamic changes of political topics in China and interpret the dynamic processes using historical background. Although our similarity measure introduces semantic differences caused by the difference between data sets and has one more parameter, the experimental results show the effectiveness of our new proposed measure.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}