Analytical sociology and computational social science

Keuschnigg, Marc; Lovsjö, Niclas; Hedström, Peter

doi:10.1007/s42001-017-0006-5

Cited by 63 publications

(52 citation statements)

References 67 publications

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“…Kalter and Kroneberg 2014; Léon-Medina 2017), and demonstrates that this perspective is not only compatible with big-data approaches (for a recent statement, see Keuschnigg et al 2017) but can equally well guide qualitatively-oriented, small-N studies. Finally, our paper shows that ethnoarcheology, when coupled with refined quantitative methods, and simulation techniques, is indeed able to identify robust generative causal patterns that can serve as explanatory building blocks for comparable contexts for which all required empirical information may not be available (for a recent debate, see Gosselain 2016; Roux 2017).…”

Section: Resultsmentioning

confidence: 88%

Complex Contagions and the Diffusion of Innovations: Evidence from a Small-N Study

Manzo

Gabbriellini

Roux

et al. 2018

J Archaeol Method Theory

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The recent literature on "complex contagions" challenges Granovetter's classic hypothesis on the strength of weak ties and argues that, when the actors' choice requires reinforcement from several sources, it is the structure of strong ties that really matters to sustain rapid and wide diffusion. The paper contributes to this debate by reporting on a small-N study that relies on a unique combination of ethnographic data, social network analysis, and computational models. In particular, we investigate two rural populations of Indian and Kenyan potters who have to decide whether adopting new, objectively more efficient and economically more attractive, technical/stylistic options. Qualitative field data show that religious sub-communities within the Indian and Kenyan populations exhibit markedly different diffusion rates and speed over the last thirty years. To account for these differences, we first analyze empirically observed kinship networks and advice networks, and, then, we recreate the actual aggregate diffusion curves through a series of empirically-calibrated agent-based simulations. Combining the two methods, we show that, while single exposure through heterophilious weak ties were sufficient to initiate the diffusion process, large bridges made of strong ties can in fact lead to faster or slower diffusion depending on the type of signals circulating in the network. We conclude that, even in presence of "complex contagions", dense local ties cannot be regarded as a sufficient condition for faster diffusion.

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Section: Resultsmentioning

confidence: 88%

Complex Contagions and the Diffusion of Innovations: Evidence from a Small-N Study

Manzo

Gabbriellini

Roux

et al. 2018

J Archaeol Method Theory

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“…Due to the focus on universal mechanisms and the interdisciplinarity of contributors also from outside of the traditional social sciences, computational social science represents an integrated approach to the social sciences, where the traditional social and behavioral sciences serve as different perspectives for modeling how people think (psychology), handle wealth (economics), relate to each other (sociology), govern themselves (political science), and create culture (anthropology) (Conte et al, 2012), or operate in geographical space (Torrens, 2010) to gain quantitative and qualitative insight about societal questions and real-world problems (cf. Watts, 2013;Keuschnigg et al, 2017). These aspects can be subsumed under the current, broad definition by Amaral (2017, p.…”

Section: The Rise Of Computational Social Sciencementioning

confidence: 99%

Computational Conflict Research

Deutschmann¹,

Lorenz²,

Nardin³

et al. 2020

Computational Social Sciences

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adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence and indicate if changes were made. The images or other third party material in this book are included in the book's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the book's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

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“…Being inspired by Complex Systems and its holistic and systemic perspective, they therefore understand a social group as an ecosystem, where actors interact and coevolve in a non-trivial manner. One of the many options to characterize social interactions (Keuschnigg et al, 2017) is to build experimental situations by means of the so-called Social Dilemmas, in the frame of the so-called "Game Theory". These dilemmas include a series of stylized interactive games where participants' individual interest is in conflict with collective interest thus allowing to infer social behavioural traits.…”

Section: Computational Social Science and Citizen Science Synergiesmentioning

confidence: 99%

Reformulating computational social science with citizen social science: the case of a community-based mental health care research

Bonhoure¹,

Cigarini²,

Vicens³

et al. 2019

Preprint

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“Citizen Social Science” is a fast-growing term within Citizen Science world but not many experiences have been shared in the literature to better shape its meaning. This article discusses novel possibilities of these participatory practices through the critical analysis of a concrete community-based project. We here embrace under the “Social” tag of Citizen Social Science both Computational Social Science methodologies and the Social concerns expressed by the mental health community. The interpretation place persons with a mental condition, as well as caregivers and relatives, at the center of the research cycle by taking the role of Competent Experts In-The-Field. A synergetic relation between Citizen Science, Mental Health research and Computational Social Science also imply a conceptual shift in comparison to standard approaches such as the inclusion of research subjects as active co-designers or the consideration of communitarian spaces as most natural experimental spaces. We here describe how these concepts are put into practice during the whole duration of a research project that has studied the social interactions inside the Community Mental Health Care ecosystem. Important steps entail the creation of a Knowledge Coalition, including a diversity of relevant actors with diverse knowledge and expertise, that is later involved in co-designing the research and in embedding experimental settings in communitarian spaces. The experience allows us to open a wider discussion on the possibilities and limitations of Citizen Social Science practices. Having in mind the ethical debate raised by Citizen Science Public Health and Patients’ driven research, we propose a set of values and practices to be agreed on. We also analyse the participation of the scientists in these kind of projects, which forces them to adopt the role of “camaleons” when executing diverse and versatile tasks. We additionally advocate for a more extended collective interpretation of the results in order to produce socially robust knowledge and enhance actions and policies grounded on these results. Exemplified with the experience herein presented, a more horizontal process that include the enhancement of participation and the revision of the notion of experiment offer new opportunities for Social Sciences from a multidisciplinary perspective.

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Analytical sociology and computational social science

Cited by 63 publications

References 67 publications

Complex Contagions and the Diffusion of Innovations: Evidence from a Small-N Study

Complex Contagions and the Diffusion of Innovations: Evidence from a Small-N Study

Computational Conflict Research

Reformulating computational social science with citizen social science: the case of a community-based mental health care research

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