Housing models that target rather typical family structures are increasingly failing to meet the needs of the new social changes regarding the rapid urbanization due to the mass-migration to cities, the lack of affordable housing, and the adoption of the sharing economy practices. As an architectural counterpart of the social dimension of sustainable development, co-living is introduced as a connected way of living, enabling sustainable living practices through efficient use of resources and space while sharing consumption. With respect to this, adapted collective residential units (namely informal co-living environments) come into use in places where affording a house becomes a challenging aspect and the conventional residential units do not reflect the transforming social demographics and economy. The reflection of the requirements of changing social and economic structures on urban settings can be seen in Turkish houses as well. This research, accordingly, focuses on co-living environments in Ankara, Turkey that were transformed from typical single-family residential units by its residents. Through investigating these co-living spaces, it is aimed to contribute to the current understanding of co-living practices, explore the spatial, economic and social underpinnings of these living models, and their relevance to the sustainable development while presenting initial findings regarding spatial use that can be of guidance for future co-living design processes.
This paper aims to improve the usability of qualitative urban big data sources by utilizing Natural Language Processing (NLP) as a promising AI-based technique. In this research, we designed a digital participation experiment by deploying an open-source and customizable asynchronous participation tool, "Consul Project", with 47 participants in the campus transformation process of the Singapore University of Technology and Design (SUTD). At the end of the data collection process with several debate topics and proposals, we analysed the qualitative data in entry scale, topic scale, and module scale. We investigated the impact of sentiment scores of each entry on the overall discussion and the sentiment scores of each introduction text on the ongoing discussions to trace the interaction and engagement. Furthermore, we used Latent Dirichlet Allocation (LDA) topic modelling to visualize the abstract topics that occurred in the participation experiment. The results revealed the links between different debates and proposals, which allow designers and decision makers to identify the most interacted arguments and engaging topics throughout participation processes. Eventually, this research presented the potentials of qualitative data while highlighting the necessity of adopting new methods and techniques, e.g., NLP, sentiment analysis, LDA topic modelling, to analyse and represent the collected qualitative data in asynchronous digital participation processes.
Data-driven urban design processes consist of iterative actions of many stakeholders, which require digital participatory approaches for collecting data from a high number of participants to make informed decisions. It is important to evaluate such processes to justify the necessary costs and efforts while continuously improving digital participation. Nevertheless, such evaluation remains a challenge due to the involvement of different stakeholders including participants, designers, and policymakers in decision-making processes, and the lack of a systematic method to generalize participation outputs that are mostly situated and context based. By addressing this challenge, this paper introduces a Multi-Criteria Decision Analysis (MCDA) based framework to measure the effectiveness and quality of digital participation systematically and quantitatively. To achieve such evaluation, we conducted a digital participation experiment and investigated such processes with the help of participants, designers, and policymakers from Singapore and Hamburg. By formulating this framework, we aim to reveal perspectives of different stakeholders towards digital participation and enable the evaluation and comparison of digital participation processes based on the introduced digital participation criteria.
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