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\n  \n 2024\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n The influence of Automated Decision-Making systems in the context of street-level bureaucrats' practices.\n \n \n \n\n\n \n Portela, M.; Müller, A P. R.; and Tangi, L.\n\n\n \n\n\n\n . 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{portela_influence_2024,\n\ttitle = {The influence of {Automated} {Decision}-{Making} systems in the context of street-level bureaucrats' practices},\n\tcopyright = {All rights reserved},\n\tdoi = {arXiv:2407.19427},\n\tabstract = {In an era of digital governance, the use of automation for individual and cooperative work is increasing in public administrations (Tangi et al., 2022). Despite the promises of efficiency and cost reduction, automation could bring new challenges to the governance schemes. Regional, national, and local governments are taking measures to regulate and measure the impact of automated decision-making systems (ADMS). This research focuses on the use and adoption of ADMS in European public administrations to understand how these systems have been transforming the roles, tasks, and duties of street-level bureaucrats. We conducted a qualitative study in which we interviewed street-level bureaucrats from three administrations who had used an ADMS for several years, which was embedded in their daily work routines. The outcome of our research is an analysis of five dimensions of how collaborative work, the organizational settings, the capacities of bureaucrats and the implementation of the ADMS enable or limit the capacities for offering better services towards the citizens.},\n\tlanguage = {en},\n\tauthor = {Portela, Manuel and Müller, A Paula Rodriguez and Tangi, Luca},\n\tyear = {2024},\n}\n\n\n\n\n\n\n\n
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\n In an era of digital governance, the use of automation for individual and cooperative work is increasing in public administrations (Tangi et al., 2022). Despite the promises of efficiency and cost reduction, automation could bring new challenges to the governance schemes. Regional, national, and local governments are taking measures to regulate and measure the impact of automated decision-making systems (ADMS). This research focuses on the use and adoption of ADMS in European public administrations to understand how these systems have been transforming the roles, tasks, and duties of street-level bureaucrats. We conducted a qualitative study in which we interviewed street-level bureaucrats from three administrations who had used an ADMS for several years, which was embedded in their daily work routines. The outcome of our research is an analysis of five dimensions of how collaborative work, the organizational settings, the capacities of bureaucrats and the implementation of the ADMS enable or limit the capacities for offering better services towards the citizens.\n
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\n \n\n \n \n \n \n \n Addressing Challenges and Opportunities in Data Sharing for the Common Good: The Case of Europe’s First Data Altruism Organisation.\n \n \n \n\n\n \n Estivill-Castro, V.; Portela, M. P.; and Maccani, G.\n\n\n \n\n\n\n In Marrakech, Morocco, May 2024. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{estivill-castro_addressing_2024,\n\taddress = {Marrakech, Morocco},\n\ttitle = {Addressing {Challenges} and {Opportunities} in {Data} {Sharing} for the {Common} {Good}: {The} {Case} of {Europe}’s {First} {Data} {Altruism} {Organisation}},\n\tcopyright = {Licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC-BY-NC-SA)},\n\tabstract = {Smart-cities are heavily linked to decision-making based on data. However, despite the different waves of open data, those pertaining to the citizens themselves are not directly contributing to citizen participation and engagement. This is particularly true of the fine grained data regarding utilities consumption despite the huge potential to impact climate change. The common good that such data represents has raised debate about the schemes by which such data could be shared and what tools could empower those the data is about. DATALOG is a non-profit association aiming to facilitate data donation, sharing, and re-use for the common good and planetary well-being coordinated by Universitat Pompeu Fabra, with the collaboration of the innovation consultancy Ideas for Change. In 2023 it became the first data altruism organisation recognised by the European Union under the Data Governance Act. However, data altruism organisations as defined face several challenges. In this article we describe the process of creating DATALOG to collect consumption data from utilities (water, gas, electricity) in Barcelona. We reflect on the barriers and opportunities we faced during its creation as well as those challenges that we foresee in the near future. These lessons learnt will contribute to inspire new organizations and promote data sharing through the creation these new data intermediaries.},\n\tlanguage = {en},\n\tauthor = {Estivill-Castro, Vladimir and Portela, Manuel Portela and Maccani, Giovanni},\n\tmonth = may,\n\tyear = {2024},\n}\n\n\n\n\n\n\n\n
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\n Smart-cities are heavily linked to decision-making based on data. However, despite the different waves of open data, those pertaining to the citizens themselves are not directly contributing to citizen participation and engagement. This is particularly true of the fine grained data regarding utilities consumption despite the huge potential to impact climate change. The common good that such data represents has raised debate about the schemes by which such data could be shared and what tools could empower those the data is about. DATALOG is a non-profit association aiming to facilitate data donation, sharing, and re-use for the common good and planetary well-being coordinated by Universitat Pompeu Fabra, with the collaboration of the innovation consultancy Ideas for Change. In 2023 it became the first data altruism organisation recognised by the European Union under the Data Governance Act. However, data altruism organisations as defined face several challenges. In this article we describe the process of creating DATALOG to collect consumption data from utilities (water, gas, electricity) in Barcelona. We reflect on the barriers and opportunities we faced during its creation as well as those challenges that we foresee in the near future. These lessons learnt will contribute to inspire new organizations and promote data sharing through the creation these new data intermediaries.\n
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\n \n\n \n \n \n \n \n \n A Comparative User Study of Human Predictions in Algorithm-Supported Recidivism Risk Assessment.\n \n \n \n \n\n\n \n Portela, M.; Castillo, C.; Tolan, S.; Karimi-Haghighi, M.; and Pueyo, A. A.\n\n\n \n\n\n\n Artificial Intelligence and Law, 1(1). 2024.\n arXiv: 2201.11080 Publisher: Association for Computing Machinery ISBN: 9781450351003\n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{portela_comparative_2024,\n\ttitle = {A {Comparative} {User} {Study} of {Human} {Predictions} in {Algorithm}-{Supported} {Recidivism} {Risk} {Assessment}},\n\tvolume = {1},\n\turl = {http://arxiv.org/abs/2201.11080},\n\tdoi = {https://doi.org/ 10.1007/s10506-024-09393-y},\n\tabstract = {In this paper, we study the effects of using an algorithm-based risk assessment instrument to support the prediction of risk of criminalrecidivism. The instrument we use in our experiments is a machine learning version ofRiskEval(name changed for double-blindreview), which is the main risk assessment instrument used by the Justice Department ofCountry(omitted for double-blind review).The task is to predict whether a person who has been released from prison will commit a new crime, leading to re-incarceration,within the next two years. We measure, among other variables, the accuracy of human predictions with and without algorithmicsupport. This user study is done with (1)generalparticipants from diverse backgrounds recruited through a crowdsourcing platform,(2)targetedparticipants who are students and practitioners of data science, criminology, or social work and professionals who workwithRiskEval. Among other findings, we observe that algorithmic support systematically leads to more accurate predictions fromall participants, but that statistically significant gains are only seen in the performance of targeted participants with respect to thatof crowdsourced participants. We also run focus groups with participants of the targeted study to interpret the quantitative results,including people who useRiskEvalin a professional capacity. Among other comments, professional participants indicate that theywould not foresee using a fully-automated system in criminal risk assessment, but do consider it valuable for training, standardization,and to fine-tune or double-check their predictions on particularly difficult cases.},\n\tnumber = {1},\n\tjournal = {Artificial Intelligence and Law},\n\tauthor = {Portela, Manuel and Castillo, Carlos and Tolan, SongÜl and Karimi-Haghighi, Marzieh and Pueyo, Antonio Andres},\n\tyear = {2024},\n\tnote = {arXiv: 2201.11080\nPublisher: Association for Computing Machinery\nISBN: 9781450351003},\n}\n\n\n\n
\n
\n\n\n
\n In this paper, we study the effects of using an algorithm-based risk assessment instrument to support the prediction of risk of criminalrecidivism. The instrument we use in our experiments is a machine learning version ofRiskEval(name changed for double-blindreview), which is the main risk assessment instrument used by the Justice Department ofCountry(omitted for double-blind review).The task is to predict whether a person who has been released from prison will commit a new crime, leading to re-incarceration,within the next two years. We measure, among other variables, the accuracy of human predictions with and without algorithmicsupport. This user study is done with (1)generalparticipants from diverse backgrounds recruited through a crowdsourcing platform,(2)targetedparticipants who are students and practitioners of data science, criminology, or social work and professionals who workwithRiskEval. Among other findings, we observe that algorithmic support systematically leads to more accurate predictions fromall participants, but that statistically significant gains are only seen in the performance of targeted participants with respect to thatof crowdsourced participants. We also run focus groups with participants of the targeted study to interpret the quantitative results,including people who useRiskEvalin a professional capacity. Among other comments, professional participants indicate that theywould not foresee using a fully-automated system in criminal risk assessment, but do consider it valuable for training, standardization,and to fine-tune or double-check their predictions on particularly difficult cases.\n
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\n  \n 2023\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Citizen Engagement in Urban Data Initiatives: Approaches, Challenges and Recommendations.\n \n \n \n \n\n\n \n Chignard, S.; Micheli, M.; Portela, M.; and Boettcher, P.\n\n\n \n\n\n\n Human rights in the digital era - UNHABITAT. 2023.\n \n\n\n\n
\n\n\n\n \n \n \"CitizenPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{chignard_citizen_2023,\n\ttitle = {Citizen {Engagement} in {Urban} {Data} {Initiatives}: {Approaches}, {Challenges} and {Recommendations}},\n\tcopyright = {United Nations Human Settlements Programme (UN-Habitat)},\n\turl = {https://unhabitat.org/human-rights-in-the-digital-era-learnings-on-local-governance-from-pilots-in-europe},\n\tjournal = {Human rights in the digital era - UNHABITAT},\n\tauthor = {Chignard, Simon and Micheli, Marina and Portela, Manuel and Boettcher, Paul},\n\tyear = {2023},\n}\n\n\n\n
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\n  \n 2022\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Human Response to an AI-Based Decision Support System: A User Study on the Effects of Accuracy and Bias.\n \n \n \n \n\n\n \n Solans, D.; Beretta, A.; Portela, M.; Castillo, C.; and Monreale, A.\n\n\n \n\n\n\n In volume 1, 2022. \n arXiv: 2203.15514 Publication Title: Proceedings of ACM Conference (Conference'17) Issue: 1\n\n\n\n
\n\n\n\n \n \n \"HumanPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{solans_human_2022,\n\ttitle = {Human {Response} to an {AI}-{Based} {Decision} {Support} {System}: {A} {User} {Study} on the {Effects} of {Accuracy} and {Bias}},\n\tvolume = {1},\n\turl = {http://arxiv.org/abs/2203.15514},\n\tdoi = {https://doi.org/10.48550/arXiv.2203.15514},\n\tabstract = {Artificial Intelligence (AI) is increasingly used to build Decision Support Systems (DSS) across many domains. This paper describes a series of experiments designed to observe human response to different characteristics of a DSS such as accuracy and bias, particularly the extent to which participants rely on the DSS, and the performance they achieve. In our experiments, participants play a simple online game inspired by so-called "wildcat" (i.e., exploratory) drilling for oil. The landscape has two layers: a visible layer describing the costs (terrain), and a hidden layer describing the reward (oil yield). Participants in the control group play the game without receiving any assistance, while in treatment groups they are assisted by a DSS suggesting places to drill. For certain treatments, the DSS does not consider costs, but only rewards, which introduces a bias that is observable by users. Between subjects, we vary the accuracy and bias of the DSS, and observe the participants' total score, time to completion, the extent to which they follow or ignore suggestions. We also measure the acceptability of the DSS in an exit survey. Our results show that participants tend to score better with the DSS, that the score increase is due to users following the DSS advice, and related to the difficulty of the game and the accuracy of the DSS. We observe that this setting elicits mostly rational behavior from participants, who place a moderate amount of trust in the DSS and show neither algorithmic aversion (under-reliance) nor automation bias (over-reliance).However, their stated willingness to accept the DSS in the exit survey seems less sensitive to the accuracy of the DSS than their behavior, suggesting that users are only partially aware of the (lack of) accuracy of the DSS.},\n\tauthor = {Solans, David and Beretta, Andrea and Portela, Manuel and Castillo, Carlos and Monreale, Anna},\n\tyear = {2022},\n\tnote = {arXiv: 2203.15514\nPublication Title: Proceedings of ACM Conference (Conference'17)\nIssue: 1},\n}\n\n\n\n
\n
\n\n\n
\n Artificial Intelligence (AI) is increasingly used to build Decision Support Systems (DSS) across many domains. This paper describes a series of experiments designed to observe human response to different characteristics of a DSS such as accuracy and bias, particularly the extent to which participants rely on the DSS, and the performance they achieve. In our experiments, participants play a simple online game inspired by so-called \"wildcat\" (i.e., exploratory) drilling for oil. The landscape has two layers: a visible layer describing the costs (terrain), and a hidden layer describing the reward (oil yield). Participants in the control group play the game without receiving any assistance, while in treatment groups they are assisted by a DSS suggesting places to drill. For certain treatments, the DSS does not consider costs, but only rewards, which introduces a bias that is observable by users. Between subjects, we vary the accuracy and bias of the DSS, and observe the participants' total score, time to completion, the extent to which they follow or ignore suggestions. We also measure the acceptability of the DSS in an exit survey. Our results show that participants tend to score better with the DSS, that the score increase is due to users following the DSS advice, and related to the difficulty of the game and the accuracy of the DSS. We observe that this setting elicits mostly rational behavior from participants, who place a moderate amount of trust in the DSS and show neither algorithmic aversion (under-reliance) nor automation bias (over-reliance).However, their stated willingness to accept the DSS in the exit survey seems less sensitive to the accuracy of the DSS than their behavior, suggesting that users are only partially aware of the (lack of) accuracy of the DSS.\n
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\n \n\n \n \n \n \n \n \n Towards Meaningful Oversight of Automated Decision Making Systems.\n \n \n \n \n\n\n \n Portela, M.; and Alvarez, T.\n\n\n \n\n\n\n 2022.\n \n\n\n\n
\n\n\n\n \n \n \"TowardsPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@misc{portela_towards_2022,\n\ttitle = {Towards {Meaningful} {Oversight} of {Automated} {Decision} {Making} {Systems}},\n\tcopyright = {Licencia Creative Commons Atribución-CompartirIgual 4.0 Internacional (CC-BY-SA)},\n\turl = {https://digitalfuturesociety.com/report/towards-a-meaningful-human-oversight-of-automated-decision-making-systems/},\n\tpublisher = {Digital Future Society Think Tank},\n\tauthor = {Portela, Manuel and Alvarez, Tanya},\n\tyear = {2022},\n}\n\n\n\n\n\n\n\n
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\n  \n 2021\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Interfacing participation in citizen science projects with conversational agents.\n \n \n \n \n\n\n \n Portela, M.\n\n\n \n\n\n\n Human Computation Journal, 8(2): 33–53. July 2021.\n \n\n\n\n
\n\n\n\n \n \n \"InterfacingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{Portela2021,\n\ttitle = {Interfacing participation in citizen science projects with conversational agents},\n\tvolume = {8},\n\tissn = {2330-8001},\n\turl = {https://hcjournal.org/index.php/jhc/article/view/114},\n\tdoi = {10.15346/hc.v8i2.114},\n\tabstract = {This paper assesses the use of conversational agents (chatbots) as an interface to enhance communication with participants in citizen science projects. After developing a study of the engagement and motivations to interact with chatbots, we explored our results. We based our analysis on the current needs exposed in citizen science literature to assess the opportunities. We found that chatbots are great communication platforms that can help to engage participants as an all-in-one interface. Chatbots can benefit projects in reducing the need for developing an exclusive app while it can be deployed on several platforms. Finally, we establish design suggestions to help citizen science practitioners to incorporate such platforms to new projects. We encourage the development of more advanced interfaces through the incorporation of Machine Learning to several processes.},\n\tnumber = {2},\n\tjournal = {Human Computation Journal},\n\tauthor = {Portela, Manuel},\n\tmonth = jul,\n\tyear = {2021},\n\tpages = {33--53},\n}\n\n\n\n
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\n This paper assesses the use of conversational agents (chatbots) as an interface to enhance communication with participants in citizen science projects. After developing a study of the engagement and motivations to interact with chatbots, we explored our results. We based our analysis on the current needs exposed in citizen science literature to assess the opportunities. We found that chatbots are great communication platforms that can help to engage participants as an all-in-one interface. Chatbots can benefit projects in reducing the need for developing an exclusive app while it can be deployed on several platforms. Finally, we establish design suggestions to help citizen science practitioners to incorporate such platforms to new projects. We encourage the development of more advanced interfaces through the incorporation of Machine Learning to several processes.\n
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\n \n\n \n \n \n \n \n Affective Technology, Enchanting Spaces and Cultivating Places.\n \n \n \n\n\n \n Portela, M.; and Granell-Canut, C.\n\n\n \n\n\n\n In Aurigi, A.; and Odendaal, N., editor(s), Shaping Smart for Better Cities, Rethinking and Shaping Relationships between Urban Space and Digital Technologies, pages 157–176. Academic Press, 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@incollection{Portela2020,\n\ttitle = {Affective {Technology}, {Enchanting} {Spaces} and {Cultivating} {Places}},\n\tisbn = {978-0-12-818636-7},\n\tbooktitle = {Shaping {Smart} for {Better} {Cities}, {Rethinking} and {Shaping} {Relationships} between {Urban} {Space} and {Digital} {Technologies}},\n\tpublisher = {Academic Press},\n\tauthor = {Portela, Manuel and Granell-Canut, Carlos},\n\teditor = {Aurigi, Alessandro and Odendaal, Nancy},\n\tyear = {2020},\n\tdoi = {10.1016/C2018-0-04503-X},\n\tpages = {157--176},\n}\n\n\n\n
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\n \n\n \n \n \n \n \n \n Citizen science in the social sciences and humanities: the power of interdisciplinarity.\n \n \n \n \n\n\n \n Tauginienė, L.; Butkevičienė, E.; Vohland, K.; Heinisch, B.; Daskolia, M.; Suškevičs, M.; Portela, M.; Balázs, B.; and Prūse, B.\n\n\n \n\n\n\n Palgrave Communications, 6(1): 89. December 2020.\n \n\n\n\n
\n\n\n\n \n \n \"CitizenPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{Tauginiene2020,\n\ttitle = {Citizen science in the social sciences and humanities: the power of interdisciplinarity},\n\tvolume = {6},\n\tissn = {2055-1045},\n\turl = {http://www.nature.com/articles/s41599-020-0471-y},\n\tdoi = {10.1057/s41599-020-0471-y},\n\tnumber = {1},\n\tjournal = {Palgrave Communications},\n\tauthor = {Tauginienė, Loreta and Butkevičienė, Eglė and Vohland, Katrin and Heinisch, Barbara and Daskolia, Maria and Suškevičs, Monika and Portela, Manuel and Balázs, Bálint and Prūse, Baiba},\n\tmonth = dec,\n\tyear = {2020},\n\tpages = {89},\n}\n\n\n\n
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\n  \n 2018\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Geographies of Empathy: Affective reconfigurations of Cities, Objects & Places.\n \n \n \n \n\n\n \n Portela, M.\n\n\n \n\n\n\n Ph.D. Thesis, Universitat Jaume I, Castelló de la Plana, November 2018.\n \n\n\n\n
\n\n\n\n \n \n \"GeographiesPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@phdthesis{Portela2018,\n\taddress = {Castelló de la Plana},\n\ttitle = {Geographies of {Empathy}: {Affective} reconfigurations of {Cities}, {Objects} \\& {Places}},\n\turl = {http://hdl.handle.net/10803/664137},\n\tschool = {Universitat Jaume I},\n\tauthor = {Portela, Manuel},\n\tmonth = nov,\n\tyear = {2018},\n\tdoi = {10.6035/14123.2018.683892},\n}\n\n\n\n
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\n \n\n \n \n \n \n \n \n Looking for “ in-between ” Places.\n \n \n \n \n\n\n \n Portela, M.; Acedo, A.; and Granell-canut, C.\n\n\n \n\n\n\n Media Theory Journal, 2(1): 108–133. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"LookingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{Portela2018,\n\ttitle = {Looking for “ in-between ” {Places}},\n\tvolume = {2},\n\turl = {http://mediatheoryjournal.org/portela-et-al-looking-for-in-between-places/},\n\tnumber = {1},\n\tjournal = {Media Theory Journal},\n\tauthor = {Portela, Manuel and Acedo, Albert and Granell-canut, Carlos},\n\tyear = {2018},\n\tpages = {108--133},\n}\n\n\n\n\n\n\n\n
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\n  \n 2017\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n A new friend in our Smartphone ? Observing Interactions with Chatbots in the search of emotional engagement.\n \n \n \n\n\n \n Portela, M.; and Granell-canut, C.\n\n\n \n\n\n\n In Proceedings of Interacción ’17, 2017. \n \n\n\n\n
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@inproceedings{Portela2017,\n\ttitle = {A new friend in our {Smartphone} ? {Observing} {Interactions} with {Chatbots} in the search of emotional engagement},\n\tisbn = {978-1-4503-5229-1},\n\tdoi = {10.1145/3123818.3123826},\n\tbooktitle = {Proceedings of {Interacción} ’17},\n\tauthor = {Portela, Manuel and Granell-canut, Carlos},\n\tyear = {2017},\n}\n\n\n\n
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\n \n\n \n \n \n \n \n A call to De-Familiarize with Everyday Objects: Understanding Modes of Ordering and Politics of Interaction.\n \n \n \n\n\n \n Portela, M.; and Granell-Canut, C.\n\n\n \n\n\n\n 8th International conference on Communities and Technologies 2017 conference, Doctoral Consortium. Troyes, France, 26 June 2017. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{PortelaEmpathy2017,\n\ttitle = {A call to {De}-{Familiarize} with {Everyday} {Objects}: {Understanding} {Modes} of {Ordering} and {Politics} of {Interaction}},\n\tjournal = {8th International conference on Communities and Technologies 2017 conference, Doctoral Consortium. Troyes, France, 26 June 2017},\n\tauthor = {Portela, Manuel and Granell-Canut, Carlos},\n\tyear = {2017},\n}\n\n\n\n
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\n \n\n \n \n \n \n \n \n Interfaces tecno-urbanas. Un análisis crítico sobre los retos socio-técnicos de las representaciones del espacio urbano.\n \n \n \n \n\n\n \n Portela, M.\n\n\n \n\n\n\n Ph.D. Thesis, Universidad Nacional General Sarmiento, 2017.\n \n\n\n\n
\n\n\n\n \n \n \"InterfacesPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@phdthesis{manuel_portela_2017_1122631,\n\ttitle = {Interfaces tecno-urbanas. {Un} análisis crítico sobre los retos socio-técnicos de las representaciones del espacio urbano.},\n\turl = {https://doi.org/10.5281/zenodo.1122631},\n\tschool = {Universidad Nacional General Sarmiento},\n\tauthor = {Portela, Manuel},\n\tyear = {2017},\n\tdoi = {10.5281/zenodo.1122631},\n}\n\n\n\n
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\n \n\n \n \n \n \n \n \n The role of Participatory Social Mapping in the struggle of the territory and the right to the city.\n \n \n \n \n\n\n \n Portela, M.; and Errandonea, L. P.\n\n\n \n\n\n\n In Proceedings of the 8th International Conference on Communities and Technologies - C&T '17, pages 100–104, New York, New York, USA, 2017. ACM Press\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{Portela2017a,\n\taddress = {New York, New York, USA},\n\ttitle = {The role of {Participatory} {Social} {Mapping} in the struggle of the territory and the right to the city},\n\tisbn = {978-1-4503-4854-6},\n\turl = {http://dl.acm.org/citation.cfm?doid=3083671.3083676},\n\tdoi = {10.1145/3083671.3083676},\n\tbooktitle = {Proceedings of the 8th {International} {Conference} on {Communities} and {Technologies} - {C}\\&{T} '17},\n\tpublisher = {ACM Press},\n\tauthor = {Portela, Manuel and Errandonea, Lucía Paz},\n\tyear = {2017},\n\tpages = {100--104},\n}\n
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\n  \n 2016\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Methods to Observe and Evaluate Interactions with Everyday Context-Aware Objects.\n \n \n \n \n\n\n \n Portela, M.; and Granell-Canut, C.\n\n\n \n\n\n\n In Ubiquitous Computing and Ambient Intelligence, pages 385–392, 2016. Springer\n Issue: 1\n\n\n\n
\n\n\n\n \n \n \"MethodsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{Portela2016,\n\ttitle = {Methods to {Observe} and {Evaluate} {Interactions} with {Everyday} {Context}-{Aware} {Objects}},\n\turl = {http://www.springer.com/us/book/9783319487458},\n\tdoi = {10.1007/978-3-319-48746-5_39},\n\tbooktitle = {Ubiquitous {Computing} and {Ambient} {Intelligence}},\n\tpublisher = {Springer},\n\tauthor = {Portela, Manuel and Granell-Canut, Carlos},\n\tyear = {2016},\n\tnote = {Issue: 1},\n\tpages = {385--392},\n}\n\n\n\n\n\n\n\n
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