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Ngoc Thanh Nguyen - One of the best experts on this subject based on the ideXlab platform.
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Computational Collective Intelligence - 11th International Conference, ICCCI 2019, Proceedings, Part I
2019Co-Authors: Ngoc Thanh Nguyen, Philippe Aniorte, Ernesto Expósito, Richard Chbeir, Bogdan TrawinskiAbstract:This two-volume set (LNAI 11683 and LNAI 11684) constitutes the refereed proceedings of the 11th International Conference on Computational Collective Intelligence, ICCCI 2019, held in Hendaye France, in September 2019.The 117 full papers presented were carefully reviewed and selected from 200 submissions. The papers are grouped in topical sections on: computational Collective Intelligence and natural language processing; machine learning in real-world data; distributed Collective Intelligence for smart manufacturing; Collective Intelligence for science and technology; intelligent management information systems; intelligent sustainable smart cities; new trends and challenges in education: the university 4.0; intelligent processing of multimedia in web systems; and big data streaming, applications and security.
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Computational Collective Intelligence - 11th International Conference, ICCCI 2019, Proceedings, Part II
2019Co-Authors: Ngoc Thanh Nguyen, Philippe Aniorte, Ernesto Expósito, Richard Chbeir, Bogdan TrawinskiAbstract:This two-volume set (LNAI 11683 and LNAI 11684) constitutes the refereed proceedings of the 11th International Conference on Computational Collective Intelligence, ICCCI 2019, held in Hendaye France, in September 2019.The 117 full papers presented were carefully reviewed and selected from 200 submissions. The papers are grouped in topical sections on: computational Collective Intelligence and natural language processing; machine learning in real-world data; distributed Collective Intelligence for smart manufacturing; Collective Intelligence for science and technology; intelligent management information systems; intelligent sustainable smart cities; new trends and challenges in education: the university 4.0; intelligent processing of multimedia in web systems; and big data streaming, applications and security.
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INISTA - Prediction markets as a vital part of Collective Intelligence
2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2017Co-Authors: Rafał Palak, Ngoc Thanh NguyenAbstract:Nowadays, Collective Intelligence becomes more and more popular. Despite its high usability, many aspects of Collective Intelligence stay unexplored. Many companies have recognized the potential of Collective Intelligence and have begun using it. Prediction markets are the real life implementation of Collective Intelligence. The fact that prediction markets outperform experts makes it a great tool for predicting the future. In this paper, we try to answer important questions that have to be asked before the creation of a prediction market e. g. “What factors influence the prediction market error and how could this be minimized?”. This paper treats the problems more broadly. Therefore, the areas of Collective Intelligence that have a strong influence on prediction markets are also included in the problem analysis.
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Transactions on Computational Collective Intelligence XXIII - Transactions on Computational Collective Intelligence XXIII
Lecture Notes in Computer Science, 2016Co-Authors: Ngoc Thanh Nguyen, Ryszard Kowalczyk, Jacek MercikAbstract:These transactions publish research in computer-based methods of computational Collective Intelligence (CCI) and their applications in a wide range of fields such as the semantic Web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of Intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational Intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other Collective Intelligence and to create new forms of CCI in natural and/or artificial systems. This twenty-third issue contains 14 carefully selected and revised contributions
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Transactions on Computational Collective Intelligence XVIII - Transactions on Computational Collective Intelligence XVIII
Lecture Notes in Computer Science, 2015Co-Authors: Ngoc Thanh NguyenAbstract:These transactions publish research in computer-based methods of computational Collective Intelligence (CCI) and their applications in a wide range of fields such as the semantic Web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of Intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational Intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other Collective Intelligence and to create new forms of CCI in natural and/or artificial systems. This eighteenth issue contains 9 carefully selected and revised contributions
Isabelle Boutron - One of the best experts on this subject based on the ideXlab platform.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence.
Journal of medical Internet research, 2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as "the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call." This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents' experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence. ©Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle Boutron. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 02.07.2019.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence.
Journal of medical Internet research, 2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:BACKGROUND Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as “the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call.” OBJECTIVE This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. METHODS We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. RESULTS A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents’ experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. CONCLUSIONS Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence (Preprint)
2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:BACKGROUND Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as “the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call.” OBJECTIVE This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. METHODS We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. RESULTS A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents’ experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. CONCLUSIONS Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence.
Van Thu Nguyen - One of the best experts on this subject based on the ideXlab platform.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence.
Journal of medical Internet research, 2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as "the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call." This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents' experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence. ©Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle Boutron. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 02.07.2019.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence.
Journal of medical Internet research, 2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:BACKGROUND Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as “the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call.” OBJECTIVE This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. METHODS We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. RESULTS A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents’ experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. CONCLUSIONS Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence.
Philippe Ravaud - One of the best experts on this subject based on the ideXlab platform.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence.
Journal of medical Internet research, 2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as "the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call." This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents' experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence. ©Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle Boutron. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 02.07.2019.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence.
Journal of medical Internet research, 2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:BACKGROUND Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as “the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call.” OBJECTIVE This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. METHODS We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. RESULTS A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents’ experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. CONCLUSIONS Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence (Preprint)
2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:BACKGROUND Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as “the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call.” OBJECTIVE This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. METHODS We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. RESULTS A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents’ experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. CONCLUSIONS Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence.
Bridget Young - One of the best experts on this subject based on the ideXlab platform.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence.
Journal of medical Internet research, 2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as "the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call." This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents' experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence. ©Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle Boutron. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 02.07.2019.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence.
Journal of medical Internet research, 2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:BACKGROUND Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as “the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call.” OBJECTIVE This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. METHODS We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. RESULTS A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents’ experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. CONCLUSIONS Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence.
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Overcoming Barriers to Mobilizing Collective Intelligence in Research: Qualitative Study of Researchers With Experience of Collective Intelligence (Preprint)
2019Co-Authors: Van Thu Nguyen, Bridget Young, Philippe Ravaud, Nivantha Naidoo, Mehdi Benchoufi, Isabelle BoutronAbstract:BACKGROUND Innovative ways of planning and conducting research have emerged recently, based on the concept of Collective Intelligence. Collective Intelligence is defined as shared Intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as “the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call.” OBJECTIVE This qualitative study aimed to identify the barriers to mobilizing Collective Intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting Collective Intelligence projects across different research disciplines. METHODS We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running Collective Intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. RESULTS A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing Collective Intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of Collective Intelligence projects. We drew on respondents’ experience to provide tips and good practice advice for governance, planning, and conducting Collective Intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage Collective Intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by Collective Intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. CONCLUSIONS Mobilizing Collective Intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of Collective Intelligence across different disciplines to overcome barriers to mobilizing Collective Intelligence.
