Approach For Investigating Crowdfunding Campaigns With Platform Data: Case Indiegogo

Jukka Huhtamäki, Lester Lasrado, Karan Menon, Hannu Kärkkäinen, Jari Jussila

    Publikation: Kapitel i bog/rapport/konferenceprocesKonferencebidrag i proceedingsForskningpeer review

    Resumé

    Crowdfunding via the internet is a relatively new phenomenon in research and gaining momentum currently. While taking a data-driven approach into investigating the properties and dynamics of crowdfunding campaigns would allow the use of computational social science in investigations on crowdfunding, existing data-driven research on crowdfunding remains very limited. This is particularly true on the level of individual funder data. In this study, we contribute to the empirical body of knowledge on crowdfunding by introducing Indiegogo as a data source and, more specifically, the development and implementation of a crawler and scraper for accessing Indiegogo campaign data, and sharing this openly for other researchers. Due to the extremely dynamic and rapidly increasing amount of crowdfunding data in terms of the number of crowdfunding campaigns and the available investment and individual investor data, we believe our approach is useful for supporting public and open data-driven research, instead of providing merely a static data set.
    Crowdfunding via the internet is a relatively new phenomenon in research and gaining momentum currently. While taking a data-driven approach into investigating the properties and dynamics of crowdfunding campaigns would allow the use of computational social science in investigations on crowdfunding, existing data-driven research on crowdfunding remains very limited. This is particularly true on the level of individual funder data. In this study, we contribute to the empirical body of knowledge on crowdfunding by introducing Indiegogo as a data source and, more specifically, the development and implementation of a crawler and scraper for accessing Indiegogo campaign data, and sharing this openly for other researchers. Due to the extremely dynamic and rapidly increasing amount of crowdfunding data in terms of the number of crowdfunding campaigns and the available investment and individual investor data, we believe our approach is useful for supporting public and open data-driven research, instead of providing merely a static data set.
    SprogEngelsk
    TitelProceedings of the 19th International Academic Mindtrek Conference : Academic MindTrek '15
    RedaktørerMarkku Turunen
    Udgivelses stedNew York
    ForlagAssociation for Computing Machinery
    Dato2015
    Sider183-190
    ISBN (Trykt)978145039483
    DOI
    StatusUdgivet - 2015
    Begivenhed19th Academic Mindtrek Conference 2015 - Solo Sokos Hotel, Tampere, Finland
    Varighed: 22 sep. 201524 sep. 2015
    Konferencens nummer: 19
    http://mindtrek.tietovisio.com/

    Konference

    Konference19th Academic Mindtrek Conference 2015
    Nummer19
    LokationSolo Sokos Hotel
    LandFinland
    ByTampere
    Periode22/09/201524/09/2015
    Internetadresse

    Emneord

    • Crowdfunding
    • Data extraction
    • Indiegogo
    • Entrepreneur
    • Crawling
    • Scraping
    • Computational social science

    Citer dette

    Huhtamäki, J., Lasrado, L., Menon, K., Kärkkäinen, H., & Jussila, J. (2015). Approach For Investigating Crowdfunding Campaigns With Platform Data: Case Indiegogo. I M. Turunen (red.), Proceedings of the 19th International Academic Mindtrek Conference: Academic MindTrek '15 (s. 183-190). New York: Association for Computing Machinery. DOI: 10.1145/2818187.2818289
    Huhtamäki, Jukka ; Lasrado, Lester ; Menon, Karan ; Kärkkäinen, Hannu ; Jussila, Jari. / Approach For Investigating Crowdfunding Campaigns With Platform Data : Case Indiegogo. Proceedings of the 19th International Academic Mindtrek Conference: Academic MindTrek '15. red. / Markku Turunen. New York : Association for Computing Machinery, 2015. s. 183-190
    @inproceedings{06b3a133f39b4974a7058f5c4d1b0a1e,
    title = "Approach For Investigating Crowdfunding Campaigns With Platform Data: Case Indiegogo",
    abstract = "Crowdfunding via the internet is a relatively new phenomenon in research and gaining momentum currently. While taking a data-driven approach into investigating the properties and dynamics of crowdfunding campaigns would allow the use of computational social science in investigations on crowdfunding, existing data-driven research on crowdfunding remains very limited. This is particularly true on the level of individual funder data. In this study, we contribute to the empirical body of knowledge on crowdfunding by introducing Indiegogo as a data source and, more specifically, the development and implementation of a crawler and scraper for accessing Indiegogo campaign data, and sharing this openly for other researchers. Due to the extremely dynamic and rapidly increasing amount of crowdfunding data in terms of the number of crowdfunding campaigns and the available investment and individual investor data, we believe our approach is useful for supporting public and open data-driven research, instead of providing merely a static data set.",
    keywords = "Crowdfunding, Data extraction, Indiegogo, Entrepreneur, Crawling, Scraping, Computational social science, Crowdfunding, Data extraction, Indiegogo, Entrepreneur, Crawling, Scraping, Computational social science",
    author = "Jukka Huhtam{\"a}ki and Lester Lasrado and Karan Menon and Hannu K{\"a}rkk{\"a}inen and Jari Jussila",
    year = "2015",
    doi = "10.1145/2818187.2818289",
    language = "English",
    isbn = "978145039483",
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    Huhtamäki, J, Lasrado, L, Menon, K, Kärkkäinen, H & Jussila, J 2015, Approach For Investigating Crowdfunding Campaigns With Platform Data: Case Indiegogo. i M Turunen (red.), Proceedings of the 19th International Academic Mindtrek Conference: Academic MindTrek '15. Association for Computing Machinery, New York, s. 183-190, 19th Academic Mindtrek Conference 2015, Tampere, Finland, 22/09/2015. DOI: 10.1145/2818187.2818289

    Approach For Investigating Crowdfunding Campaigns With Platform Data : Case Indiegogo. / Huhtamäki, Jukka; Lasrado, Lester; Menon, Karan; Kärkkäinen, Hannu ; Jussila, Jari.

    Proceedings of the 19th International Academic Mindtrek Conference: Academic MindTrek '15. red. / Markku Turunen. New York : Association for Computing Machinery, 2015. s. 183-190.

    Publikation: Kapitel i bog/rapport/konferenceprocesKonferencebidrag i proceedingsForskningpeer review

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    AU - Huhtamäki,Jukka

    AU - Lasrado,Lester

    AU - Menon,Karan

    AU - Kärkkäinen,Hannu

    AU - Jussila,Jari

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    AB - Crowdfunding via the internet is a relatively new phenomenon in research and gaining momentum currently. While taking a data-driven approach into investigating the properties and dynamics of crowdfunding campaigns would allow the use of computational social science in investigations on crowdfunding, existing data-driven research on crowdfunding remains very limited. This is particularly true on the level of individual funder data. In this study, we contribute to the empirical body of knowledge on crowdfunding by introducing Indiegogo as a data source and, more specifically, the development and implementation of a crawler and scraper for accessing Indiegogo campaign data, and sharing this openly for other researchers. Due to the extremely dynamic and rapidly increasing amount of crowdfunding data in terms of the number of crowdfunding campaigns and the available investment and individual investor data, we believe our approach is useful for supporting public and open data-driven research, instead of providing merely a static data set.

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    KW - Entrepreneur

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    M3 - Article in proceedings

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    BT - Proceedings of the 19th International Academic Mindtrek Conference

    PB - Association for Computing Machinery

    CY - New York

    ER -

    Huhtamäki J, Lasrado L, Menon K, Kärkkäinen H, Jussila J. Approach For Investigating Crowdfunding Campaigns With Platform Data: Case Indiegogo. I Turunen M, red., Proceedings of the 19th International Academic Mindtrek Conference: Academic MindTrek '15. New York: Association for Computing Machinery. 2015. s. 183-190. Tilgængelig fra, DOI: 10.1145/2818187.2818289