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Patterns of User Participation and Contribution in Global Crowdsourcing: A Data Mining Study of Stack Overflow

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F22%3A92651" target="_blank" >RIV/60460709:41110/22:92651 - isvavai.cz</a>

  • Result on the web

    <a href="https://ceur-ws.org/Vol-3293/paper30.pdf" target="_blank" >https://ceur-ws.org/Vol-3293/paper30.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Patterns of User Participation and Contribution in Global Crowdsourcing: A Data Mining Study of Stack Overflow

  • Original language description

    Among many popular crowdsourcing platforms, the Question and Answer website Stack Overflow in Stack Exchange Network is used daily to share knowledge globally by millions of software professionals. Therefore, Stack Overflow data can reveal important patterns in global crowdsourcing beneficial for software industry. The aim of this study was to perform data mining on Stack Overflow data, to discover some of these patterns. Focus of this research was to analyze the global user distribution and contribution. Big data analytic techniques were used for data mining activities using Apache Spark with Python language. Oracle Data Visualization Desktop and scikit-learn python library were used for visualization. The results show that although majority of the users are from USA and India, the average contribution is higher in European countries.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 10th International Conference on Information and Communication Technologies in Agriculture, Food and Environment (HAICTA 2022)

  • ISBN

  • ISSN

    1613-0073

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    143-150

  • Publisher name

    CEUR Workshop Proceedings (CEUR-WS.org)

  • Place of publication

    Athens, Greece

  • Event location

    Athens, Greece

  • Event date

    Sep 22, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article