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

Kód výsledku v 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>

Výsledek na webu

<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

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

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

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

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

ISBN

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ISSN

1613-0073

e-ISSN

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Počet stran výsledku

8

Strana od-do

143-150

Název nakladatele

CEUR Workshop Proceedings (CEUR-WS.org)

Místo vydání

Athens, Greece

Místo konání akce

Athens, Greece

Datum konání akce

22. 9. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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