Using crowdsourced data for empirical research in information systems: What it is and how to do it safe?

Maya Daneva*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Industry-relevant information systems (IS) and software engineering (SE) research assumes practitioners' involvement, be it in the exploration of the state-of-the-art practice or in the investigation of real-life problems experienced in organizations. Crowdsourcing is an appealing concept for collecting practitioners' perceptions on an industry-relevant phenomenon that is of interest to researchers. As practitioners-generated contents are easily available in social media platforms such as practitioners' blogs or professional discussion groups in LinkedIn, researchers face the opportunity to use this crowdsourced information for the purpose of gaining understanding of a situation from the point of view of the professionals involved therein. While there are many benefits of using crowdsourcing for data collection, there are also challenges, all of which pose validity threats of various degrees to the empirical results obtained. This tutorial will provide a systematic understanding of the use of practitioners' crowdsourced data for empirical research purposes, and of the possible ways to safely apply it in IS and SE research. The tutorial leverages the tutor's experience and lessons learned from using practitioners' blogs articles for qualitative research in business-IT alignment and in large scale online games. At the end of the tutorial, attendees should be able to critically reason about (i) the possible choices in designing a crowdsourcing-based research process, (ii) the quality criteria for judging their research designs, and (iii) the criteria for evaluating their studies.

Original languageEnglish
Title of host publication2018 12th International Conference on Research Challenges in Information Science, RCIS 2018
Place of PublicationPiscataway, NJ
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)978-1-5386-6517-6
ISBN (Print)978-1-5386-6518-3
DOIs
Publication statusPublished - 6 Jul 2018
Event12th International Conference on Research Challenges in Information Science, RCIS 2018 - Nantes, France
Duration: 29 May 201831 May 2018
Conference number: 12
http://www.rcis-conf.com/rcis2018/

Publication series

NameProceedings International Conference on Research Challenges in Information Science (RCIS)
PublisherIEEE
Volume2018
ISSN (Print)2151-1357

Conference

Conference12th International Conference on Research Challenges in Information Science, RCIS 2018
Abbreviated titleRCIS
CountryFrance
CityNantes
Period29/05/1831/05/18
Internet address

Keywords

  • Big Data
  • Croudsourcing
  • Empirical Research Method
  • Qualitative Research
  • Validity Threats

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