IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v25y2014i4p669-689.html
   My bibliography  Save this article

The IQ of the Crowd: Understanding and Improving Information Quality in Structured User-Generated Content

Author

Listed:
  • Roman Lukyanenko

    (College of Business, Florida International University, Miami, Florida 33199)

  • Jeffrey Parsons

    (Faculty of Business Administration, Memorial University of Newfoundland, St. John’s, Newfoundland A1B 3X5 Canada)

  • Yolanda F. Wiersma

    (Department of Biology, Memorial University of Newfoundland, St. John’s, Newfoundland A1B 3X5 Canada)

Abstract

User-generated content (UGC) is becoming a valuable organizational resource, as it is seen in many cases as a way to make more information available for analysis. To make effective use of UGC, it is necessary to understand information quality (IQ) in this setting. Traditional IQ research focuses on corporate data and views users as data consumers. However, as users with varying levels of expertise contribute information in an open setting, current conceptualizations of IQ break down. In particular, the practice of modeling information requirements in terms of fixed classes, such as an Entity-Relationship diagram or relational database tables, unnecessarily restricts the IQ of user-generated data sets. This paper defines crowd information quality (crowd IQ), empirically examines implications of class-based modeling approaches for crowd IQ, and offers a path for improving crowd IQ using instance-and-attribute based modeling. To evaluate the impact of modeling decisions on IQ, we conducted three experiments. Results demonstrate that information accuracy depends on the classes used to model domains, with participants providing more accurate information when classifying phenomena at a more general level. In addition, we found greater overall accuracy when participants could provide free-form data compared to a condition in which they selected from constrained choices. We further demonstrate that, relative to attribute-based data collection, information loss occurs when class-based models are used. Our findings have significant implications for information quality, information modeling, and UGC research and practice.

Suggested Citation

  • Roman Lukyanenko & Jeffrey Parsons & Yolanda F. Wiersma, 2014. "The IQ of the Crowd: Understanding and Improving Information Quality in Structured User-Generated Content," Information Systems Research, INFORMS, vol. 25(4), pages 669-689, December.
    • Handle: RePEc:inm:orisre:v:25:y:2014:i:4:p:669-689
    DOI: 10.1287/isre.2014.0537
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.2014.0537
    Download Restriction: no
    File URL: https://libkey.io/10.1287/isre.2014.0537?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Donald P. Ballou & Harold L. Pazer, 1985. "Modeling Data and Process Quality in Multi-Input, Multi-Output Information Systems," Management Science, INFORMS, vol. 31(2), pages 150-162, February.
    2. Vivek Choudhury, 1997. "Strategic Choices in the Development of Interorganizational Information Systems," Information Systems Research, INFORMS, vol. 8(1), pages 1-24, March.
    3. Hongwei Zhu & Harris Wu, 2011. "Quality of data standards: framework and illustration using XBRL taxonomy and instances," Electronic Markets, Springer;IIM University of St. Gallen, vol. 21(2), pages 129-139, June.
    4. Jonathan Silvertown, 2010. "Taxonomy: include social networking," Nature, Nature, vol. 467(7317), pages 788-788, October.
    5. Anjana Susarla & Jeong-Ha Oh & Yong Tan, 2012. "Social Networks and the Diffusion of User-Generated Content: Evidence from YouTube," Information Systems Research, INFORMS, vol. 23(1), pages 23-41, March.
    6. Jeffrey Parsons & Roman Lukyanenko & Yolanda Wiersma, 2011. "Easier citizen science is better," Nature, Nature, vol. 471(7336), pages 37-37, March.
    7. Ron Weber, 1996. "Are Attributes Entities? A Study of Database Designers' Memory Structures," Information Systems Research, INFORMS, vol. 7(2), pages 137-162, June.
    8. Jeffrey Parsons, 1996. "An Information Model Based on Classification Theory," Management Science, INFORMS, vol. 42(10), pages 1437-1453, October.
    9. Richard O. Mason & Ian I. Mitroff, 1973. "A Program for Research on Management Information Systems," Management Science, INFORMS, vol. 19(5), pages 475-487, January.
    10. Andrew Burton-Jones & Peter N. Meso, 2006. "Conceptualizing Systems for Understanding: An Empirical Test of Decomposition Principles in Object-Oriented Analysis," Information Systems Research, INFORMS, vol. 17(1), pages 38-60, March.
    11. Yair Wand & Ron Weber, 2002. "Research Commentary: Information Systems and Conceptual Modeling—A Research Agenda," Information Systems Research, INFORMS, vol. 13(4), pages 363-376, December.
    12. Mordechai Haklay, 2010. "How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets," Environment and Planning B, , vol. 37(4), pages 682-703, August.
    13. Donald P. Ballou & Harold L. Pazer, 1995. "Designing Information Systems to Optimize the Accuracy-Timeliness Tradeoff," Information Systems Research, INFORMS, vol. 6(1), pages 51-72, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Xi & Zhao, Quanwu & Sun, Heshan, 2022. "Seekers’ complaint behavior in crowdsourcing: An uncertainty perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    2. Yu-Kai Lin & Arun Rai & Yukun Yang, 2022. "Information Control for Creator Brand Management in Subscription-Based Crowdfunding," Information Systems Research, INFORMS, vol. 33(3), pages 846-866, September.
    3. Lorenz Graf-Vlachy & Tarun Goyal & Yannick Ouardi & Andreas König, 2021. "Reviews Left and Right: The Link Between Reviewers’ Political Ideology and Online Review Language," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(4), pages 403-417, August.
    4. Roman Lukyanenko & Andrea Wiggins & Holly K. Rosser, 0. "Citizen Science: An Information Quality Research Frontier," Information Systems Frontiers, Springer, vol. 0, pages 1-23.
    5. Aladwani, Adel M. & Dwivedi, Yogesh K., 2018. "Towards a theory of SocioCitizenry: Quality anticipation, trust configuration, and approved adaptation of governmental social media," International Journal of Information Management, Elsevier, vol. 43(C), pages 261-272.
    6. Minh-Tri Ha & Giang-Do Nguyen & Thi Huong-Thanh Nguyen & Bich-Duyen Nguyen, 2023. "The use of dietary supplements and vitamin consumption during and after the Covid pandemic in Vietnam: a perspective of user-generated content," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    7. Aladwani, Adel M., 2017. "Compatible quality of social media content: Conceptualization, measurement, and affordances," International Journal of Information Management, Elsevier, vol. 37(6), pages 576-582.
    8. Lala Hajibayova, 2020. "(Un)theorizing citizen science: Investigation of theories applied to citizen science studies," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(8), pages 916-926, August.
    9. Hu, Xin & He, Liuyi & Liu, Junjun, 2022. "The power of beauty: Be your ideal self in online reviews—an empirical study based on face detection," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    10. Lala Hajibayova & L. P. Coladangelo & Heather A. Soyka, 2021. "Exploring the invisible college of citizen science: questions, methods and contributions," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6989-7003, August.
    11. Yan Song & Xin Tian, 2020. "Managerial Responses and Customer Engagement in Crowdfunding," Sustainability, MDPI, vol. 12(8), pages 1-13, April.
    12. Kawaljeet Kaur Kapoor & Kuttimani Tamilmani & Nripendra P. Rana & Pushp Patil & Yogesh K. Dwivedi & Sridhar Nerur, 2018. "Advances in Social Media Research: Past, Present and Future," Information Systems Frontiers, Springer, vol. 20(3), pages 531-558, June.
    13. Geng, Yuedan & Ye, Qiang & Jin, Yu & Shi, Wen, 2022. "Crowd wisdom and internet searches: What happens when investors search for stocks?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    14. Roman Lukyanenko & Andrea Wiggins & Holly K. Rosser, 2020. "Citizen Science: An Information Quality Research Frontier," Information Systems Frontiers, Springer, vol. 22(4), pages 961-983, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Roman Lukyanenko & Andrea Wiggins & Holly K. Rosser, 0. "Citizen Science: An Information Quality Research Frontier," Information Systems Frontiers, Springer, vol. 0, pages 1-23.
    2. Roman Lukyanenko & Andrea Wiggins & Holly K. Rosser, 2020. "Citizen Science: An Information Quality Research Frontier," Information Systems Frontiers, Springer, vol. 22(4), pages 961-983, August.
    3. Xiao, Yu & Lu, Louis Y.Y. & Liu, John S. & Zhou, Zhili, 2014. "Knowledge diffusion path analysis of data quality literature: A main path analysis," Journal of Informetrics, Elsevier, vol. 8(3), pages 594-605.
    4. Rajiv D. Banker & Robert J. Kauffman, 2004. "50th Anniversary Article: The Evolution of Research on Information Systems: A Fiftieth-Year Survey of the Literature in Management Science," Management Science, INFORMS, vol. 50(3), pages 281-298, March.
    5. Guan, Jian & Levitan, Alan S. & Kuhn, John R., 2013. "How AIS can progress along with ontology research in IS," International Journal of Accounting Information Systems, Elsevier, vol. 14(1), pages 21-38.
    6. Bettina Distel & Holger Koelmann & Ralf Plattfaut & Jörg Becker, 2022. "Watch who you trust! A structured literature review to build a typology of e-government risks," Information Systems and e-Business Management, Springer, vol. 20(4), pages 789-818, December.
    7. Donald Ballou & Richard Wang & Harold Pazer & Giri Kumar Tayi, 1998. "Modeling Information Manufacturing Systems to Determine Information Product Quality," Management Science, INFORMS, vol. 44(4), pages 462-484, April.
    8. Klein, B. D. & Rossin, D. F., 1999. "Data quality in neural network models: effect of error rate and magnitude of error on predictive accuracy," Omega, Elsevier, vol. 27(5), pages 569-582, October.
    9. Yair Wand & Ron Weber, 2002. "Research Commentary: Information Systems and Conceptual Modeling—A Research Agenda," Information Systems Research, INFORMS, vol. 13(4), pages 363-376, December.
    10. Andrew Burton-Jones & Peter N. Meso, 2006. "Conceptualizing Systems for Understanding: An Empirical Test of Decomposition Principles in Object-Oriented Analysis," Information Systems Research, INFORMS, vol. 17(1), pages 38-60, March.
    11. Klein, Barbara D., 2001. "Detecting errors in data: clarification of the impact of base rate expectations and incentives," Omega, Elsevier, vol. 29(5), pages 391-404, October.
    12. Choo Yeon Kim & Seong Soo Cha, 2023. "Effect of SNS Characteristics for Dining Out on Customer Satisfaction and Online Word of Mouth," SAGE Open, , vol. 13(3), pages 21582440231, September.
    13. Irina Heimbach & Oliver Hinz, 2018. "The Impact of Sharing Mechanism Design on Content Sharing in Online Social Networks," Information Systems Research, INFORMS, vol. 29(3), pages 592-611, September.
    14. Kim, Jeeyeon & Kim, Mingyung & Choi, Jeonghye & Trivedi, Minakshi, 2019. "Offline social interactions and online shopping demand: Does the degree of social interactions matter?," Journal of Business Research, Elsevier, vol. 99(C), pages 373-381.
    15. Büttgen, Marion & al.,, 2021. "Blockchain in Service Management and Service Research - Developing a Research Agenda and Managerial Implications," SMR - Journal of Service Management Research, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 5(2), pages 71-102.
    16. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    17. O'Keefe, Robert M., 2016. "Experimental behavioural research in operational research: What we know and what we might come to know," European Journal of Operational Research, Elsevier, vol. 249(3), pages 899-907.
    18. Maggie Chuoyan Dong & Yulin Fang & Detmar W. Straub, 2017. "The Impact of Institutional Distance on the Joint Performance of Collaborating Firms: The Role of Adaptive Interorganizational Systems," Information Systems Research, INFORMS, vol. 28(2), pages 309-331, June.
    19. Natalia Levina & Manuel Arriaga, 2014. "Distinction and Status Production on User-Generated Content Platforms: Using Bourdieu’s Theory of Cultural Production to Understand Social Dynamics in Online Fields," Information Systems Research, INFORMS, vol. 25(3), pages 468-488, September.
    20. Dunn, Cheryl L. & Gerard, Gregory J. & Grabski, Severin V., 2017. "The combined effects of user schemas and degree of cognitive fit on data retrieval performance," International Journal of Accounting Information Systems, Elsevier, vol. 26(C), pages 46-67.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orisre:v:25:y:2014:i:4:p:669-689. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.