Sites such as Waze or OpenStreetMap (OSM) provide free services that utilize voluntarily contributed data. This is a type of public good which benefits users and creates common benefits.
In a recent research article, it was found that users are less inclined to contribute to such public good geospatial sites if they know others are already contributing. This could have a negative effect in diminishing accuracy or utility for public sites that need to have a large number of contributions to ensure accuracy.[1]
The Effect of Diminished Participation in Volunteered GIS
The effect of diminished participation is called the “bystander effect,” that is when someone knows many people are involved in helping in a situation then they are less likely to want to contribute. On the one hand, as the number of contributors to a site increases, research indicates that more people are encouraged to contribute. However, at some threshold, the trend may reverse or the rate of people who do not want to contribute may increase.
Reward-Based Participation
In effect, there is a diffusion of responsibility as others participate in open geospatial platforms. One way to combat the effect of diminished participation could be to reward people, similar to how a blood drive may give monetary benefits to those who give blood.
Rather than a monetary award, badges of participation or encouragement to participate could be given, similar to off-line public goods that require mass participation.[2]
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Develop a Sense of Community Value to Drive Participation
Another option that sites such as Waze and OSM could do to increase crowdsourcing participation and maintain high levels of participation is to build long-lasting community value. This would give a sense people are not only participating but they are adding value because people also desire to give informative answers or information to others that is of high quality.
Sites such as Stack Overflow, used commonly by developers to answer questions related to programming, not only encourages participation but users can rate the quality of answers. In effect, it creates a competition and incentive to provide the best answers, which motivates people to provide high quality answers and increases the rate of participation as the user’s reputation benefits.[3]
This creates long-lasting value for users who have a high degree of affinity to the site and see it as very reputable, helping people to be motivated not only in using the site but also to actively participate in answering questions.
Additionally, what the recent pandemic has shown is that online communities need to encourage interventions that maintain community support and participation. This could be more target efforts that try to encourage users to participate and feel like they can be part of a wider good.
For instance, online learning sites can benefit when designing encouragement and motivation to participate that targets a demographic or group as a way to increase overall user participation on a site and create a better sense of community.[4]
How Gender Bias Impact Participation in OpenStreetMap
Studies have also shown that there are gender biases in online geospatial participation, particularly on sites such as OSM which has had much greater male participation than females, with up to 87% of participants being males in OSM.
This suggests and supports conclusions that there may also need to be interventions and active encouragement that might be more tailored, specifically to gender in this case.[5] In effect, the result supports the idea that more target interventions are needed rather than one form of solution for all users.
Increasingly, people are depending on community sites that actively record data freely given by people, where the data have wider community benefits.
Participation has generally gone up in recent years on various community sites; however, there is also participatory decline or user contributions drop as they are made aware more users are contributing. This could diminish overall GIS data quality since crowdsourced data often depend on a large number of observations to improve accuracy and verify observations.
To maintain and encourage participation, OSM, Waze, and other geospatial sites that offer a public good, then targeted interventions and creating an online community that creates real value to users might better to maintain and encourage even greater participatory rates for data sharing.
References
[1] For more on the article on diminished contributions to public good sites, see: Chenhui Guo, Tae Hun Kim, Anjana Susarla, and Vallabh Sambamurthy (2020) Understanding Content Contribution Behavior in A Geo-Segmented Mobile Virtual Community: The Context of Waze. Information Systems Research, forthcoming., Available at SSRN: https://ssrn.com/abstract=3065303 or http://dx.doi.org/10.2139/ssrn.3065303.
[2] For more on rewards given to online participation for public goods, see: https://theconversation.com/people-may-become-less-likely-to-contribute-to-a-virtual-public-good-like-wikipedia-or-waze-if-they-know-many-others-are-already-doing-it-140421.
[3] For more on how sites could create value for users, see: Anderson, A., Huttenlocher, D., Kleinberg, J., Leskovec, J., 2012. Discovering value from community activity on focused question answering sites: a case study of stack overflow, in: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining – KDD ’12. Presented at the the 18th ACM SIGKDD international conference, ACM Press, Beijing, China, p. 850. https://doi.org/10.1145/2339530.2339665.
[4] For more on interventions to increase participation rates, see: Kizilcec, R.F., Reich, J., Yeomans, M., Dann, C., Brunskill, E., Lopez, G., Turkay, S., Williams, J.J., Tingley, D., 2020. Scaling up behavioral science interventions in online education. Proc Natl Acad Sci USA 117, 14900–14905. https://doi.org/10.1073/pnas.1921417117
[5] For more on female and male participation on OSM, see: Gardner, Z., Mooney, P., De Sabbata, S., Dowthwaite, L., 2020. Quantifying gendered participation in OpenStreetMap: responding to theories of female (under) representation in crowdsourced mapping. GeoJournal 85, 1603–1620. https://doi.org/10.1007/s10708-019-10035-z.
