Motivations, engagement, and incentives in online communitiescontributions to theory, data analytics and design

Abstract

The success of an online community depends on the contributions and actions performed by the community members. This dissertation aims to understand the dynamics of participation in regulated, not-for-profit, open online communities, and how the motivations and engagement incentives affect it, following a data analytics approach. For this purpose, this thesis provides a set of contributions around four objectives. The first objective deals with the understanding of motivational factors to participate in online communities, and the definition of a model to guide the design decisions and to better understand participants’ behavior. To tackle this objective, we have explored several motivation theories used in online communities and defined an integrated motivational model for online communities, which is a theoretical contribution from the thesis used to guide the design decisions. The second objective aims at developing online communities following a Design-Based Research (DBR) methodology and focusing on the defined motivational model. To this end, two platforms have been iteratively designed and tested in different communities from June 2018 to April 2021: a) the first platform enables communities of teachers the exploration, sharing and discussion of learning designs, and it was used in the context of two online communities for pre- and in-service teachers, namely Teachers in network (with a total of 91 participants) and Makers in the classroom (with a total of 252 participants); b) the second platform supports a virtual citizen science project to study the emotional content in music to improve the research in music emotion recognition and was iteratively tested with a total of 142 participants. The third objective is devoted to the study of motivations and incentives in online communities using a data-analytics approach. Based on the results obtained from the DBR cycles to develop the supporting platforms and on a mixed-methods approach, we studied the relation between participants’ motivations, and the implemented incentives, their behavior within the community and the quality of the contributions done. Data was collected using surveys, focus groups, interviews and data logs, and different data analytics techniques (statistical analysis, process mining, networks analysis) have been implemented to better understand the dynamics of participation and how the motivational factors influence participants’ behavior and perception of the supporting platforms’ features. Besides, this thesis presents a data-analytics framework to assist researchers, designers, developers, and data analysts in the study of motivations, data quality and behavior, and the impact of incentives in online communities. Finally, the fourth objective aims at proposing design implications and recommendations for the development and sustainability of supporting platforms for online communities. As a result of the design-based research methodology, we propose a set of design implications to guide the development of supporting platforms for online communities.