Crowdsourcing cultural heritage metadata through social gaming - Paraschakis, Dimitris
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Crowdsourcing has been used in the cultural heritage domain for a variety of tasks. One of them is generation of descriptive metadata for digital archives. Gamification offers citizens a more entertaining way to interact with digital collections and generate useful metadata as a side effect of gameplay. In this work, we explore the integration of social networks with crowdsourcing games for generating archival metadata. We studied crowdsourcing, gamification and social dynamics from the perspective of cultural heritage and combined their features in a metadata game prototype on the Facebook…mehr

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Produktbeschreibung
Crowdsourcing has been used in the cultural heritage domain for a variety of tasks. One of them is generation of descriptive metadata for digital archives. Gamification offers citizens a more entertaining way to interact with digital collections and generate useful metadata as a side effect of gameplay. In this work, we explore the integration of social networks with crowdsourcing games for generating archival metadata. We studied crowdsourcing, gamification and social dynamics from the perspective of cultural heritage and combined their features in a metadata game prototype on the Facebook platform. We tested our prototype and evaluated its results by analysing participation, contribution and player feedback. The two-week testing phase showed promising results in terms of user engagement and produced metadata: almost 3000 tags were added, 90% of which were valid dictionary terms. We conclude that deploying metadata games on social networking platforms is a feasible method for digital archives to harness human intelligence from large shared spaces. This book is recommended for curators of digital collections as well as designers of modern data-driven social games.
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Autorenporträt
Dimitris Paraschakis, PhD candidate in Computer Science at Malmö University, Sweden. The author finds himself on the wave of modern data science and follows the trend of big data, crowdsourcing, open data, machine learning, and so on. His current research work is focused on search and recommendation algorithms in e-commerce.