Advances in social computing have driven a new culture of participation. Creating documents through cooperation and social exchange benefits from a synergy of skills, distributed decisions, and the dynamic maintenance of shared knowledge. webLyzard provides several features to support such collaborative processes:
- synchronous document editing with instant content recommendations based on a real-time analysis of the co-authored document,
- visual navigational aids that reflect shared meaning and the evolving semantic context of the edited document (author, topic, location, etc.),
- the ability to export jointly created resources for reuse in third-party applications and integration into existing workflows.
Authoring Models. Traditional models to collaboratively create documents assume a sequential process. Authors (i) investigate a topic by reviewing the literature, scanning news articles or using a search engine; (ii) communicate with co-authors, (iii) draft and revise the manuscript. The sequential character of these phases fragments the workflow. To meet the requirements of companies operating in dynamic markets, webLyzard’s automated content recommendations merge these distinct phases. They go beyond online word processing tools such as Google Docs and MS Word Web App by enabling implicit information seeking, where the system infers informational needs from user actions rather than explicit queries.
Real-Time Content Recommendations. When users jointly edit a document, the system immediately distributes changes to all co-authors, performs background queries to fetch similar documents from the selected set of sources (news, social media, etc.), and suggests appropriate tags for classifying the document in terms of topic, sentiment, or geographic location. webLyzard delivers content on the fly, while users are typing. These suggestions align the evolving document with the existing body of knowledge. Co-authors learn about related threads in various online media channels. This instant feedback loop guides the collaborative work and highlights issues that co-authors might otherwise have overlooked. To recommend documents, webLyzard follows a content-based ranking strategy. Authors can customize this ranking strategy in line with their current tasks and preferences using the slider elements of the advanced search dialog.
To embed the (co-)created knowledge into existing workflows, webLyzard supports a range of export formats – in line with calls for a Semantic Social Web, in which data is not locked away within data silos but can be easily integrated and exchanged between applications and authors.
Social Innovation. The platform is currently being extended through DecarboNet, a research project funded within the European 7th Framework Programme. The project will integrate the collaborative editor with eco-feedback tools to engage citizens in games with a purpose, and to capture collective awareness by tracking information diffusion processes and resonance patterns in online communication. To apply the technology, DecarboNet will pursue a large-scale awareness campaign together with WWF Switzerland and the Climate Program Office of the National Oceanic and Atmospheric Administration (NOAA).
- Scharl, A., Hubmann-Haidvogel, A., et al. (2013). “From Web Intelligence to Knowledge Co-Creation – A Platform to Analyze and Support Stakeholder Communication”, IEEE Internet Computing, 17(5): 21-29.
- Scharl, A., Reyes, C. and Hubmann-Haidvogel, A. (2014). Supporting the Collaborative Editing of Documents with Real-Time Content Recommendations. 13th Brazilian Symposium on Human Factors in Computer Systems (IHC-2014). Foz do Iguaçu, Brazil: Forthcoming (Accepted 17 Aug 2014).