TransAgere Agent-Oriented Engineering of Social Software - Shaping Social Interactions for Knowledge Transfer

With today`s work environments becoming more knowledge-intensive, collaborative, distributed and dynamic in nature, effective knowledge transfer across time, individuals, groups and locations becomes a competitive advantage. Traditional technologies are known to be able to facilitate knowledge transfer only to a certain extent. With social software, a new breed of technologies emerged recently that focuses specifically on supporting social activities in digital social networks. Because knowledge transfer has an inherent social component, social software can be expected to have an extraordinary impact on the way knowledge transfer is being facilitated in the future. However, social software represents a very recent phenomenon, has emerged out of practical considerations (e.g. easy-to-use interfaces) and was not specifically intended for knowledge transfer. As a result, our theoretical understanding of applying social software for knowledge transfer is insufficient. However, internet users increasingly use social software for knowledge transfer purposes implicitly, which raises a series of fundamental research questions: What specific purposes can social software serve in a knowledge transfer context? How can we evaluate the effectiveness of social software for knowledge transfer in different settings? What kind of social interactions are especially relevant in the light of knowledge transfer, and how can we identify, analyze and shape them through social software? To address these questions, the TransAgere project will develop methods for evaluating and shaping social interactions for knowledge transfer through social software by exploring an agent- oriented engineering approach. Agent orientation can be viewed as an especially promising paradigm in this context by providing a strong theoretical foundation and relevant ontological constructs for the weakly-understood phenomenon of social software. The results of this project will consist of empirical knowledge about the social mechanisms of knowledge transfer in social software, methods for evaluating the situated effectiveness of social software for knowledge transfer, methods for shaping social interactions through social software, social software prototypes and comprehensive evaluations of the usefulness of the developed methods and prototypes. This international research cooperation project will be executed at the Know-Center Graz, Austria`s competence centre for knowledge based systems and applications in cooperation with the Institute of Knowledge Management at the University of Technology Graz, Austria and the Knowledge Management Lab at the Department of Computer Science at University of Toronto, Canada. The main project applicant is Markus Strohmaier.

The overall objective of this project was to systematically increase our understanding about the role of agents and their goals and motivations in engineering social software. The project focussed on two domains, in particular two kinds of social software that have gained certain relevance on the web. On one hand, this project focused on the studying and measuring the motivations of human agents in the context of so-called social tagging systems. The results of this work led to an improved understanding about individual usage patterns, their underlying causes and related social processes in such systems. On the other hand, this project studied the goals and intentions of users who search the world wide web. Based on an analysis of existing search query logs, the project developed and applied methods for acquiring and - to some extent - predicting the goals of users while they search. The results of this project, including the developed methods and the conducted empirical studies, contribute to advancing our knowledge about the role of agents and their motivations and goals in engineering social software systems.