A Social Search Engine Built Upon the Actor-Network Theory

This research leverages information retrieval activity in order to build a network of organizational expertise in a distributed R&D laboratory. The authors describe traditional knowledge management practices and review post-cognitivists theories in order to define social creation in collaborative information retrieval activity. The Actor-Network theory accurately describes association processes and includes both human and non-human entities. This chapter compares this theory with the emergence of Social Search services online and Experts’ Retrieval Systems. The chapter authors suggest afterward, a social search engine named DemonD that identifies documents but more specifically users relevant to a query. DemonD relies on transparent profile construction based upon user activity, community participation, and shared documents. Individuals are invited to participate in a dedicated newsgroup and the information exchanged is capitalized. The evaluation of our service both ergonomic and through a simulation provides encouraging data. InTRoduCTIon And ConTexT deSCRIPTIon During the early years of the Personal Computer research, two rather distinctive philosophical approaches competed. Artificial Intelligence believers wished to replace humans by machine whereas Human Intelligence Augmentation project, led by Douglas Engelbart, envisioned computers as a technology to augment human mind and eventually network each other’s (Markoff, 2005). This debate is still vibrant in the Information Retrieval community where the algorithmic approach is recently challenged by human approaches leveraging individual’s social capital to identify pertinent knowledge sources. Our work contributes to this “Social Search movement”, in a corporate DOI: 10.4018/978-1-60566-306-7.ch008