Algorithmic mediation for collaborative exploratory search

  • Authors:

  • Jeremy Pickens;Gene Golovchinsky;Chirag Shah;Pernilla Qvarfordt;Maribeth Back

  • Affiliations:

  • FX Palo Alto Lab, Inc., Palo Alto, CA, USA;FX Palo Alto Lab, Inc., Palo Alto, CA, USA;University of North Carolina, Chapel Hill, NC, USA;FX Palo Alto Lab, Inc., Palo Alto, CA, USA;FX Palo Alto Lab, Inc., Palo Alto, CA, USA

  • Venue:
  • Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
  • Year:
  • 2008

Quantified Score

Hi-index 0.02

Visualization

Abstract

We describe a new approach to information retrieval: algorithmic mediation for intentional, synchronous collaborative exploratory search. Using our system, two or more users with a common information need search together, simultaneously. The collaborative system provides tools, user interfaces and, most importantly, algorithmically-mediated retrieval to focus, enhance and augment the team's search and communication activities. Collaborative search outperformed post hoc merging of similarly instrumented single user runs. Algorithmic mediation improved both collaborative search (allowing a team of searchers to find relevant information more efficiently and effectively), and exploratory search (allowing the searchers to find relevant information that cannot be found while working individually).