Search (2 results, page 1 of 1)

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Abstract

In explicit collaborative search, two or more individuals coordinate their efforts toward a shared goal. Every day, Internet users with similar information needs have the potential to collaborate. However, online search is typically performed in solitude. Existing search systems do not promote explicit collaborations, and collaboration opportunities (collabportunities) are missed. In this article, we describe a method to evaluate the feasibility of transforming these collabportunities into recommendations for explicit collaboration. We developed a technique called pseudocollaboration to evaluate the benefits and costs of collabportunities through simulations. We evaluate the performance of our method using three data sets: (a) data from single users' search sessions, (b) data with collaborative search sessions between pairs of searchers, and (c) logs from a large-scale search engine with search sessions of thousands of searchers. Our results establish when and how collabportunities would significantly help or hinder the search process versus searches conducted individually. The method that we describe has implications for the design and implementation of recommendation systems for explicit collaboration. It also connects system-mediated and user-mediated collaborative search, whereby the system evaluates the likely benefits of collaborating for a search task and helps searchers make more informed decisions on initiating and executing such a collaboration.

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Abstract

People frequently answer consequential questions, such as those with a medical focus, using Internet search engines. Their primary goal is to revise or establish beliefs in one or more outcomes. Search engines are not designed to furnish answers, and instead provide results that may contain answers. Information retrieval research has targeted aspects of information access such as query formulation, relevance, and search success. However, there are important unanswered questions on how beliefs-and potential biases in those beliefs-affect search behaviors and how beliefs are shaped by searching. To understand belief dynamics, we focus on yes-no medical questions (e.g., "Is congestive heart failure a heart attack?"), with consensus answers from physicians. We show that (a) presearch beliefs are affected only slightly by searching and changes are likely to skew positive (yes); (b) presearch beliefs affect search behavior; (c) search engines can shift some beliefs by manipulating result rank and availability, but strongly-held beliefs are difficult to move using uncongenial information and can be counterproductive, and (d) search engines exhibit near-random answer accuracy. Our findings suggest that search engines should provide correct answers to searchers' questions and develop methods to persuade searchers to shift strongly held but factually incorrect beliefs.