Recomendation systems and crowdsourcing: a good wedding for enabling innovation? Results from technology affordances and costraints theory

Recommendation Systems have come a long way since their first appearance in the e-commerce platforms.Since then, evolved Recommendation Systems have been successfully integrated in social networks. Now its time to test their usability and replicate their success in exciting new areas of web -enabled phenomena. One of these is crowdsourcing. Research in the IS field is investigating the need, benefits and challenges of linking the two phenomena. At the moment, empirical works have only highlighted the need to implement these techniques for tasks assignment in crowdsourcing distributed work platforms and the derived benefits for contributors and firms. We review the variety of the tasks that can be crowdsourced through these platforms and theoretically evaluate the efficiency of using RS to recommend a task in creative crowdsourcing platforms. Adopting a Technology Affordances and Constraints Theory, an emerging perspective in the Information Systems (IS) literature to understand technology use and consequences, we anticipate the tensions that this implementation can generate

Real-time crowd control of existing interfaces

Crowdsourcing has been shown to be an effective approach for solving difficult problems, but current crowdsourcing systems suffer two main limitations: (i) tasks must be repackaged for proper display to crowd workers, which generally requires substantial one-off programming effort and support infrastructure, and (ii) crowd workers generally lack a tight feedback loop with their task. In this paper, we introduce Legion, a system that allows end users to easily capture existing GUIs and outsource them for collaborative, real-time control by the crowd. We present mediation strategies for integrating the input of multiple crowd workers in real-time, evaluate these mediation strategies across several applications, and further validate Legion by exploring the space of novel applications that it enables

LuzDeploy: A Collective Action System for Installing Navigation Infrastructure for Blind People

Providing navigation assistance to people with visual impairments often requires augmenting the environment with after-market technology. However, installing navigation infrastructure in large environments requires a critical mass of trained personnel. Recruiting, training and managing participants for such a task is difficult. LuzDeploy is a computational method to recruit, instruct and orchestrate volunteers to perform physical crowdsourcing tasks. We use LuzDeploy to orchestrate volunteers to install physical infrastructure for the navigation assistance of people with visual impairments. Our system provides on-the-go enrollment so that volunteers can participate to the collective action whenever they have time, coming and leaving as needed. Providing automated instructions also allows to avoid instructing participants directly, so experts do not need to be available on-site

Ontological Services Using Crowdsourcing

This paper develops a service for ontology evolution based on crowdsourcing. The approach is demonstrated using OntoAssist, a specially designed semantic search service that is capable of capturing and disambiguating user’s search intent as well as automatically enabling ontology evolution. Successful and consistent ontology evolution often requires large amount of input data to specify new terms or changes in relationships. These inputs typically come mainly from domain experts or ontology professionals, which makes it hard to keep up with the change of open, dynamic World Wide Web environment. By integrating OntoAssist with an existing search engine, we show that users’ search intent can be disambiguated and aggregated to help to evolve underlying ontology. The disambiguation feature helps the users to find desirable search results. OntoAssist has been implemented and tested by Turkers from Amazon Mechanical Turk in a live demonstration site. Promising results and analysis are reported