Name
Abstract | ||
|---|---|---|
Information literacy encompasses a range of information evaluation skills for the purpose of making judgments. In the context of crowdsourcing, divergent evaluation criteria might introduce bias into collective judgments. Recent experiments have shown that crowd estimates can be swayed by social influence. This might be an unanticipated effect of media literacy training: encouraging readers to critically evaluate information falls short when their judgment criteria are unclear and vary among social groups. In this exploratory study, we investigate the criteria used by crowd workers in reasoning through a task. We crowdsourced evaluation of a variety of information sources, identifying multiple factors that may affect individual's judgment, as well as the accuracy of aggregated crowd estimates. Using a multi-method approach, we identified relationships between individual information assessment practices and analytical outcomes in crowds, and propose two analytic criteria, relevance and credibility, to optimize collective judgment in complex analytical tasks. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.24251/hicss.2019.051 | PROCEEDINGS OF THE 52ND ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES |
Field | DocType | Citations |
Computer science,Knowledge management,Information literacy | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 14 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Olga Boichak | 1 | 1 | 1.75 |
| Jordan Canzonetta | 2 | 0 | 0.34 |
| Niraj Sitaula | 3 | 0 | 0.68 |
| Brian McKernan | 4 | 2 | 3.44 |
| Sarah M. Taylor | 5 | 26 | 6.60 |
| Patrícia G. C. Rossini | 6 | 0 | 1.01 |
| Benjamin A. Clegg | 7 | 36 | 7.23 |
| Kate Kenski | 8 | 0 | 0.34 |
| Rosa Mikeal Martey | 9 | 2 | 0.79 |
| Nancy McCracken | 10 | 0 | 0.34 |
| Carsten S. Østerlund | 11 | 124 | 17.43 |
| Roc Myers | 12 | 0 | 0.34 |
| James E. Folkestad | 13 | 2 | 2.08 |
| Jennifer Stromer-galley | 14 | 119 | 17.81 |