Decisions 2.0: the power of collective intelligence

By Eric Bonabeau. 2009

509 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/65f0033ef461d287978987e6f54bf35f5102396c

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Citations in the corpus

An Empirical Examination of the Antecedents and Consequences of Contribution Patterns in Crowd-Funded Markets (2013, unknown): “In terms of the implications of our findings for policy and regulation, the identification of social influence in this market raises the potential that some markets may enable fundraisers to “game” or manipulate the system (Bonabeau 2009).”
Crowdsourcing: A Review and Suggestions for Future Research (2018, unknown): “Some studies, however, question the performance of crowdsourcing in the process of assessing ideas: while Bonabeau (2009) found that there are advantages in assessing data through crowdsourcing, other studies conclude that collective intelligence is better at generating ideas than at evaluating…”
Darwin or Lamarck? Future Challenges in Evolutionary Algorithms for Knowledge Discovery and Data Mining (2014, background): “This is a recent and important research area in computer science [51] which can be applied for many purposes, a prominent example being the NASA crater finding [52] using human collective intelligence [53], [54].”
An Open Government Maturity Model for social media-based public engagement (2012, background): “This collective intelligence, based on a large number of individuals from diverse backgrounds, helps government agencies to make informed, reliable decisions in nearly real time (Bonabeau, 2009).”
- in-Progress (2012, unknown): “Yet others report negative impacts such as decreased time to market (Knudsen and Mortensen, 2011), more costly and resource intensive projects (Jouret, 2009), increased costs in setting up legal frameworks and protecting IP (Jouret, 2009), and loss of control by the organization (Bonabeau, 2009).”
Network dynamics of social influence in the wisdom of crowds (2017, background): “Based on these ideas, commercial and nonproﬁt organizations have implemented automated aggregation tools to collect individuals’ independent beliefs in ways that minimize the information exchanged between them (37).”
Evaluation on crowdsourcing research: Current status and future direction (2012, background): “…may lose a significant degree of control over the behavior of the crowd and outcome of the project, as the crowd is likely to make unpredictable moves or is steered by undue influences (Bonabeau 2009), and sometimes the crowd may even change the project and the organization ’ s primary goals.”