Abstract Certification by analysts on a FinTech platform that harnesses the “wisdom of crowds” is associated with successful initial coin offerings (ICOs). We show favorable ratings group diverse backgrounds positively predict fundraising success and long-run token performance. Analysts’ also help detect potential fraud ex ante. document have career concerns are incentivized to issue informativ...

Machine learning applications can benefit greatly from vast amounts of data, provided that reliable labels are available. Mobilizing crowds to annotate the unlabeled data is a common solution. Although the labels provided by the crowd are subjective and noisy, the wisdom of crowds can be captured by a variety of techniques. Finding the mean or the median of a sample’s annotations are widely use...

The Wisdom of Crowds, an innovative theory described in social science, claims that the aggregate decisions made by a group will often be better than those of its individual members if the four fundamental criteria of this theory are satisfied. This theory used for in clustering problems. Previous researches showed that this theory can significantly increase the stability and performance of...

We are sympathetic with Bentley et al.'s attempt to encompass the wisdom of crowds in a generative model, but posit that a successful attempt at using big data will include more sensitive measurements, more varied sources of information, and will also build from the indirect information available through technology, from ancillary technical features to data from brain-computer interfaces.

We study a novel mechanism design model in which agents arrive sequentially and each in turn chooses one action from a set of actions with unknown rewards. The information that becomes available affects the incentives of an agent to explore and generate new information. We characterize the optimal disclosure policy of a planner whose goal is to maximizes social welfare. One interpretation for o...

Purpose: One of the under-explored aspects in the process of user information seeking behaviour is influence of time on relevance evaluation. It has been shown in previous studies that individual users might change their assessment of search results over time. It is also known that aggregated judgments of multiple individual users can lead to correct and reliable decisions; this phenomenon is k...