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Title: Information aggregation and computational intelligence
Authors: 陳樹衡
Chen, Shu-Heng
Venkatachalam, Ragupathy
Contributors: 經濟學系
Date: 2017
Issue Date: 2017-08-17 16:58:02 (UTC+8)
Abstract: This study examines the possibility that the computational intelligence (CI) inspired tools can effectively aggregate the rich information generated from the Web 2.0 economy and, thereby, enhance the quality of decision-making. Despite many advancements and commendable applications of CI in recent years, this issue has not been well addressed. We argue that this question is intimately related to the central issue of the socialist calculation debate since the time of Friedrich Hayek. In terms of information aggregation, we examine whether there is a better engineering than the market mechanism. More precisely, we focus on whether the CI-driven sentiment analysis can generate signals like prices and whether CI can process unstructured text data better than the market. We argue that Web 2.0 economy may not be able to set us free from information overload problems that have long coexisted with the presence of markets. We attribute this to the tacitness and subjectivity of knowledge and the recursive (feedback) characteristic of the sentiments. In this sense, Hayek’s fundamental assertion that the effectiveness of the market mechanism may not be so much conditioned on the information and communication technology still applies.
Relation: Evolutionary and Institutional Economics Review
June 2017, Volume 14, Issue 1, pp 231–252
Data Type: article
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Appears in Collections:[經濟學系] 期刊論文

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