Improving Judgment Reliability in Social Networks via Jury Theorems

Paolo Galeazzi; Rasmus K. Rendsvig; Marija Slavkovik

doi:10.1007/978-3-662-60292-8_17

Improving Judgment Reliability in Social Networks via Jury Theorems

Paolo Galeazzi, Rasmus K. Rendsvig, Marija Slavkovik

Department of Communication

Abstract

Opinion aggregators—such as ‘like’ or ‘retweet’ counters—are ubiquitous on social media platforms and often treated as implicit quality evaluations of the entry liked or retweeted, with higher counts indicating higher quality. Many such aggregators are poor quality evaluators as they allow disruptions of the conditions for positive wisdom-of-the-crowds effects. This paper proposes a design of theoretically justified aggregators that improve judgment reliability. Interpreting states of diffusion processes on social networks as implicit voting scenarios, we specify procedures for isolating sets of independent voters in order to use jury theorems to quantify the reliability of network states as quality evaluators. As real-world networks tend to grow very large and independence tests are computationally expensive, a primary goal is to limit the number of such tests. We consider five procedures, each trading a degree of reliability for efficiency, the most efficient requiring a low-degree polynomial number of tests.

Original language	English
Title of host publication	Logic, Rationality, and Interaction. LORI 2019.
Number of pages	14
Volume	11813
Publisher	Springer
Publication date	2019
Pages	230-243
ISBN (Print)	9783662602911
ISBN (Electronic)	9783662602928
DOIs	https://doi.org/10.1007/978-3-662-60292-8_17
Publication status	Published - 2019

Series	Lecture Notes in Computer Science
ISSN	0302-9743

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10.1007/978-3-662-60292-8_17

Cite this

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AU - Galeazzi, Paolo

AU - Rendsvig, Rasmus K.

AU - Slavkovik, Marija

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N2 - Opinion aggregators—such as ‘like’ or ‘retweet’ counters—are ubiquitous on social media platforms and often treated as implicit quality evaluations of the entry liked or retweeted, with higher counts indicating higher quality. Many such aggregators are poor quality evaluators as they allow disruptions of the conditions for positive wisdom-of-the-crowds effects. This paper proposes a design of theoretically justified aggregators that improve judgment reliability. Interpreting states of diffusion processes on social networks as implicit voting scenarios, we specify procedures for isolating sets of independent voters in order to use jury theorems to quantify the reliability of network states as quality evaluators. As real-world networks tend to grow very large and independence tests are computationally expensive, a primary goal is to limit the number of such tests. We consider five procedures, each trading a degree of reliability for efficiency, the most efficient requiring a low-degree polynomial number of tests.

AB - Opinion aggregators—such as ‘like’ or ‘retweet’ counters—are ubiquitous on social media platforms and often treated as implicit quality evaluations of the entry liked or retweeted, with higher counts indicating higher quality. Many such aggregators are poor quality evaluators as they allow disruptions of the conditions for positive wisdom-of-the-crowds effects. This paper proposes a design of theoretically justified aggregators that improve judgment reliability. Interpreting states of diffusion processes on social networks as implicit voting scenarios, we specify procedures for isolating sets of independent voters in order to use jury theorems to quantify the reliability of network states as quality evaluators. As real-world networks tend to grow very large and independence tests are computationally expensive, a primary goal is to limit the number of such tests. We consider five procedures, each trading a degree of reliability for efficiency, the most efficient requiring a low-degree polynomial number of tests.

UR - http://www.mendeley.com/research/improving-judgment-reliability-social-networks-via-jury-theorems

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DO - 10.1007/978-3-662-60292-8_17

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BT - Logic, Rationality, and Interaction. LORI 2019.

PB - Springer

ER -

Improving Judgment Reliability in Social Networks via Jury Theorems

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