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Enhancing crowd wisdom using measures of diversity computed from social media data

Authors:

Shreyansh Bhatt,

Brandon Minnery,

Srikanth Nadella,

Valerie Shalin,

Amit ShethAuthors Info & Claims

WI '17: Proceedings of the International Conference on Web Intelligence

Pages 907 - 913

https://doi.org/10.1145/3106426.3106491

Published: 23 August 2017 Publication History

Abstract

"Wisdom of Crowds" (WoC) refers to a form of collective intelligence in which the aggregate judgment of a group of individuals is, in most instances, superior to that of any one group member. For a crowd to be wise, its members must possess diverse knowledge and viewpoints. Such diversity leads to uncorrelated judgment errors that cancel out in aggregate. Yet despite the fact that diversity is known to be an essential ingredient in WoC, little research aims to measure and exploit diversity in human social systems for the purpose of maximizing crowd intelligence. Here we quantify the diversity of a group of individuals through semantic analysis of their social media (Twitter) communications. Focusing on the domain of fantasy sports, we show that virtual crowds of fantasy team owners selected based on the diversity of their tweet content can outperform both non-diverse and randomly sampled crowds. Our results suggest a new approach for intelligent crowd assembly in which measures of diversity extracted from online social media communications can guide the selection of crowd members. These results have implications for numerous domains that utilize aggregated judgments - from consumer reviews, to econometrics, to geopolitical forecasting and intelligence analysis.

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Cited By

Baj-Rogowska A(2024)The Crowd as a Source of Knowledge - From User Feedback to Fulfilling RequirementsProceedings of the 32nd International Conference on Information Systems Development10.62036/ISD.2024.109Online publication date: 2024
https://doi.org/10.62036/ISD.2024.109
Truong HNguyen V(2024)A new method for enhancing collective intelligence using expert’s knowledgeJournal of Information and Telecommunication10.1080/24751839.2024.23180738:4(531-547)Online publication date: 20-Feb-2024
https://doi.org/10.1080/24751839.2024.2318073
Nguyen VTruong H(2023)Intelligent Collectives: Impact of Independence on Collective PerformanceCybernetics and Systems10.1080/01969722.2022.216273555:3(618-633)Online publication date: 13-Jan-2023
https://doi.org/10.1080/01969722.2022.2162735
Show More Cited By

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Information & Contributors

Information

Published In

cover image ACM Conferences

WI '17: Proceedings of the International Conference on Web Intelligence

August 2017

1284 pages

ISBN:9781450349512

DOI:10.1145/3106426

Conference Chair:
Amit Sheth
Wright State University GuoROLE@GENERAL CHAIR
,
General Chairs:
Axel Ngonga
Leipzig University, Germany
,
yin Wang
Chongqing University of Posts and Telecommunications, China
,
Elizabeth Chang
The University of New South Wales, Australia
,
Dominik Ślęzak
Infobright Inc. & University of Warsaw, Poland
,
Bogdan Franczyk
Leipzig University, Germany
,
Program Chairs:
Rainer Alt
Leipzig University, Germany
,
Xiaohui Tao
University of Southern Queensland, Australia

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGAI: ACM Special Interest Group on Artificial Intelligence
TCII: IEEE Computer Society Technical Committee on Intelligent Informatics
Web Intelligence Consortium

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 August 2017

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Army Research Office

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WI '17

Sponsor:

SIGAI
TCII

WI '17: International Conference on Web Intelligence 2017

August 23 - 26, 2017

Leipzig, Germany

Acceptance Rates

WI '17 Paper Acceptance Rate 118 of 178 submissions, 66%;

Overall Acceptance Rate 118 of 178 submissions, 66%

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Cited By

Baj-Rogowska A(2024)The Crowd as a Source of Knowledge - From User Feedback to Fulfilling RequirementsProceedings of the 32nd International Conference on Information Systems Development10.62036/ISD.2024.109Online publication date: 2024
https://doi.org/10.62036/ISD.2024.109
Truong HNguyen V(2024)A new method for enhancing collective intelligence using expert’s knowledgeJournal of Information and Telecommunication10.1080/24751839.2024.23180738:4(531-547)Online publication date: 20-Feb-2024
https://doi.org/10.1080/24751839.2024.2318073
Nguyen VTruong H(2023)Intelligent Collectives: Impact of Independence on Collective PerformanceCybernetics and Systems10.1080/01969722.2022.216273555:3(618-633)Online publication date: 13-Jan-2023
https://doi.org/10.1080/01969722.2022.2162735
Sulik JBahrami BDeroy O(2021)The Diversity Gap: When Diversity Matters for KnowledgePerspectives on Psychological Science10.1177/1745691621100607017:3(752-767)Online publication date: 4-Oct-2021
https://doi.org/10.1177/17456916211006070
Nguyen VTran VTruong HNguyen N(2021)Social Networks as Platforms for Enhancing Collective IntelligenceCybernetics and Systems10.1080/01969722.2021.201854453:5(425-442)Online publication date: 31-Dec-2021
https://doi.org/10.1080/01969722.2021.2018544
Bhatt SPadhee SSheth AChen KShalin VDoran DMinnery BCulpepper JMoffat ABennett PLerman K(2019)Knowledge Graph Enhanced Community Detection and CharacterizationProceedings of the Twelfth ACM International Conference on Web Search and Data Mining10.1145/3289600.3291031(51-59)Online publication date: 30-Jan-2019
https://dl.acm.org/doi/10.1145/3289600.3291031
Nebbione GDoran DNadella SMinnery B(2019)Deep Neural Ranking for Crowdsourced Geopolitical Event ForecastingMachine Learning for Networking10.1007/978-3-030-19945-6_18(257-269)Online publication date: 10-May-2019
https://doi.org/10.1007/978-3-030-19945-6_18
Bhatt SGaur MBullemer BShalin VSheth AMinnery B(2018)Enhancing Crowd Wisdom Using Explainable Diversity Inferred from Social Media2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)10.1109/WI.2018.00-77(293-300)Online publication date: Dec-2018
https://doi.org/10.1109/WI.2018.00-77
Kursuncu UGaur MLokala UThirunarayan KSheth AArpinar I(2018)Predictive Analysis on Twitter: Techniques and ApplicationsEmerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining10.1007/978-3-319-94105-9_4(67-104)Online publication date: 18-Sep-2018
https://doi.org/10.1007/978-3-319-94105-9_4

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