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Using humans as sensors: an estimation-theoretic perspective

Authors:

Md Tanvir Amin,

Tarek Abdelzaher,

Charu C. Aggarwal,

Prasant Mohapatra,

Boleslaw Szymanski,

Hieu LeAuthors Info & Claims

IPSN '14: Proceedings of the 13th international symposium on Information processing in sensor networks

Pages 35 - 46

Published: 15 April 2014 Publication History

Abstract

The explosive growth in social network content suggests that the largest "sensor network" yet might be human. Extending the participatory sensing model, this paper explores the prospect of utilizing social networks as sensor networks, which gives rise to an interesting reliable sensing problem. In this problem, individuals are represented by sensors (data sources) who occasionally make observations about the physical world. These observations may be true or false, and hence are viewed as binary claims. The reliable sensing problem is to determine the correctness of reported observations. From a networked sensing standpoint, what makes this sensing problem formulation different is that, in the case of human participants, not only is the reliability of sources usually unknown but also the original data provenance may be uncertain. Individuals may report observations made by others as their own. The contribution of this paper lies in developing a model that considers the impact of such information sharing on the analytical foundations of reliable sensing, and embed it into a tool called Apollo that uses Twitter as a "sensor network" for observing events in the physical world. Evaluation, using Twitter-based case-studies, shows good correspondence between observations deemed correct by Apollo and ground truth.

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Cited By

Wu GZhuo XBao XHu XHong RWu X(2022)Crowdsourcing Truth Inference via Reliability-Driven Multi-View Graph EmbeddingACM Transactions on Knowledge Discovery from Data10.1145/356557617:5(1-26)Online publication date: 4-Oct-2022
https://dl.acm.org/doi/10.1145/3565576
Cui HAbdelzaher T(2021)SenseLens: An Efficient Social Signal Conditioning System for True Event DetectionACM Transactions on Sensor Networks10.1145/348504718:2(1-27)Online publication date: 29-Oct-2021
https://dl.acm.org/doi/10.1145/3485047
Xu FSheng VWang M(2021)A Unified Perspective for Disinformation Detection and Truth Discovery in Social Sensing: A SurveyACM Computing Surveys10.1145/347713855:1(1-33)Online publication date: 23-Nov-2021
https://dl.acm.org/doi/10.1145/3477138
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Index Terms

Using humans as sensors: an estimation-theoretic perspective
1. Information systems
  1. Information systems applications

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Information & Contributors

Information

Published In

cover image ACM Conferences

IPSN '14: Proceedings of the 13th international symposium on Information processing in sensor networks

April 2014

368 pages

ISBN:9781479931460

General Chair:
Adam Wolisz
TU Berlin, Germany
,
Program Chairs:
Jie Liu
Microsoft Research, USA
,
Lin Zhong
Rice University, USA

Sponsors

IEEE
SIGBED: ACM Special Interest Group on Embedded Systems
IEEE-CS\DATC: IEEE Computer Society

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IEEE Press

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Published: 15 April 2014

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Division of Computer and Network Systems
Defense Threat Reduction Agency
U.S. Army Research Laboratory
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IPSN '14 Paper Acceptance Rate 23 of 111 submissions, 21%;

Overall Acceptance Rate 143 of 593 submissions, 24%

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Cited By

Wu GZhuo XBao XHu XHong RWu X(2022)Crowdsourcing Truth Inference via Reliability-Driven Multi-View Graph EmbeddingACM Transactions on Knowledge Discovery from Data10.1145/356557617:5(1-26)Online publication date: 4-Oct-2022
https://dl.acm.org/doi/10.1145/3565576
Cui HAbdelzaher T(2021)SenseLens: An Efficient Social Signal Conditioning System for True Event DetectionACM Transactions on Sensor Networks10.1145/348504718:2(1-27)Online publication date: 29-Oct-2021
https://dl.acm.org/doi/10.1145/3485047
Xu FSheng VWang M(2021)A Unified Perspective for Disinformation Detection and Truth Discovery in Social Sensing: A SurveyACM Computing Surveys10.1145/347713855:1(1-33)Online publication date: 23-Nov-2021
https://dl.acm.org/doi/10.1145/3477138
Gianini GMio CViola FLin JAlmoosa NChbeir RManolopoulos YDamiani EBenslimane DBellatreche LMorzy T(2020)Selection of Information Streams in Social SensingProceedings of the 12th International Conference on Management of Digital EcoSystems10.1145/3415958.3433099(157-161)Online publication date: 2-Nov-2020
https://dl.acm.org/doi/10.1145/3415958.3433099
Cui HAbdelzaher TKaplan L(2019)A Semi-Supervised Active-learning Truth Estimator for Social NetworksThe World Wide Web Conference10.1145/3308558.3313712(296-306)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308558.3313712
Zhang HLi YMa FGao JSu LGuo YFarooq F(2018)TextTruthProceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3219819.3219977(2729-2737)Online publication date: 19-Jul-2018
https://dl.acm.org/doi/10.1145/3219819.3219977
Abdelzaher TAyanian NBasar TDiggavi SDiesner JGanesan DGovindan RJha SLepoint TMarlin BNahrstedt KNicol DRajkumar RRussell SSeshia SSha FShenoy PSrivastava MSukhatme GSwami ATabuada PTowsley DVaidya NVeeravalli V(2018)Toward an Internet of Battlefield ThingsComputer10.1109/MC.2018.287604851:11(24-36)Online publication date: 1-Nov-2018
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Wang SGiridhar PKaplan LAbdelzaher T(2017)Unsupervised Event Tracking by Integrating Twitter and InstagramProceedings of the 2nd International Workshop on Social Sensing10.1145/3055601.3055615(81-86)Online publication date: 18-Apr-2017
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Roy APebesma E(2017)A Machine Learning Approach to Demographic Prediction using GeohashesProceedings of the 2nd International Workshop on Social Sensing10.1145/3055601.3055603(15-20)Online publication date: 18-Apr-2017
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Wang SGiridhar PWang HKaplan LPham TYener AAbdelzaher T(2017)StoryLineProceedings of the Second International Conference on Internet-of-Things Design and Implementation10.1145/3054977.3054992(83-93)Online publication date: 18-Apr-2017
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