Demo Paper: A Confidence-aware Truth Estimation Tool for Social Sensing Applications

Chao Huang, Dong Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a demonstration of our SECON 2015 paper using Twitter based case studies for social sensing applications. Social sensing has emerged as a new paradigm of data collection, where a group of individuals volunteer (or are recruited) to share certain observations or measurements about the physical world. A key challenge in social sensing applications lies in ascertaining the correctness of reported observations from unvetted data sources with unknown reliability. We refer to this problem as truth estimation. In this paper, we showed a demo of a new confidence-aware truth estimation scheme that explicitly considers different degrees of confidence that sources express on the reported data. In the demo session: the participants will have a chance to (i) play with the tool on some historic datasets we have collected from Twitter; (ii) send live queries to Twitter and perform real-time truth estimation analysis in the events of their interests.

Original languageEnglish (US)
Title of host publication2015 12th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages187-189
Number of pages3
ISBN (Electronic)9781467373319
DOIs
StatePublished - Nov 25 2015
Externally publishedYes
Event12th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2015 - Seattle, United States
Duration: Jun 22 2015Jun 25 2015

Publication series

Name2015 12th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2015

Other

Other12th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2015
Country/TerritoryUnited States
CitySeattle
Period6/22/156/25/15

Keywords

  • Apollo Fact-finder
  • Confidence-Aware
  • Expectation Maximization
  • Maximum Likelihood Estimation
  • Social Sensing
  • Truth Estimation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Instrumentation

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