@inproceedings{8884482c2176432b84a64c178c7be710,
title = "Critical Source Selection in Social Sensing Applications",
abstract = "Social sensing has emerged as a new data collection paradigm in networked sensing applications where humans are used as 'sensors' to report their observations about the physical world. While many previous studies in social sensing focus on the problem of ascertaining the reliability of data sources and the correctness of their reported claims (often known as truth discovery), this paper investigates a new problem of critical source selection. The goal of this problem is to identify a subset of critical sources that can help effectively reduce the computational complexity of the original truth discovery problem and improve the accuracy of the analysis results. In this paper, we propose a new scheme, Critical Sources Selection (CSS) scheme, to find the critical set of sources by explicitly exploring both dependency and speak rate of sources. We evaluated the performance of our scheme and compared it to the state-of-the-art baselines using two data traces collected from a real world social sensing application. The results showed that our scheme significantly outperforms the baselines by finding more truthful information at a faster speed.",
keywords = "Social Sensing, Source Dependency, Source Selection, Speak Rate, Twitter",
author = "Chao Huang and Dong Wang",
note = "Funding Information: This material is based upon work supported by the National Science Foundation under Grant No. CBET-1637251, CNS-1566465 and IIS-1447795 and Army Research Office under Grant W911NF-16-1-0388. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. Publisher Copyright: {\textcopyright} 2017 IEEE.; 13th International Conference on Distributed Computing in Sensor Systems, DCOSS 2017 ; Conference date: 05-06-2017 Through 07-06-2017",
year = "2018",
month = jan,
day = "26",
doi = "10.1109/DCOSS.2017.27",
language = "English (US)",
series = "Proceedings - 2017 13th International Conference on Distributed Computing in Sensor Systems, DCOSS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "53--60",
booktitle = "Proceedings - 2017 13th International Conference on Distributed Computing in Sensor Systems, DCOSS 2017",
address = "United States",
}