A Human-Machine Collaborative System for Identifying Rumors on Twitter
Name
vosoughi_ICDM_EASM_2015.pdf
Description
Main article
Size
473.86 KB
Format
Adobe PDF
Checksum (MD5)
d87a374e939997adc112ac1d1d14b70b
Author(s)
Vosoughi, Soroush
Roy, Deb K
Date Issued
November 2015
Journal
Proceedings of the 2015 IEEE International Conference on Data Mining Workshop (ICDMW)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Vosoughi, Soroush, and Deb Roy. “A Human-Machine Collaborative System for Identifying Rumors on Twitter.” 2015 IEEE International Conference on Data Mining Workshop (ICDMW) (November 2015).
Version
Author's final manuscript
Abstract
The spread of rumors on social media, especially in time-sensitive situations such as real-world emergencies, can have harmful effects on individuals and society. In this work, we developed a human-machine collaborative system on Twitter for fast identification of rumors about real-world events. The system reduces the amount of information that users have to sift through in order to identify rumors about real-world events by several orders of magnitude.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICDMW.2015.221
