@inproceedings{91869278efe849b1b5647742cb11529d,
title = "Information provenance in social media",
abstract = "Information appearing in social media provides a challenge for determining the provenance of the information. However, the same characteristics that make the social media environment challenging provide unique and untapped opportunities for solving the information provenance problem for social media. Current approaches for tracking provenance information do not scale for social media and consequently there is a gap in provenance methodologies and technologies providing exciting research opportunities for computer scientists and sociologists. This paper introduces a theoretical approach aimed guiding future efforts to realize a provenance capability for social media that is not available today. The guiding vision is the use of social media information itself to realize a useful amount provenance data for information in social media.",
keywords = "data mining, data provenance, information provenance, provenance, provenance path, social media",
author = "Geoffrey Barbier and Huan Liu",
note = "Copyright: Copyright 2011 Elsevier B.V., All rights reserved.; 4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2011 ; Conference date: 29-03-2011 Through 31-03-2011",
year = "2011",
doi = "10.1007/978-3-642-19656-0_39",
language = "English (US)",
isbn = "9783642196553",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "276--283",
booktitle = "Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings",
}