Identifying malicious behavior in multi-party bipolar argumentation debates
File(s)
Accepted version
Author(s)
Kontarinis, D
Toni, F
Type
Conference Paper
Abstract
Lately, several works have analyzed potential uses of argumentation in multi-party debates. Usually, the focus of such works is the computation of a collectively “correct” outcome, a challenging task even when the debate’s users truthfully express their beliefs. This work focuses on debates where some users may exhibit specific types of “malicious” behavior: they may lie (bymaking statements they do not believe to hold) and they may hide valuable information (by not making relevant statements they believe to hold). Our approach is the following: firstly, we define “user attributes” which capture different aspects of a user’s behavior in a debate (how active, how opinionated and how classifiable a user has been); then, we build and test experimentally hypotheses that, from the values of these attributes, can predict whether a user has lied and/or hidden valuable information.
Date Issued
2016-04-17
Date Acceptance
2015-12-01
Citation
Lecture Notes in Computer Science, 2016, 9571, pp.267-278
ISBN
9783319335087
ISSN
0302-9743
Publisher
Springer
Start Page
267
End Page
278
Journal / Book Title
Lecture Notes in Computer Science
Volume
9571
Copyright Statement
© Springer Verlag 2016. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-33509-4_21
Sponsor
Commission of the European Communities
Grant Number
FP7 - 314581
Source
13th European Conference, EUMAS 2015, and Third International Conference, AT 2015
Subjects
Artificial Intelligence & Image Processing
08 Information And Computing Sciences
Publication Status
Published
Start Date
2015-12-17
Finish Date
2015-12-18
Coverage Spatial
Athens, Greece