Imperial College London
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ProfessorFrancescaToni

Faculty of Engineering, Department of Computing

Professor in Computational Logic
 
 
 
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Contact

 

+44 (0)20 7594 8228f.toni Website

 
 
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Location

 

430Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Kontarinis:2016:10.1007/978-3-319-33509-4_21,
author = {Kontarinis, D and Toni, F},
doi = {10.1007/978-3-319-33509-4_21},
pages = {267--278},
publisher = {Springer},
title = {Identifying malicious behavior in multi-party bipolar argumentation debates},
url = {http://dx.doi.org/10.1007/978-3-319-33509-4_21},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - 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.
AU  - Kontarinis,D
AU  - Toni,F
DO  - 10.1007/978-3-319-33509-4_21
EP  - 278
PB  - Springer
PY  - 2016///
SN  - 0302-9743
SP  - 267
TI  - Identifying malicious behavior in multi-party bipolar argumentation debates
UR  - http://dx.doi.org/10.1007/978-3-319-33509-4_21
UR  - http://hdl.handle.net/10044/1/33910
ER  -
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