Expert knowledge for automatic detection of bullies in social networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cyberbullying is a serious social problem in online environments and social networks. Current approaches to tackle this problem are still inadequate for detecting bullying incidents or to flag bullies. In this study we used a multi-criteria evaluation system to obtain a better understanding of YouTube users‟ behaviour and their characteristics through expert knowledge. Based on experts‟ knowledge, the system assigns a score to the users, which represents their level of “bulliness‿ based on the history of their activities, The scores can be used to discriminate among users with a bullying history and those who were not engaged in hurtful acts. This preventive approach can provide information about users of social networks and can be used to build monitoring tools to aid finding and stopping potential bullies.
LanguageUndefined
Title of host publication25th Benelux Conference on Artificial Intelligence, BNAIC 2013
Place of PublicationDelft
PublisherTU Delft
Pages57-64
Number of pages8
ISBN (Print)not assigned
StatePublished - Nov 2013
Event25th Benelux Conference on Artificial Intelligence, BNAIC 2013 - Delft University of Technology, Delft, Netherlands
Duration: 7 Nov 20138 Nov 2013
Conference number: 25

Publication series

Name
PublisherTU Delft

Conference

Conference25th Benelux Conference on Artificial Intelligence, BNAIC 2013
Abbreviated titleBNAIC
CountryNetherlands
CityDelft
Period7/11/138/11/13

Keywords

  • EWI-23856
  • Multi-criteria evaluation system
  • METIS-300101
  • IR-88358
  • Cyberbullying
  • Sentiment Analysis

Cite this

Dadvar, M., Trieschnigg, R. B., & de Jong, F. M. G. (2013). Expert knowledge for automatic detection of bullies in social networks. In 25th Benelux Conference on Artificial Intelligence, BNAIC 2013 (pp. 57-64). Delft: TU Delft.
Dadvar, M. ; Trieschnigg, Rudolf Berend ; de Jong, Franciska M.G./ Expert knowledge for automatic detection of bullies in social networks. 25th Benelux Conference on Artificial Intelligence, BNAIC 2013. Delft : TU Delft, 2013. pp. 57-64
@inproceedings{77e9a758994745fba5db9256b3b6f9ae,
title = "Expert knowledge for automatic detection of bullies in social networks",
abstract = "Cyberbullying is a serious social problem in online environments and social networks. Current approaches to tackle this problem are still inadequate for detecting bullying incidents or to flag bullies. In this study we used a multi-criteria evaluation system to obtain a better understanding of YouTube users‟ behaviour and their characteristics through expert knowledge. Based on experts‟ knowledge, the system assigns a score to the users, which represents their level of “bulliness‿ based on the history of their activities, The scores can be used to discriminate among users with a bullying history and those who were not engaged in hurtful acts. This preventive approach can provide information about users of social networks and can be used to build monitoring tools to aid finding and stopping potential bullies.",
keywords = "EWI-23856, Multi-criteria evaluation system, METIS-300101, IR-88358, Cyberbullying, Sentiment Analysis",
author = "M. Dadvar and Trieschnigg, {Rudolf Berend} and {de Jong}, {Franciska M.G.}",
year = "2013",
month = "11",
language = "Undefined",
isbn = "not assigned",
publisher = "TU Delft",
pages = "57--64",
booktitle = "25th Benelux Conference on Artificial Intelligence, BNAIC 2013",
address = "Netherlands",

}

Dadvar, M, Trieschnigg, RB & de Jong, FMG 2013, Expert knowledge for automatic detection of bullies in social networks. in 25th Benelux Conference on Artificial Intelligence, BNAIC 2013. TU Delft, Delft, pp. 57-64, 25th Benelux Conference on Artificial Intelligence, BNAIC 2013, Delft, Netherlands, 7/11/13.

Expert knowledge for automatic detection of bullies in social networks. / Dadvar, M.; Trieschnigg, Rudolf Berend; de Jong, Franciska M.G.

25th Benelux Conference on Artificial Intelligence, BNAIC 2013. Delft : TU Delft, 2013. p. 57-64.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Expert knowledge for automatic detection of bullies in social networks

AU - Dadvar,M.

AU - Trieschnigg,Rudolf Berend

AU - de Jong,Franciska M.G.

PY - 2013/11

Y1 - 2013/11

N2 - Cyberbullying is a serious social problem in online environments and social networks. Current approaches to tackle this problem are still inadequate for detecting bullying incidents or to flag bullies. In this study we used a multi-criteria evaluation system to obtain a better understanding of YouTube users‟ behaviour and their characteristics through expert knowledge. Based on experts‟ knowledge, the system assigns a score to the users, which represents their level of “bulliness‿ based on the history of their activities, The scores can be used to discriminate among users with a bullying history and those who were not engaged in hurtful acts. This preventive approach can provide information about users of social networks and can be used to build monitoring tools to aid finding and stopping potential bullies.

AB - Cyberbullying is a serious social problem in online environments and social networks. Current approaches to tackle this problem are still inadequate for detecting bullying incidents or to flag bullies. In this study we used a multi-criteria evaluation system to obtain a better understanding of YouTube users‟ behaviour and their characteristics through expert knowledge. Based on experts‟ knowledge, the system assigns a score to the users, which represents their level of “bulliness‿ based on the history of their activities, The scores can be used to discriminate among users with a bullying history and those who were not engaged in hurtful acts. This preventive approach can provide information about users of social networks and can be used to build monitoring tools to aid finding and stopping potential bullies.

KW - EWI-23856

KW - Multi-criteria evaluation system

KW - METIS-300101

KW - IR-88358

KW - Cyberbullying

KW - Sentiment Analysis

M3 - Conference contribution

SN - not assigned

SP - 57

EP - 64

BT - 25th Benelux Conference on Artificial Intelligence, BNAIC 2013

PB - TU Delft

CY - Delft

ER -

Dadvar M, Trieschnigg RB, de Jong FMG. Expert knowledge for automatic detection of bullies in social networks. In 25th Benelux Conference on Artificial Intelligence, BNAIC 2013. Delft: TU Delft. 2013. p. 57-64.