Textual Analysis for the Protection of Children and Teenagers in Social Media - Classification of Inappropriate Messages for Children and Teenagers

Thársis Salathiel de Souza Viana, Marcos de Oliveira, Ticiana Linhares Coelho da Silva, Mário Sérgio Rodrigues Falcão Júnior, Enyo José Tavares Gonçalves

2017

Abstract

Nowadays the Internet is widely used by children and teenagers, where privacy and exposure protection are often not prioritised. This can leave them exposed to paedophiles, who can use a simple chat to start a conversation, which may be the first step towards sexual abuse. In the paper (Falcão Jr. et al, 2016), the authors proposed a tool to detect possible dangerous conversations for a minor in a social network, based on the minor's behaviour. However, the proposed tool does not thoroughly address the analyses of the messages exchanged and attempts to detect the suspicious ones in a chat conversation using a superficial approach. This project aims to extend (Falcão Jr. et al, 2016) by automatically classifying the messages exchanged between a minor and an adult in a social network, hence to separate the ones that seem to come from a paedophile from those that seem to be a normal conversation. An experiment with a real conversation was done to test the effectiveness of the created model.

References

  1. Falcão Jr., M. S. R., Gonçalves, E. J. T., Silva, T. L. C. da S., de Oliveira, M., 2016. Behavioral Analysis for Child Protection in Social Network through Data Mining and Multiagent Systems. In Proceedings of 18th International Conference on Enterprise Information Systems (ICEIS 2016). SCITEPRESS.
  2. Inches, G., Crestani, F., 2012. Overview of the International Sexual Predator Identification Competition at PAN - 2012. In CLEF (Online working notes/labs/workshop). Vol. 30.
  3. Morris, C., 2013. Identifying online sexual predators by svm classification with lexical and behavioral features. Master of Science Thesis, University Of Toronto, Canada.
  4. Leite, J. L. A., 2015. Mineração de textos do twitter utilizando técnicas de classificação. Monografia de Final de Curso. Univercidade Federal do Ceará, Campus Quixadá.
  5. Tan, P., Steinbach, M., Kumar, V., 2005. Introduction to Data Mining. Addison-Wesley, 1° Edition.
  6. McCallum, A., Kamal, N., 1998. A comparison of event models for naive bayes text classification. In Proceedings of AAAI-98 workshop on learning for text categorization. Vol. 752.
  7. Bogdanova, D., Rosso, P., Solorio, T., 2012. On the impact of sentiment and emotion based features in detecting online sexual predators. In Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis. Association for Computational Linguistics.
  8. Metsis., Androutsopoulos, I., Paliouras, G., 2006. Spam filtering with naive bayes-which naive bayes?. CEAS. Vol. 17.
  9. Carletta, J., 1996. Assessing agreement on classification tasks: the kappa statistic. Computational linguistics Vol. 22.2. pp 249-254.
Download


Paper Citation


in Harvard Style

de Souza Viana T., de Oliveira M., Linhares Coelho da Silva T., Rodrigues Falcão Júnior M. and Tavares Gonçalves E. (2017). Textual Analysis for the Protection of Children and Teenagers in Social Media - Classification of Inappropriate Messages for Children and Teenagers . In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-248-6, pages 656-662. DOI: 10.5220/0006370606560662


in Bibtex Style

@conference{iceis17,
author={Thársis Salathiel de Souza Viana and Marcos de Oliveira and Ticiana Linhares Coelho da Silva and Mário Sérgio Rodrigues Falcão Júnior and Enyo José Tavares Gonçalves},
title={Textual Analysis for the Protection of Children and Teenagers in Social Media - Classification of Inappropriate Messages for Children and Teenagers},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2017},
pages={656-662},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006370606560662},
isbn={978-989-758-248-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Textual Analysis for the Protection of Children and Teenagers in Social Media - Classification of Inappropriate Messages for Children and Teenagers
SN - 978-989-758-248-6
AU - de Souza Viana T.
AU - de Oliveira M.
AU - Linhares Coelho da Silva T.
AU - Rodrigues Falcão Júnior M.
AU - Tavares Gonçalves E.
PY - 2017
SP - 656
EP - 662
DO - 10.5220/0006370606560662