Nowadays, the constant development of information and communication technologies (ICTs) has changed the inter-personal interaction, allowing to transfer real experiences to a virtualized medium such as Internet. In this sense, although the space-time barriers of traditional communication are broken and social relationships are strengthened, problems related to adverse behaviors may arise. Bullying, defined as an act that threatens a person's holistic well-being, becomes cyberbullying when it is done over Internet, causing anxiety problems, depression and even suicide attempts. For this reason, it is essential to detect this type of behaviour in time. This research deploys a Spanish cyberbullying prevention system (SPC), which relies on Natural Language Processing (NLP) methods and different machine learning techniques (Naive Bayes, Support Vector Machine and Logistic Regression), using Twitter as the basis for the extraction of knowledge bases or corpus. Several precision metrics and variable corpus sizes are used for the training. The learning results reach a maximum accuracy of 93%, verified through the application of three study cases.
|Title of host publication||IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - Nov 2019|
|Event||2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019 - Valparaiso, Chile|
Duration: 13 Nov 2019 → 27 Nov 2019
|Name||IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019|
|Conference||2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019|
|Period||13/11/19 → 27/11/19|
Bibliographical noteFunding Information:
ACKNOWLEDGMENT The authors would like to thank to the Universidad Politécnica Salesiana, Sede Cuenca, especially to its Research Groups GIHP4C and GITEL for the support provided during this research.
© 2019 IEEE.
- Expert System
- Natural Language Processing
- Sentiment Analysis
- Spanish Language Processing