Submitted as part of the requirements for Project 4 in the B Tech (I.T.) program at the Cape Peninsula University of Technology.
This study examines the complexities of automatically detecting improper behaviour on online Social Networks. Improper behaviour such as cyber-bullying, cyber-stalking and hate speech detection will be explored. The project considers how technological innovations such as sentiment analysis can restrict the harm caused by improper behaviour and content on online Social Networks.
Nathaniel Brown 209076879
This project was generated with Angular CLI version 1.4.1.
Run ng serve for a dev server. Navigate to http://localhost:4200/. The app will automatically reload if you change any of the source files.
Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|guard|interface|enum|module.
Run ng build to build the project. The build artifacts will be stored in the dist/ directory. Use the -prod flag for a production build.
Run ng test to execute the unit tests via Karma.
Run ng e2e to execute the end-to-end tests via Protractor.
Before running the tests make sure you are serving the app via ng serve.
To get more help on the Angular CLI use ng help or go check out the Angular CLI README.