Cyberbullying Detection in Social Media Using Supervised Machine Learning Techniques
With the increasing use of social media platforms such as Facebook, Twitter and Instagram, more and more people are connecting with each other throughout the world. People use these social media platforms to express their individuality, thoughts, ideas and opinions freely. However, a certain grou...
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| Formato: | Thesis |
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Asian University for Women, Chittagong, Bangladesh
2022
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| Acceso en liña: | https://repository.auw.edu.bd/handle/123456789/157 |
| _version_ | 1857448933812338688 |
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| author | Alam, Nabila |
| author_facet | Alam, Nabila |
| author_sort | Alam, Nabila |
| collection | institutional Repository |
| description | With the increasing use of social media platforms such as Facebook, Twitter and Instagram,
more and more people are connecting with each other throughout the world. People use these
social media platforms to express their individuality, thoughts, ideas and opinions freely.
However, a certain group of people abuse this freedom of speech to offend others. This is called
cyberbullying. Some common examples of cyberbullying are posting derogatory or offensive
comments, expressing hostility or aggression online, spreading false rumors, creating fake IDs
etc. In this paper, we propose the use of Supervised Machine Learning techniques to find an
efficient labeling method for effectively predicting and detecting cyberbullying in social media
sites through comparative analysis. |
| format | Thesis |
| id | 123456789-157 |
| institution | Asian University for Women |
| publishDate | 2022 |
| publisher | Asian University for Women, Chittagong, Bangladesh |
| record_format | dspace |
| spelling | 123456789-1572026-02-18T06:09:50Z Cyberbullying Detection in Social Media Using Supervised Machine Learning Techniques Alam, Nabila Cyber bullying, social media, machine learning With the increasing use of social media platforms such as Facebook, Twitter and Instagram, more and more people are connecting with each other throughout the world. People use these social media platforms to express their individuality, thoughts, ideas and opinions freely. However, a certain group of people abuse this freedom of speech to offend others. This is called cyberbullying. Some common examples of cyberbullying are posting derogatory or offensive comments, expressing hostility or aggression online, spreading false rumors, creating fake IDs etc. In this paper, we propose the use of Supervised Machine Learning techniques to find an efficient labeling method for effectively predicting and detecting cyberbullying in social media sites through comparative analysis. Submitted by: Nabila Alam Supervisor: Amina Akhter Asian University for Women Bangladesh May 2018. 2022-12-19T09:38:31Z 2022-12-19T09:38:31Z 2018 Thesis https://repository.auw.edu.bd/handle/123456789/157 application/pdf Asian University for Women, Chittagong, Bangladesh |
| spellingShingle | Cyber bullying, social media, machine learning Alam, Nabila Cyberbullying Detection in Social Media Using Supervised Machine Learning Techniques |
| title | Cyberbullying Detection in Social Media Using Supervised Machine Learning Techniques |
| title_full | Cyberbullying Detection in Social Media Using Supervised Machine Learning Techniques |
| title_fullStr | Cyberbullying Detection in Social Media Using Supervised Machine Learning Techniques |
| title_full_unstemmed | Cyberbullying Detection in Social Media Using Supervised Machine Learning Techniques |
| title_short | Cyberbullying Detection in Social Media Using Supervised Machine Learning Techniques |
| title_sort | cyberbullying detection in social media using supervised machine learning techniques |
| topic | Cyber bullying, social media, machine learning |
| url | https://repository.auw.edu.bd/handle/123456789/157 |
| work_keys_str_mv | AT alamnabila cyberbullyingdetectioninsocialmediausingsupervisedmachinelearningtechniques |