Leveraging Social Media to Detect Online Bullying
Lakshmi Shree C V
, Dr. Shivamurthy R C
Cyberbullying, machine learning algorithms, supervised learning, sentiment analysis, paraphrase, sentiment score, social media.
Cyberbullying has emerged as a pervasive issue in the contemporary digital landscape, inflicting severe consequences on its victims, including mental health challenges and social exclusion. To combat this troubling phenomenon, a project is developed, proposing a machine learning-based approach to effectively identify and stop bullying on social media platforms. By harnessing the potential of advanced machine learning algorithms, the project aims to swiftly identify instances of bullying in real time, allowing for timely alerts to be sent to relevant authorities for necessary action. To train the machine learning model, the project will utilize a comprehensive dataset of social media tweets, manually classified as either bullying or non-bullying. As a result, the model will acquire the ability to efficiently scan new social media content and accurately recognize cyberbullying instances, thereby enabling the implementation of effective intervention and prevention strategies. Through in-depth analysis of the collected data, the project endeavors to enhance public awareness and understanding of cyberbullying while developing practical strategies to combat it. Ultimately, the project seeks to make a significant positive impact in the fight against cyberbullying, fostering a safer online environment that promotes inclusivity and respect for all users. By synergizing machine learning technology with proactive measures, the project aspires to mitigate the deleterious effects of cyberbullying and foster a more compassionate and harmonious online community.
"Leveraging Social Media to Detect Online Bullying", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 8, page no.55 - 62, August-2023, Available :https://ijsdr.org/papers/IJSDR2308009.pdf
Volume 8
Issue 8,
August-2023
Pages : 55 - 62
Paper Reg. ID: IJSDR_208079
Published Paper Id: IJSDR2308009
Downloads: 000347247
Research Area: Computer Science & Technology
Country: Mysore, Karnataka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
