Advancements in NLP for social media analytics
H A Hadi, Ibrahim Mahmood Ibrahim · International Journal of Scientific World · 2025
Natural Language Processing (NLP) is an essential element of computational linguistics and artificial intelligence, enabling fluid interactions between humans and machines. Social networking networks produce substantial volumes of user-generated text daily, offering both opportunities and challenges for NLP researchers. Social media discourse's informal, dynamic, and context-dependent characteristics necessitate specific NLP techniques for precise processing and analysis. This study thoroughly examines NLP applications in social media, including essential tasks such as sentiment analysis, topic modeling, misinformation detection, and hate speech identification. It examines the influence of machine learning and deep learning methodologies, particularly transformer models, on the advancement of NLP capabilities. This study also emphasizes the ethical issues related to NLP-driven social media apps, including data privacy, algorithmic bias, and the regulation of misinformation. The paper continues by discussing emerging research paths, highlighting the necessity for adaptable and ethical NLP solutions in the changing social media environment.