NLP in Social Media Data Processing
N. S. Saba, Kumari Anjali, Akansha Tanu, Aryan Porwal, Ahan Tejaswi, R. Sindhu Rajendran · Advances in computational intelligence and robotics book series · 2025
Natural Language Processing (NLP) represents a cross-disciplinary domain that merges computer science with linguistics, empowering machines to comprehend, interpret, and generate human language. Its significance extends to transformative applications like chatbots, language translation, and sentiment analysis, thereby reshaping the landscape of human-computer interaction. Within the context of social media data analysis, NLP is indispensable for gleaning valuable insights from unstructured text data present on platforms such as Twitter, Facebook and Instagram. NLP serves as a linchpin in sentiment analysis, unraveling emotions in posts and comments. It aids businesses in understanding public opinion, customer satisfaction, and brand perception. Additionally, NLP facilitates trend analysis, user engagement, and personalized marketing by dissecting user-generated content. A notable trend is the fusion of NLP with image and video processing, ushering in multimodal analysis. Explainable AI (XAI) enhances transparency in NLP models, contributing to accountable decision-making. NLP also plays an important role in combating misinformation on social media and assisting companies in refining their engagement strategies. The chapter explores the future of NLP in social media data analysis. It also involves advancements in contextual understanding, accuracy, and adaptability. It also includes incorporation of multimodal analysis and real-time data processing promises deeper insights and informed decision-making. The evolving landscape of NLP in social media analysis ensures refined analyses, responsible implementation, and informed decisions across diverse industries and societal contexts.