Lossan BondeSeverin Dembele2026-08-252026-08-252025-10http://dx.doi.org/10.5772/intechopen.1012726Full text book chapterThis chapter presents a comprehensive and systematic review of the various tech niques and tools used for information extraction (IE), focusing on social media. The aim of the review is triple: (1) identify the techniques and tools used for IE applied to social media, with a recommendation on when to use these techniques and tools; (2) determine what applications along with the social networks use IE from social media; and (3) identify the challenges associated with IE from social media. We combined Kitchenham and the PRISMA methodologies to conduct the systematic review. Guided by a review protocol and quality assessment, 58 papers were selected and analysed. This review highlights the potential of social media information extraction, empha sizing the central role of Machine Learning alongside emerging techniques like trans formers. Applications span sentiment analysis, health, security, marketing, and misinformation detection. Twitter dominates research, though other platforms are studied. Key challenges include ethics, privacy, data scarcity, accuracy, and computa tional costs, necessitating refined methods and ethical focus.enInformation extractionsocial media content processingtransformer-based modelslarge language modelsnatural language processingmachine learningdeep learningBook chapter