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Explore natural language processing techniques specifically designed for analyzing social media content in this comprehensive summer school lecture from Johns Hopkins University's Center for Language & Speech Processing. Delve into the unique challenges and opportunities presented by social media text, including handling informal language, abbreviations, emojis, and multilingual content. Learn about specialized preprocessing methods, sentiment analysis approaches, and machine learning models adapted for platforms like Twitter, Facebook, and Instagram. Discover how to extract meaningful insights from user-generated content while addressing issues such as noise, spam detection, and ethical considerations in social media data mining. Gain practical knowledge about building robust NLP pipelines that can handle the dynamic and evolving nature of social media language, and understand the applications of these techniques in areas such as public opinion analysis, trend detection, and social network analysis.
