Social media platforms (Twitter, Facebook, Instagram, WhatsApp, etc.) have revolutionized the way we communicate with individuals, groups, communities, corporations, government agencies and so on. This, in turn, has changed the established norms and everyday practices of how businesses and government agencies conduct things like sales, marketing, public relations and customer service. Since a large part of this communication occurs in text, Text Mining and Natural Language Processing (NLP) play a fundamental role in building systems that allow us to implement, understand and analyze communication and interaction on these platforms. Their applications are extremely varied and range from sentiment analysis/opinion mining, recommender systems, predictive word models, user profiling and chatbots, to customer support, meme and fake news filtering, automatic summaries and early risk detection.
In this presentation, we analyze such applications of text mining and PLN in social networks, the challenges they present with respect to natural language processing in more formal texts, and the main classical and neural network-based techniques used in the area.