دانلود کتاب یادگیری عمیق برای تجزیه و تحلیل داده های رسانه های اجتماعی

The content of this volume focuses on both theory and practical application of Deep Learning for Social Media Data Analytics. Nowadays, social media platforms are overwhelmed by content constantly being generated by billions of users. These huge volumes of data are mostly unstructured and thus, while offering an enormous potential to influence business, politics, security, and other social aspects, technical challenges emerge that still need to be fully addressed by research. Social media posts, shared in the form of texts, often accompanied by images or videos, have a heterogeneous nature and complex structure due to the wide range of embedded expressions and features, making deep learning and model training rather useful for processing, classifying, analyzing, managing, and storing the large volumes of data involved. This information then becomes resourceful for use on many day-to-day applications. For instance, natural language processing of the text shared in social media allows drawing conclusions often necessary for sentiment analysis or opinion mining, whereas image recognition models are helpful for making sense of posts containing photos with no caption. Likewise, acquiring users’ personal interests and identifying social media influencers is crucial for targeted advertisements, whereas group-centric studies, flow of information, and prediction of links are relevant for recommendations. Effective customer services based on chatbots allow businesses to automate customer services. For instance, interactive question-answering systems are often used for which deep learning techniques are incorporated. In view of its great potential, the research presented in this book emerges from the conviction that there is still much progress to be made towards exploiting deep learning in the context of social media data analytics and its applications to benefit society in a wide range of areas from health to smart cities. The collaborative effort between experts from different fields has enabled the integration of a varied range of approaches to deep learning-based theories, techniques, and methods applied to social media data. It comprises detailed studies that cover some of the most salient areas of research in the field.