Pradeep Kumar Roy – författare

This reference text presents the important components for grasping the potential of social computing with an emphasis on concerns, challenges, and benefits of the social platform in depth.

Features:

Detailed discussion on social-cyber issues, including hate speech, cyberbullying, and others Discusses usefulness of social platforms for societal needs Includes framework to address the social issues with their implementations Covers fake news and rumor detection models Describes sentimental analysis of social posts with advanced learning techniques

The book is ideal for undergraduate, postgraduate, and research students who want to learn about the issues, challenges, and solutions of social platforms in depth.

This reference text presents the important components for grasping the potential of social computing with an emphasis on concerns, challenges, and benefits of the social platform in depth.

Features:

Detailed discussion on social-cyber issues, including hate speech, cyberbullying, and others Discusses usefulness of social platforms for societal needs Includes framework to address the social issues with their implementations Covers fake news and rumor detection models Describes sentimental analysis of social posts with advanced learning techniques

The book is ideal for undergraduate, postgraduate, and research students who want to learn about the issues, challenges, and solutions of social platforms in depth.

This reference text presents the important components for grasping the potential of social computing with an emphasis on concerns, challenges, and benefits of the social platform in depth.Features:Detailed discussion on social-cyber issues, including hate speech, cyberbullying, and othersDiscusses usefulness of social platforms for societal needsIncludes framework to address the social issues with their implementationsCovers fake news and rumor detection modelsDescribes sentimental analysis of social posts with advanced learning techniquesThe book is ideal for undergraduate, postgraduate, and research students who want to learn about the issues, challenges, and solutions of social platforms in depth.

This reference text presents the important components for grasping the potential of social computing with an emphasis on concerns, challenges, and benefits of the social platform in depth.Features:Detailed discussion on social-cyber issues, including hate speech, cyberbullying, and othersDiscusses usefulness of social platforms for societal needsIncludes framework to address the social issues with their implementationsCovers fake news and rumor detection modelsDescribes sentimental analysis of social posts with advanced learning techniquesThe book is ideal for undergraduate, postgraduate, and research students who want to learn about the issues, challenges, and solutions of social platforms in depth.

This book presents the cutting-edge techniques of social network analytics, focusing on both the positive and negative aspects of social media. While platforms like X, Facebook, and LinkedIn serve as powerful tools for product promotion and crisis management, they also present challenges such as the spread of misinformation, cyberbullying, and hateful content. This book explores these dimensions while highlighting the advancements in social media analytics, specifically through the lens of emerging technologies like artificial intelligence, machine learning, and deep learning. This book is intended for data engineers, researchers, practitioners, and students in the fields of data science, social computing, and artificial intelligence.This book Explores state-of-the-art deep learning methodologies tailored for social network analysis, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Graph Neural Networks (GNNs) to uncover hidden patterns and trends within social media data. Examines the application of large language models, such as GPT (Generative Pre-trained Transformer), in analysing and generating text-based content. Readers will gain practical insights into using these models for content generation, summarisation, and classification tasks. Provides detailed coverage of sentiment analysis techniques, enabling readers to extract valuable insights from user-generated content, helping organisations better understand public opinion. Explores methodologies for detecting communities within social networks, uncovering hidden structures, relationships, and influential nodes or communities. Offers insights into predicting user behaviour on social media platforms, including engagement, preferences, and click-through rates, equipping readers with tools to drive informed decision-making.

This book presents the cutting-edge techniques of social network analytics, focusing on both the positive and negative aspects of social media. While platforms like X, Facebook, and LinkedIn serve as powerful tools for product promotion and crisis management, they also present challenges such as the spread of misinformation, cyberbullying, and hateful content. This book explores these dimensions while highlighting the advancements in social media analytics, specifically through the lens of emerging technologies like artificial intelligence, machine learning, and deep learning. This book is intended for data engineers, researchers, practitioners, and students in the fields of data science, social computing, and artificial intelligence.This book Explores state-of-the-art deep learning methodologies tailored for social network analysis, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Graph Neural Networks (GNNs) to uncover hidden patterns and trends within social media data. Examines the application of large language models, such as GPT (Generative Pre-trained Transformer), in analysing and generating text-based content. Readers will gain practical insights into using these models for content generation, summarisation, and classification tasks. Provides detailed coverage of sentiment analysis techniques, enabling readers to extract valuable insights from user-generated content, helping organisations better understand public opinion. Explores methodologies for detecting communities within social networks, uncovering hidden structures, relationships, and influential nodes or communities. Offers insights into predicting user behaviour on social media platforms, including engagement, preferences, and click-through rates, equipping readers with tools to drive informed decision-making.