Social Network Analytics: Empowering Data Engineering with Deep Learning and Large Language Models
暫譯: 社交網絡分析：利用深度學習和大型語言模型增強數據工程
Roy, Pradeep Kumar, Tripathy, Asis Kumar, Kumar, Abhinav
- 出版商: CRC
- 出版日期: 2026-09-03
- 售價: $4,060
- 貴賓價: 9.5 折 $3,857
- 語言: 英文
- 頁數: 236
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 104100690X
- ISBN-13: 9781041006909
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相關分類:
Large language model、Data-mining
尚未上市，無法訂購
商品描述
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. The book explores these dimensions while highlighting the advancements in social media analytics, specifically through the lens of emerging technologies like AI, 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.
- 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.
商品描述(中文翻譯)
這本書介紹了社交網絡分析的尖端技術，專注於社交媒體的正面和負面方面。儘管像 X、Facebook 和 LinkedIn 這樣的平台是產品推廣和危機管理的強大工具，但它們也帶來了挑戰，例如錯誤資訊的傳播、網路霸凌和仇恨內容。本書探討了這些維度，同時突顯社交媒體分析的進展，特別是通過人工智慧（AI）、機器學習和深度學習等新興技術的視角。本書適合數據工程師、研究人員、實務工作者以及數據科學、社會計算和人工智慧領域的學生。
- 探討針對社交網絡分析的最先進深度學習方法，包括卷積神經網絡（CNNs）、循環神經網絡（RNNs）和圖神經網絡（GNNs），以揭示社交媒體數據中的隱藏模式和趨勢。
- 檢視大型語言模型的應用，例如 GPT（生成預訓練變壓器），在分析和生成基於文本的內容方面。讀者將獲得使用這些模型進行內容生成、摘要和分類任務的實用見解。
- 提供情感分析技術的詳細介紹，使讀者能夠從用戶生成的內容中提取有價值的見解，幫助組織更好地理解公眾意見。
- 探討在社交網絡中檢測社群的方法，揭示隱藏的結構、關係以及有影響力的節點或社群。
- 提供有關預測社交媒體平台上用戶行為的見解，包括參與度、偏好和點擊率，為讀者提供驅動明智決策的工具。
作者簡介
Pradeep Kumar Roy earned a BTech degree in Computer Science and Engineering from BPUT University Odisha. He earned his MTech and PhD degrees in Computer Science and Engineering from the National Institute of Technology Patna in 2015 and 2018, respectively. He received a Certificate of Excellence for securing a top rank in the MTech course. He is currently an assistant professor in the Decision Science and Information Systems area, IIM Nagpur Maharashtra, India.
Asis Kumar Tripathy is a professor at the School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India. He has more than ten years of teaching experience. He completed his PhD from the National Institute of Technology, Rourkela. His areas of research interest include wireless sensor networks, cloud computing, the Internet of Things, and advanced network technologies. He has several publications in refereed journals, reputed conferences, and book chapters to his credit.
Abhinav Kumar is currently an assistant professor in the Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology Allahabad (MNNIT Allahabad), Prayagraj, India. Prior to joining MNNIT Allahabad, he worked as an assistant professor in the Department of CSE at IIIT Surat and Siksha "O" Anusandhan Deemed to be University, Bhubaneswar, Odisha. He earned a PhD in Computer Science & Engineering from the Department of CSE of the National Institute of Technology Patna, India.
Dr. Yulei Wu is an associate professor working across the Faculty of Engineering and the Bristol Digital Futures Institute, University of Bristol, UK. He is also affiliated with the Smart Internet Lab and is a member of the High-Performance Networks Research Group. He earned his PhD in Computing and Mathematics and BSc (1st Class Hons.) in Computer Science from the University of Bradford, UK, in 2010 and 2006, respectively. Before joining the University of Bristol, Dr. Wu worked at the University of Exeter and the Chinese Academy of Sciences (CAS).
作者簡介(中文翻譯)
Pradeep Kumar Roy 取得了奧迪沙邦BPUT大學的計算機科學與工程學士學位。他於2015年和2018年分別在國立技術學院帕特納獲得計算機科學與工程的碩士和博士學位。他因在碩士課程中獲得高排名而獲得卓越證書。目前，他是印度馬哈拉施特拉邦納格浦爾IIM的決策科學與資訊系統領域的助理教授。
Asis Kumar Tripathy 是印度維洛爾科技學院資訊科技與工程學院的教授。他擁有超過十年的教學經驗。他在國立技術學院羅爾凱拉完成了博士學位。他的研究興趣包括無線感測器網路、雲計算、物聯網和先進網路技術。他在同行評審的期刊、知名會議和書籍章節上發表了多篇論文。
Abhinav Kumar 目前是印度普拉亞格拉傑的莫蒂拉爾·尼赫魯國立技術學院（MNNIT Allahabad）計算機科學與工程系的助理教授。在加入MNNIT Allahabad之前，他曾在IIIT Surat和奧迪沙邦布巴內斯瓦爾的Siksha 'O' Anusandhan大學擔任計算機科學與工程系的助理教授。他在印度國立技術學院帕特納的計算機科學與工程系獲得博士學位。
Dr. Yulei Wu 是英國布里斯托大學工程學院和布里斯托數位未來研究所的副教授。他同時隸屬於智慧網際網路實驗室，並且是高效能網路研究小組的成員。他於2010年和2006年分別在英國布拉德福德大學獲得計算與數學的博士學位和計算機科學的一級榮譽學士學位。在加入布里斯托大學之前，Dr. Wu曾在埃克塞特大學和中國科學院（CAS）工作。
