Social Network Analytics : Empowering Data Engineering with Deep Learning and Large Language Models
Language: English
Published by CRC Press Sep 2026, 2026
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 204.59
Quantity: 2 available
Add to basketItem description from seller
Neuware - 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.…
Seller Inventory # 9781041006909
- Title
- Social Network Analytics : Empowering Data Engineering with Deep Learning and Large Language Models
- Author
- Asis Kumar Tripathy
- Publisher
- CRC Press Sep 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 104100690X
- ISBN 13
- 9781041006909
- Item weight
- 526 grams
- Dimensions
- 234x156x16 mm
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.
"Synopsis" may belong to another edition of this title.
About the Author
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).
"About the title" may belong to another edition of this title.
Shipping rates from Germany to U.S.A.
| Item | 5 to 7 business days | 7 to 10 business days |
|---|---|---|
| First item | £ 26.09 | £ 26.09 |
Payment methods
- Bank Wire Transfer
- Check
- Paypal
Store description
Das Unternehmen AHA-BUCH GmbH: Seit der Gründung von AHA-BUCH im Juli 2005 ist unser Hauptziel, zufriedenen Kunden so schnell und so preisgünstig wie möglich ihren Bücherwunsch zu erfüllen. Unsere Firma beschäftigt 16 Mitarbeiter, die nur ein Ziel kennen: den Kunden und seine Wünsche! Auf über 3700 m2 Fläche haben wir über 100.000 Bücher, Modernes Antiquariat und Spiele auf Lager.
Specialty
Kinderbücher & Kinderhör Casetten, German Books, Software, Natur & Tiere, Ratgeber, Sachbücher, Englische Bücher, Medizin & Gesundheit, Universität & StudiumSeller's business information
AHA-BUCH GmbH
Garlebsen 48
Einbeck, Germany 37574
Terms of sale
Imprint
Seller Info:
AHA-BUCH GmbH
represented by the managing director Christel Glass
Garlebsen 48
37574 Einbeck
Deutschland
Telefon: 055639996039
Telefax: 055639995974
E-Mail: abebooks@aha-buch.de
USt-IdNr.: DE261904229
registered at Commercial register Amtsgerichtes Göttingen
Handelsregisternummer HRB 200691
Alternative dispute resolution:
The European Commission provides a platform for out-of-court online dispute resolution (ODR platform), which can be accessed under https://ec.europa.eu/odr.
We have been a member of the "FairCommerce" initiative since 25.05.2018.
For more information, see www.fair-commerce.de.
Right of withdrawal
If you are a consumer you can withdraw from the contract in accordance with the following. Consumer means any natural person who is acting for purposes which are outside his trade, business, craft or profession.
Information regarding the right of withdrawal
Statutory right to withdraw
You have the right to withdraw from this contract within 14 days without giving any reason.
The withdrawal period will expire after 14 days from the day on which you acquire, or a third party other than the carrier and indicated by you acquires, physical possession of the last good or the last lot or piece.
To exercise the right of withdrawal, electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". We will communicate to you an acknowledgement of receipt of such a withdrawal on a durable medium (e.g. by e-mail) without delay.
To meet the withdrawal deadline, it is sufficient for you to send your communication concerning your exercise of the right of withdrawal before the withdrawal period has expired.
Effects of withdrawal
If you withdraw from this contract, we will reimburse to you all payments received from you, including the costs of delivery (except for the supplementary costs arising if you chose a type of delivery other than the least expensive type of standard delivery offered by us).
We may make a deduction from the reimbursement for loss in value of any goods supplied, if the loss is the result of unnecessary handling by you.
We will make the reimbursement without undue delay, and not later than 14 days after the day on which we are informed about your decision to withdraw from this contract.
We will make the reimbursement using the same means of payment as you used for the initial transaction, unless you have expressly agreed otherwise; in any event, you will not incur any fees as a result of such reimbursement.
We may withhold reimbursement until we have received the goods back, or you have supplied evidence of having sent back the goods, whichever is the earliest.
You shall send back the goods or hand them over to AHA-BUCH GmbH, Einbeck, Germany, without undue delay and in any event not later than 14 days from the day on which you communicate your withdrawal from this contract to us. The deadline is met if you send back the goods before the period of 14 days has expired. You will have to bear the direct cost of returning the goods. You are only liable for any diminished value of the goods resulting from the handling other than what is necessary to establish the nature, characteristics and functioning of the goods.
Exceptions to the right of withdrawal
The right of withdrawal does not apply to:
- The delivery of newspapers, journals or magazines with the exception of subscription contracts; and
- The supply of digital content which is not supplied on a tangible medium (e.g. on a CD or DVD) if you accepted when you placed your order that we could start to deliver it, and that you could not withdraw once delivery had started.
Shipping terms
We ship your order after we received them
for articles on hand latest 24 hours,
for articles with overnight supply latest 48 hours.
In case we need to order an article from our supplier our dispatch time depends on the reception date of the articles, but the articles will be shipped on the same day.
Our goal is to send the ordered articles in the fastest, but also most efficient and secure way to our customers.