Call for Chapters

Abstracts due: February 8th, 2021
Chapters due: May 31st, 2021

We are in the process of editing a book on:
Book title: Social Media Analytics using Graph Databases (TBC)
Publisher: Science Publishers and CRC Press, Taylor & Francis Group
We kindly invite you to submit your work in the form of a book chapter abstract initially, followed by chapter proposals after screening and review.

Objective and Short Description of the Book
With Facebook having 2 billion active users, YouTube following with 1.5 billion, Instagram 800 million and Twitter 330 million, the amount of data published daily is excessive. In 2020 it was estimated that 500 million tweets were published daily, 4.5 billion posts were liked daily, there were 17 billion posts with location tracking in Facebook, and 350 million uploaded daily, with the accumulated number of uploaded photos reaching 250 billion. Every minute 500 hours of new video content is uploaded in YouTube, meaning that 82,2 years of video content is uploaded daily. In Instagram 95 million photos and videos are being uploaded daily. The importance of gathering such rich data, often called “the digital gold rush”, processing it and retrieving information is vital.

This practical book aims at combining various state-of-the-art tools, technologies and techniques to aid understanding and better utilizing the power of Social Media Analytics, Data Mining and Graph Databases. The proposed book will strive to support its readers students, researchers, developers, and simple users involved with Data Science and Graph Databases to master the notions, concepts, techniques, and tools necessary to extract data from social media that facilitate information acquisition, management and prediction.

The provisional contents of Social Media Analytics with Graph Databases will indicatively showcase:

• Social Media analytics with hands on real-world examples
• Data mining tools for optimized knowledge acquisition
• How to crawl and mine data from Social Media
• The advantages of Graph Databases
• Graph Databases use cases
  • Understand common patterns and graph components
  • Model data and find solutions using code-level examples written in Python, SQL and Cypher query language
  • Migrating data from Relational to Graph Databases
  • Use analytical techniques and algorithms to mine Graph Database information

Suggested Topics for Book Chapters
The recommended topics for book chapters include, but are not limited to:

1. Social Media Statistics
2. Relational vs. NoSQL Databases
3. Information Network modeling, NoSQL and Machine Learning
4. Graph Databases Literature Review
5. Migration from RD databases to Neo4j
6. Twitter Domain specific data crawling
7. Sentiment Analysis with Graph Databases
8. Forecasting with Graph Databases
9. Data Mining and Forecasting utilizing regression models

Important Dates
Abstract proposal submission: February 8th. 2021
Initial shortlist with feedback to authors: March 28th, 2021
Book chapter deadline: May 31st, 2021
Book chapter reviews: July 26th, 2021
Camera ready chapters: September 13th, 2021

Please submit a book chapter abstract proposal consisting of:
A) A short title
B) List of author(s), affiliation(s), contact details including email, ORCID number(s)
C) An abstract of up to 150-200 words for the proposed chapter
D) A short description of the proposed chapter and its contents, of up to 400 words
E) A brief CV of up to 200 words per author

This book intends to provide a concise coverage of Social Media Analytics utilizing Graph Databases. Each of the submitted chapters must act as a complete, standalone section and must be original. They should not have been published anywhere else and should not be simultaneously submitted anywhere else for publication.

For queries and chapter abstract proposal submission, kindly send an email to the editor, with subject: “Social Media Analytics using Graph Databases” at: c.tjortjis@ihu.edu.gr
Looking forward to receiving your submissions.

Christos Tjortjis,
Associate Professor
Vice Chair, Dept. of Science and Technology,
School of Science and Technology
International Hellenic University