WEB and SOCIAL MEDIA DATA ANALYTICS

AIM

The objective of this course is to provide students with an understanding of concepts and techniques associated with web and social media search, mining and analytics, including concept, principle, architecture, design, implementation, application of web and social media analytic techniques. This course also aims to enable students to discuss and critically evaluate the relative strengths and limitations of the different web search, mining and analytic methods and approaches, to implement and use some of the important web search, mining, and analytics algorithms, apply them to real-world web applications.

CONTENT

This course contains; Introduction to Web and Social Media, Search, Mining and Web Technologies,Introduction to Web and Social Media, Search, Mining and Web Technologies,Information Retrieval Models: Boolean Model,The Terms and postings lists, Dictionary Data Structures, and Tolerant Retrieval, Index Construction and Compression,Scoring, Term Weighting, and Vector Space Model,Components of an IR system and Performance Evaluation of Information Retrieval Systems,Midterm Week,Introduction Web mining, Association Rules and Sequential Patterns ,Supervised Learning,Unsupervised Learning,Social Network Analysis,Opinion Mining and Sentiment Analysis ,Web Usage Mining ,Project presentations.

1. 1

   1. Recognizes the web, social media, web and social network data, mining, and analytics methods.

   Taught by: Project Based Learning Model · Assessed by: Homework

2. 2

   2. Defines how web search engines crawl, index, and rank web content, how network analysis and mining methods work.

   Taught by: Question - Answer Technique, Project Based Learning Model · Assessed by: Oral Exam, Project Task

3. 3

   3. Asseses in-depth knowledge of the fundamental web mining, networks analysis and analytics concepts and techniques.

   Taught by: Problem Solving Method, Self Study Method, Simulation Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Oral Exam, Quiz

4. 4

   4. Describe and utilize a range of techniques for web search, mining, and analytics systems, appreciate the strengths and limitations of various web mining and web search models.

WEEKLY PLAN

1. WEEK 1

   Introduction to Web and Social Media, Search, Mining and Web Technologies

2. WEEK 2

   Introduction to Web and Social Media, Search, Mining and Web Technologies

3. WEEK 3

   Information Retrieval Models: Boolean Model

4. WEEK 4

   The Terms and postings lists, Dictionary Data Structures, and Tolerant Retrieval, Index Construction and Compression

5. WEEK 5

   Scoring, Term Weighting, and Vector Space Model

6. WEEK 6

   Components of an IR system and Performance Evaluation of Information Retrieval Systems

7. WEEK 7

   Midterm Week

8. WEEK 8

   Introduction Web mining, Association Rules and Sequential Patterns

9. WEEK 9

   Supervised Learning

10. WEEK 10

    Unsupervised Learning

11. WEEK 11

    Social Network Analysis

12. WEEK 12

    Opinion Mining and Sentiment Analysis

13. WEEK 13

    Web Usage Mining

14. WEEK 14

    Project presentations

ASSESSMENT

• Rate of Midterm Exam to Success50%
• Rate of Final Exam to Success50%

WORKLOAD

READING

• • Social Media Data Mining and Analytics, Gabor Szabo, Gungor Polatkan, P. Oscar Boykin, Antonios Chalkiopoulos, 2018, Wiley • Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites 1st Edition, Matthew A. Russell, Oreilly. • Mark Levene, An Introduction to Search Engines and Web Navigation, Pearson Education, 2010, ISBN 0321306775 • R. Baeza-Yates, B. Ribeiro-Neto. Modern Information Retrieval: the concepts and technology behind search. Addison-Wesley, 2011. • Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008. • Soumen Chakrabarti, Mining the Web: Discovering Knowledge from Hypertext Data, Morgan-Kaufmann Publishers, 2003, ISBN 1-55860-754-4 • Pierre Baldi,Paolo Frasconi, Padhraic Smyth, Modeling the Internet and the Web, John Wiley and Sons Ltd, 2003, ISBN 0470849061

TEACHING STAFF

• Prof.Dr. Reda ALHAJJCOORDINATOR
• Prof.Dr. Reda ALHAJJ