Social Media Mining (Wintersemester 2018/2019)

Lecturer: Prof. Dr. Christoph Meinel (Internet-Technologien und -Systeme) , M.Sc. Ali Alhosseini (Internet-Technologien und -Systeme)

General Information

• Weekly Hours: 4
• Credits: 6
• Graded: yes
• Enrolment Deadline: 26.10.2018
• Teaching Form: Seminar / Project
• Enrolment Type: Compulsory Elective Module

Programs, Module Groups & Modules

Description

social media analytics refers to the science and discipline of deriving useful hidden insights from massive amounts of semi structured and unstructured data to enable knowledgeable and insightful decision making processes. However, it is increasingly difficult - if not impossible - for the average internet user and weblog enthusiast to grasp the blogosphere’s and social media platforms complexity as a whole, due to thousands of new weblogs and an almost uncountable number of new posts adding up to the before-mentioned collective on a daily basis. Therefore, mining, analyzing, modeling and presenting this immense data collection is of central interest. This could enable the user to detect technical trends, political atmospheric pictures or news articles about a specific topic.

In this seminar, we focus on understanding and analyzing social media streams from different platforms such as (Facebook, Twitter, Instagram, Blogs, Reddit, LinkedIn, Xing) . To reveal potential relationships or visualize the dynamics of social media, various data mining technologies will be used within the selected topics in this seminar.

 Please find the topics presentation here: https://owncloud.hpi.de/index.php/s/JYufb0f7PjjVwjT

Requirements

Good knowledge in

• Operating Systems and Software Engineering
• Internet Basics
• Data Mining Techniques

Literature

Selected publications: 

• 2010, Bross, Justus and Berger, P and Hennig, P and Meinel, Christoph
  RSS-Crawler enhancement for blogosphere-mapping
• 2011, Berger, Philipp and Hennig, Patrick and Bross, Justus and Meinel, Christoph
  Mapping the Blogosphere--Towards a universal and scalable Blog-Crawler
• 2013, Berger, Philipp and Hennig, Patrick and Klingbeil, Thomas and Kohnen, Matthias and Pade, Steffen and Meinel, Christoph
  Mining the Boundaries of Social Networks: Crawling Facebook and Twitter for BlogIntelligence
• 2014, Berger, Philipp and Hennig, Patrick and Detje, Stephan
  BlogSphere-A Topical Map of the Blogosphere
• 2017, BinTareaf, Raad and Berger, Philipp, and Hennig, Patrick and Koall, Sebastian and Kohstall, Jan and Meinel, Christoph
  Information Propagation Speed and Patterns in Social Networks: a Case Study Analysis of German Tweets
• 2017, BinTareaf, Raad and Berger, Philipp, and Hennig, Patrick and Jung, Jaeyoon and Meinel, Christoph
  Identifying Audience Attributes - Predicting Age, Gender and Personality for Enhanced Article Writing
• 2018, BinTareaf, Raad and Berger, Philipp, and Hennig, Patrick and Meinel, Christoph
  Malicious Behavioural Identification in Online Social Networks
• 2018, BinTareaf, Raad and Berger, Philipp, and Hennig, Patrick and Meinel, Christoph
  ASEDS: Towards Automatic Social Emotion Detection System Using Facebook Reactions
• 2018, BinTareaf, Raad and Berger, Philipp, and Hennig, Patrick and Meinel, Christoph
  Personality Exploration System for Online Social Networks: Facebook Brands As a Use Case

Examination

The final evaluation will be based on:

• Initial implementation / idea presentation, 15%
• Final presentation, 25%
• Report, 12-18p LNCS template, 30%
• Implementation, 15%
• Integration, 15%
• Participation in the seminar, paper review (bonus points)

Dates

-Seminar Meetings: Tuesdays, (9.15-10:45). Room A-1.1

-First meetings:

16.10.2018 - Topic Presentations (Lecturers will provide a set of varied topics to be investigated during the seminar)

31.10.2018 - Topic Assignment

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