Social Media Mining (Wintersemester 2018/2019)
Dozent:
Prof. Dr. Christoph Meinel
(Internet-Technologien und -Systeme)
,
M.Sc. Ali Alhosseini
(Internet-Technologien und -Systeme)
Allgemeine Information
- Semesterwochenstunden: 4
- ECTS: 6
- Benotet:
Ja
- Einschreibefrist: 26.10.2018
- Lehrform: Seminar / Projekt
- Belegungsart: Wahlpflichtmodul
Studiengänge, Modulgruppen & Module
- IT-Systems Engineering
- IT-Systems Engineering
- IT-Systems Engineering
- IT-Systems Engineering
- ISAE: Internet, Security & Algorithm Engineering
- HPI-ISAE-S Spezialisierung
- ISAE: Internet, Security & Algorithm Engineering
- HPI-ISAE-T Techniken und Werkzeuge
- ISAE: Internet, Security & Algorithm Engineering
- HPI-ISAE-K Konzepte und Methoden
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-K Konzepte und Methoden
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-S Spezialisierung
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-T Techniken und Werkzeuge
- CODS: Complex Data Systems
- HPI-CODS-K Konzepte und Methoden
- CODS: Complex Data Systems
- HPI-CODS-T Techniken und Werkzeuge
- CODS: Complex Data Systems
- HPI-CODS-S Spezialisierung
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-C Concepts and Methods
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-T Technologies and Tools
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-S Specialization
Beschreibung
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
Voraussetzungen
Good knowledge in
- Operating Systems and Software Engineering
- Internet Basics
- Data Mining Techniques
Literatur
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
Leistungserfassung
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)
Termine
-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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