Text Mining and Social Media Mining 2400-DS2TMS
Course contents:
‒ unstructured data analysis - basic concepts and methods
‒ natural language processing and text mining
‒ knowledge representation and information extraction
‒ text categorization
‒ text clustering
‒ text visualization
‒ topic modeling
‒ sentiment analysis
‒ web pages content analysis
‒ social media analysis
‒ patterns and trends in social media usage
‒ information diffusion on social networks
The student’s own research activity during the course also involves review of assigned scientific articles.
Type of course
Course coordinators
Learning outcomes
‒ Student has knowledge about text mining
‒ Student is familiar with text mining methodology
‒ Student is able to use knowledge about text mining to conduct his/her own research
‒ Student processes data independently
‒ Student designs the schedule of his/her own research project
‒ Student conducts his/her own research project
‒ Student is capable of working in groups and co-operating with others
‒ Student is able to formulate his/her point of view and express it
‒ Student expresses his/her research curiosity and openness towards economic phenomenon
Assessment criteria
Evaluation of group projects.
Bibliography
Papers (articles from top journals) provided by lecturers as well as:
Ch. Aggarwal, Ch.X. Zhai (2012). Mining Text Data. Springer. – excerpts [http://www.charuaggarwal.net/text-content.pdf]
Ch. Aggarwal (2011). Social Network Data Analytics, Springer – excerpts [http://www.charuaggarwal.net/socialintro.pdf]
S. Bird, E. Klein, E. Loper (2009). Natural Language Processing with Python. O’Reilly Media. [http://www.nltk.org/book_1ed/]
J. Silge, D. Robinson (2020). Text Mining with R. O’Reilly Media. [https://www.tidytextmining.com/]
R. A. Irizarry (2020). Introduction to Data Science. Data Analysis and Prediction Algorithms with R. CRC Press. [https://rafalab.github.io/dsbook/]
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: