96803 - WEB AND SOCIAL MINING

Learning outcomes

At the end of the course the student is able to choose and use recent methods for web and social Mining. In particular the student is able to extract knowledge from the web and social media by applying machine learning techniques to analyze associations and carry out clickstream, sentiment, text mining and network analysis. The student is able to: - use methods for extracting knowledge from the web; - use recent data mining software for solving practical problems of web mining; and has the experience to carry out independent study and research.

Course contents

1. Aims and steps of web mining
2. Data extraction
   • web scraping
     • structure of web pages, the html language
     • procedures and functions for web scraping
   • use of application programming interfaces (APIs)
     • data extraction from social media using APIs
3. Text mining
   • data pre-processing
     • data cleaning
     • tokenization and part of speech tagging
     • text vectorization
   • exploratory data analysis of text data
   • topic modelling
   • sentiment analysis
4. Analysis of Social Networks
   • network theory
   • centrality measures

Readings/Bibliography

Slides and R scripts of the lessons will be made available on virtuale.unibo.it

Teaching methods

Lectures and laboratory exercises using R software

Assessment methods

The examination is aimed at ascertaining the knowledge and ability to use the tools presented in the lecture.
The assessment of learning involves the presentation of a project in which the various topics covered in class are covered.

Office hours

See the website of Fabrizio Alboni