Social media generates massive amounts of user-generated-content data. Such data differs from classic data and poses new challenges to data mining. This tutorial presents fundamental issues of social media mining, ranging from network representation to influence/diffusion modeling, elaborate state-of-the-art approaches of processing and analyzing social media data, and show how to utilize patterns to real-world applications, such as recommendation and behavior analytics. The tutorials designed for researchers, students and scholars interested in studying social media and social networks. No prerequisite is required for ICDM participants to attend this tutorial.
@inproceedings{mohammad2013social,
title = {Social Media Mining: Fundamental Issues and Challenges},
author = {Mohammad Ali Abbasi and Huan Liu and Reza Zafarani},
year = {2013},
keywords = {tutorial},
booktitle = {Proceedings of the 2013 IEEE International Conference on Data Mining (ICDM)},
abstract = {Social media generates massive amounts of user-generated-content data. Such data differs from classic data and poses new challenges to data mining. This tutorial presents fundamental issues of social media mining, ranging from network representation to influence/diffusion modeling, elaborate state-of-the-art approaches of processing and analyzing social media data, and show how to utilize patterns to real-world applications, such as recommendation and behavior analytics. The tutorials designed for researchers, students and scholars interested in studying social media and social networks. No prerequisite is required for ICDM participants to attend this tutorial.},
slides = {../tutorials/ICDM13/TutorialICDM13SMM.pdf},
}