ICWSM-11

About us

ICWSM-11 Tutorial Day Program

The ICWSM-11 Committee is pleased to present the Tutorials Day Program for the Fifth International Conference on Weblogs and Social Media (ICWSM-11), to be held July 17, 2011 in Barcelona, Spain. The Tutorials Day provides an opportunity for junior and senior researchers to spend a day before ICWSM freely exploring exciting advances in disciplines outside their normal focus.

John Breslin (NUI Galway), Tutorial Chair
john.breslin@nullnuigalway.ie / @johnbreslin

Tutorials
SA1: How to use Mechanical Turk for Behavioral Research
SA2: Text Mining from User Generated Content | Slides
SP1: Exploratory Network Analysis with Gephi

In this tutorial, we will demonstrate how to conduct behavioral research on Amazon's Mechanical Turk. We will begin by discussing the four main advantages to using Mechanical Turk as a platform for running online studies: access to a large pool of participants, diversity of the participants, low cost of running studies, and faster research cycle. We will outline the fundamental components of a job on Mechanical Turk and discuss the features of the marketplace, including who is doing the work. We will describe how to run three kinds of studies on Mechanical Turk: surveys, experiments with random assignment, and synchronous experiments. We will demonstrate the mechanics of putting a task on Mechanical Turk by creating a survey, posting the job to Mechanical Turk, reviewing the responses and paying the workers. Finally, we will discuss methods for quality assurance and ethical issues surrounding Mechanical Turk.

Winter Mason received a B.S. in Psychology from University of Pittsburgh in 1999 and a Ph.D. in Cognitive Science and Social Psychology from Indiana University in 2007. Since then he has worked at Yahoo! Research in the Human Social Dynamics group.

Siddharth Suri joined the Human & Social Dynamics group at Yahoo! Research in August 2008. Prior to that he was a postdoctoral associate in the computer science department at Cornell University. He earned his Ph.D. in computer and information science from the University of Pennsylvania in January 2007.

The proliferation of documents available on the Web and on corporate intranets is driving a new wave of text mining research and application. Earlier research addressed extraction of information from relatively small collections of well-structured documents such as newswire or scientific publications. Text mining from the other corpora such as the web requires new techniques drawn from data mining, machine learning, NLP and IR. Text mining requires preprocessing document collections (text categorization, information extraction, term extraction), storage of the intermediate representations, analysis of these intermediate representations (distribution analysis, clustering, trend analysis, association rules, etc.), and visualization of the results. In this tutorial we will present the algorithms and methods used to build text mining systems. The tutorial will cover the state of the art in this rapidly growing area of research, including recent advances in unsupervised methods for extracting facts from text and methods used for web-scale mining. We will also present several real world applications of text mining. Special emphasis will be given to lessons learned from years of experience in developing real world text mining systems, including recent advances in sentiment analysis and how to handle user generated text such as blogs and user reviews.

Lyle H. Ungar is an Associate Professor of Computer and Information Science (CIS) at the University of Pennsylvania. He also holds appointments in several other departments at Penn in the Schools of Engineering and Applied Science, Business (Wharton), and Medicine. Dr. Ungar received a B.S. from Stanford University and a Ph.D. from M.I.T. He directed Penn's Executive Masters of Technology Management (EMTM) Program for a decade, and is currently Associate Director of the Penn Center for BioInformatics (PCBI). He has published over 100 articles and holds eight patents. His current research focuses on developing scalable machine learning methods for data mining and text mining.

Ronen Feldman is an Associate Professor of Information Systems at the Business School of the Hebrew University in Jerusalem. He received his B.Sc. in Math, Physics and Computer Science from the Hebrew University and his Ph.D. in Computer Science from Cornell University in NY. He is the author of the book "The Text Mining Handbook" published by Cambridge University Press in 2007.

Gephi is an interactive visualization and exploration software for all kinds of networks and relational data: online social networks, emails, communication and financial networks, but also semantic networks, inter-organizational networks and more. Designed to make data navigation and manipulation easy, it aims to fulfill the complete chain from data importing to aesthetics refinements and interaction. Users interact with the visualization and manipulate structures, shapes and colors to reveal hidden properties. The goal is to help data analysts to make hypotheses, intuitively discover patterns or errors in large data collections.

In this tutorial we will provide a hands-on demonstration of the essential functionalities of Gephi, based on a real case scenario: the exploration of student networks from the "Facebook100" dataset (Social Structure of Facebook Networks, Amanda L. Traud et al, 2011). The participants will be guided step by step through the complete chain of representation, manipulation, layout, analysis and aesthetics refinements. Particular focus will be put on filters and metrics for the creation of their first visualizations. They will be incited to compare the hypotheses suggested by their own exploration to the results actually published in the academic paper afterwards. They finally will walk away with the practical knowledge enabling them to use Gephi for their own projects. The tutorial is intended for professionals, researchers and graduates who wish to learn how playing during a network exploration can speed up their studies.

Sébastien Heymann is a Ph.D. Candidate in Computer Science at Université Pierre et Marie Curie, France. His research at the ComplexNetworks team focuses on the dynamics of realworld networks. He leads the Gephi project since 2008, and is the administrator of the Gephi Consortium.

Julian Bilcke is a Software Engineer at ISC-PIF (Complex Systems Institute of Paris, France). He is a founder and a developer for the Gephi project since 2008.

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