Big Data and Social Media Analytics
The rise of social networking websites on the Internet has revolutionized the way in which information is shared and consumed online. Twitter, a social networking website created in 2006, was established as a place where people could post and share 140-character messages with one another. This sharing of snippets of information by people about their personal lives and opinions became an intensive and popular online activity termed microblogging. The microblogging feature enabled Twitter to evolve into the role of a serious newswire with reports of credible news appearing on it before anywhere else on the web. Is it possible to effectively spread news articles to a large audience using 140 characters? How does Twitter get used as a platform for the news media agencies to create awareness about the articles they publish on a daily basis? To address these questions, our study of the diffusion patterns of news articles from 12 popular news sources, including BBC, New York Times, and Mashable on Twitter, reveals that a large number of users not only consume and comment on these news articles but also share them in different ways. Combining the methods of network and temporal analyses, we examine and report on how news articles diffuse on Twitter, and how different propagation mechanisms result in different lifespans for news articles.This research appeared in Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, August 2012.
TIME AND LOCATION
Wednesday 3rd of April - from 10-16 in room A-401 The Main Building Aalto University School of Business and
Thursday 4th of April - from 10-15 in room A-401 The Main Building Aalto University School of Business. (Runeberginkatu 14–16, Helsinki).
Sudha Ram is McClelland Professor, Management Information Systems in the Eller College of Management at the University of Arizona, Tucson, AZ 85718. Email: email@example.comOrganizer: Professor Matti Rossi, Aalto University
APRIL 3, 2013
10:00 - 11:30 What is Big Data and Analytics
11:30 - 11:45 Break
11:45 - 12:30 Introduction to Social Media Landscape and Business Models
12:30 - 13:30 Lunch*
13:30 - 15:30 Introduction to Networks and Graphs, Network Measures, and Network Visualizations
15:30 - 16:00 Team Assignment for Day 2
APRIL 4, 2013
10:00 - 11:30 Research Project Example: Network Analysis of News Propagation on Twitter
11:30 - 11:45 Break
11:45 - 12:30 Team Assignment: Selection of Social Media Phenomenon for Analysis and Research Study Design
12:30 - 13:30 Lunch*
13:30 - 14:00: Continue Team Assignment: Research Study Design, Developing Research Questions, Dataset Collection & Network Construction and Analysis Plan
14:00 15:00 Team Presentations of Research Study Design and class discussion/feedback
Note that you can access all of the readings via the ACM and IEEE Digital libraries that your institution will have access to.
1. Devipsita Bhattacharya and Sudha Ram, “Sharing News Article Using 140 Characters: A Diffusion Analysis on Twitter”, IEEE 2012 International Conference on Advances in Social Network Analysis and Mining (ASONAM 2012), pp, 966-971. http://www.computer.org/csdl/proceedings/asonam/2012/4799/00/4799a966-abs.html
2. Wei Wei and Sudha Ram, “Using a Network Analysis Approach for Organizing Bookmarking Tags and Enabling Web Content Discovery”, ACM Transactions on Information Systems, Vol. 3, No. 3, October 2012. http://dl.acm.org/citation.cfm?id=2361260
3. Jun Liu and Sudha Ram, “Who does what: Collaboration patterns in the Wikipedia and their impact on Article Quality”, ACM Transactions on Information Systems, Vol. 2, No. 2, June 2011. http://dl.acm.org/citation.cfm?id=1985352
4. Sinan Aral, Chrysanthis Dellarocas, and David Godes, “ Social Media and Business Transformation: A Framework for Research”, Information Systems Research, Vol. 24, No. 1, March 2013, pp. 3-13.
This seminar is free-of-charge for INFORTE.fi member organization's staff and their PhD-students. For others the participation fee is 750 €. The participation fee includes access to the event and the event materials. Lunch and dinner are not included.
CREDIT POINTS FOR PhD STUDENTS
Doctoral students participating in the seminar can obtain two (2) credit points. This requires participating on both days and completing the assignments given at the seminar.