Project Draft Overwijk
Contents
Team Members
Project
A decade ago the main channels of news were the news paper, radio and television. News was mainly conveyed by professional journalists that were trained to be objective. Nowadays news spreads around the world over the internet in a much higher pace. Moreover news is more and more conveyed by people without any professional training, e.g. via social networks, blogs, etc. This makes it intractable to consume it all, but more importantly news is more often biased towards a certain perspective. For example a political article written by a republican is likely to reflect a different viewpoint than an article about the same event that is written by a democrat. Another example is the word choice between 'terrorists' and 'freedom fighters'.
Wei-Hao Lin [1] has addressed the problem of predicting perspectives of news videos based on visual concepts. This potentially allows to make people aware of highly biased articles and suggest content from a different perspective. In this project I would like to continue his work. First I want to predict perspectives based on close captions and compare the results with using visual concepts. The next step then would be to combine both types of features to do an even better job.
Dataset
For this project I plan to use the TRECVID 2005 dataset. This contains Arabic, Chinese and English television news from November 2004. I have created the following 5 topics:
- Arafat's death (133 segments)
- Iraq war (134 segments)
- Al Qaeda (307 segments)
- AIDS (139 segments)
- United States elections (203 segments)
All segments have a duration between 30 seconds and 7 minutes. Furthermore each perspective is represented reasonably well in each topic.
References
1. W.-H. Lin and A. Hauptmann, Identifying News Videos' Ideological Perspectives using Emphatic Patterns of Visual Concepts, ACM Multimedia 2009, Beijing, China.
