Understanding the information propagation process in social networks: Difference between revisions
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Today, social networking platforms such as Facebook, Twitter have become another important ways for information propagation. We directly become aware of more and more latest news from links and tweets our friends shared with us. This is just like the conversation we make with our friends. What is different here is that, with the help of computers, this time we can record every details we are interested in with very little cost. The access to those data makes it possible for us to understand information propagation in a better way. There are already lots of efforts made by researchers . In those efforts, one recent work is to treat each information propagation process as a tree or forests(two or more trees) embedded in the social graph. | Today, social networking platforms such as Facebook, Twitter have become another important ways for information propagation. We directly become aware of more and more latest news from links and tweets our friends shared with us. This is just like the conversation we make with our friends. What is different here is that, with the help of computers, this time we can record every details we are interested in with very little cost. The access to those data makes it possible for us to understand information propagation in a better way. There are already lots of efforts made by researchers . In those efforts, one recent work is to treat each information propagation process as a tree or forests(two or more trees) embedded in the social graph. | ||
In this project, the work will start with reading papers and being familiar with the concepts and methods on the independent cascade model, which is a powerful model for the information propagation process. Then lots of effort is needed for the quantitative analysis on the information cascade trees. We are | In this project, the work will start with reading papers and being familiar with the concepts and methods on the independent cascade model, which is a powerful model for the information propagation process. Then lots of effort is needed for the quantitative analysis on the information cascade trees. We are hoping to find some interesting results on the difference between the large trees (which represents popular news) and the small ones (which represent non-popular news). | ||
If you would like to join this work, please get in contact with us and depending on your experience and educational level, we will check out how you can participate! | If you would like to join this work, please get in contact with us and depending on your experience and educational level, we will check out how you can participate! | ||
== Required Skills == | == Required Skills == | ||
* Good programming skills | * Good programming skills | ||
* Basic understanding of computer networks (e.g., passed course Computer Networks) | * Basic understanding of computer networks (e.g., passed course Computer Networks) | ||
Latest revision as of 15:19, 14 May 2013
Details
| Supervisor: | Narisu Tao |
| Duration: | 3-6 months |
| Type: | Bachelor Thesis or Master Thesis or Student Project |
| Status: | open |
Project Description
In our everyday life, we become aware of new ideas or news happening around us by many kinds of ways. One of the most important ways would be the communication we made with our friends or colleagues in the daily life. This way of information propagation can be imagined as pieces of information flowing in a huge network which is made up by thousands of people. It is definitely very interesting process to understand. However, we hardly can do any research just a few years ago, simply because it is too expensive or just impossible to record every details of the information propagation process in a large scale.
Today, social networking platforms such as Facebook, Twitter have become another important ways for information propagation. We directly become aware of more and more latest news from links and tweets our friends shared with us. This is just like the conversation we make with our friends. What is different here is that, with the help of computers, this time we can record every details we are interested in with very little cost. The access to those data makes it possible for us to understand information propagation in a better way. There are already lots of efforts made by researchers . In those efforts, one recent work is to treat each information propagation process as a tree or forests(two or more trees) embedded in the social graph.
In this project, the work will start with reading papers and being familiar with the concepts and methods on the independent cascade model, which is a powerful model for the information propagation process. Then lots of effort is needed for the quantitative analysis on the information cascade trees. We are hoping to find some interesting results on the difference between the large trees (which represents popular news) and the small ones (which represent non-popular news).
If you would like to join this work, please get in contact with us and depending on your experience and educational level, we will check out how you can participate!
Required Skills
- Good programming skills
- Basic understanding of computer networks (e.g., passed course Computer Networks)