Popularity Prediction of Online Messages
| has title::Popularity Prediction of Online Messages | |
|---|---|
status: ongoing
| |
| Master: | project within::Knowledge Technology and Intelligent Internet Applications |
| Student name: | student name::S.U. Weller |
| Dates | |
| Start | start date:=2011/02/01 |
| End | end date:=2011/07/31 |
| Supervision | |
| Supervisor: | Stefan Schlobach |
| Second reader: | has second reader::Zoltan Szlavik |
| Company: | has company::Buzzcapture |
| Poster: | has poster::Media:Swr500_poster.pdf |
Signature supervisor
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Abstract
Vast numbers of people post messages about their lives and opinions using online media platforms (blogs, forums, microblogs, social-networks, etc). Some of the messages posted are very popular, i.e. get large number of responses, extreme ratings, a lot of views, or make it to official news sites. It would be interesting to be able to predict the popularity of messages at a relatively early stage, which is possible if we have a way of expressing popularity. In order to find a way to express this, the data from the message platforms needs to be normalized. In this presentation, I will outline the methods that will be used in this research to obtain message data from online platforms, and the structure of an ontology in which this data can be uniformly stored (the SIOC ontology, sioc-project.org).
