Write up a short document explaining final project:
- The dataset that will be used for the project. (An overview of what the dataset contains.)
- What type of analysis you will be performing on the dataset.
- Which of the topics in class your project will incorporate.
Expectations for Final Project:
- Choose a web mining topic that interests you. Examples from previous classes include: sentiment analysis, document ranking, classification, clustering, etc.
- Find a data set that supports the topic. For example, a previous group collected data related to election candidate (including website text and tweets). Kaggle.com and kdnuggets.com have some nice datasets available for download.
- Implement the web mining topic you selected in R. You can use some of the lab code as your starting point but I expect that you will submit code that has included topics beyond those that are covered in the labs. For example, we’ll implement a simple sentiment analyzer in R. If you choose this topic, you should implement a more sophisticated algorithm than the one coded during the lab assignment.
- Write a report on your project. This should include the motivation and overview of the project, information about the dataset (data dictionary), information about your approach, the analysis results, and some conclusion. There is no hard requirement on the number of pages, however, historically project reports have been about 10-20 pages long. I’m looking for quality, not quantity. Include graphs and images to support your analysis.
- Along with your report, you should include your R code and a PowerPoint presentation outlining the information contained in the report. You do not have to record a video of the group delivering the PowerPoint presentation. Submitting the PowerPoint file is sufficient.
- Submit a document outlining each group member’s contribution to the final project.