Project 2: Text and Geospatial visualization
- Project screenshot (a 1200 x 600 jpg image of your visualization which should be named p1.<your_last_name1><your_last_name2><your_last_name3>.jpg), demo link, and github link are due at 3pm Wednesday, Nov 9th to the TA. The TA will make an html table with your group projects.
- You can update your source code and project report uptill 3pm Friday, Nov 11th.
- This project is 30% of your final grade:
- 20% for design and implementation.
- 5% for in-class presentation.
- 5% for project report on Github.
- Each student needs to send a peer evaluation for other teammates by 3pm Monday, Nov 14th to the TA. This peer evaluation is significant to your individual project grade. One team member can get A but another can get D or Fail. The peer evaluation contains:
- Teammate name.
- Rating from 0 to 5 (5 is best).
- Less than 3-sentence review.
- Project 2 is a group (3 or 4 students) project (assigned here). A leader is also selected by the instructor.
- In this project, students will work on the texts extracted from news/blogs and classified into 4 categories: people names, locations, organizations, and miscellaneous. Each entry also contains the published time/date of the article/blog.
- Students are provided 2 datasets: The Wikinews data (roughly 3.3M) contains 11,267 articles and the Huffington Post data (roughly 29.4M) contains 75,293 political blogs. Students are required to demonstrate their web applications on both datasets.
For a C, you need to visualize terms:
For a B, you need to visualize relationships:
- Show the top 50 popular terms (all categories) in Worldle/Tag Cloud
- Show the monthly frequency of the 50 popular terms over time
- Select a term and highlight its monthly frequency
- Allow users to quickly zoom into a time interval for more details (daily frequencies)
For a A, you need to make discoveries:
- Input a term and display the top 50 related terms (terms appear in the same blog)
- Show relationships between terms
- Mousing over a term highlight related terms (within the 50 terms)
- Plot locations mentioned in news/blogs on a map.
- Your ideas on making visualizations for highlighting patterns within the data
- Automatically highlight importants events.
- Compare topics from 2 sources?
- Tell your stories.
Your code should run on all browsers (Chrome, Safari, Firefox, Explorer,...). No refreshing: Every refresh costs you 1%.
Your application should start out showing some data or an overview and then allow users to add more or request details on demand. Do not start with an empty screen and do not overwhelm viewers by showing a lot of the data right away.
Do not write the application at the last minute to avoid mistakes. Make sure that your code runs and that you have enough time to design intuitive interfaces.
Make sure your code is well commented (this is a good practice since you will work in a team). Instructor may inspect your source code.
Project report on Github (readme file):
Create a 3-minute video showing the use of your application with your voice over. That video should appear on the top of your github readme file.
The video is a good way to show your interactive application in a short amount of time. If you submit a paper to a visualization conference, a video is very useful. It can be also a backup during your presentation just in case of something go wrong.
Add a link to your web-based application (right after the video). You can host it on your github or your ttu personal page.
Clearly explain the duties of each student in your group.
Discrible your application and highlight your findings by screenshots.
The presentation is 10 minutes per group (everyone needs to present). It is 8 minute talk and 2 minute for questions. Make sure that you are ready to talk right after the group in front of you is done.
Please practice your talk. Show the basic functionality and emphasize on why your visualization is different.
© Last revised: Oct 14, 2016