Important Links:

OverLeaf final report

Planning and logs per week

Week 2

Meeting notes:

Discussed which dataset to use. Outcome: use Reddit data

We will have teem meetings every Wednesday after the lecture and every Thursday after our TA meeting.

Decisions:

• Use Python and Flask as back-end
• Front-end to use will be decided base don features we want to visualize
• Use git branching model, where master=stable, all other features are developed in a separate branch. Changes go through a feature review via pull request.
• Focus on analytics primarily

Action items:

Every team member creates 2 paper models of a feature or workflow we want to visualize. Next week we go over the features and discuss any changes

Idea's from brainstorm session

This list is non-exhaustive. If you have other idea, please add it below or into the board.

• Visualize how communities evolved over the years -> timeline
• During election cycle, explore relationship between communities
• Sentiment analysis
• Which ones link the most to each other
• Most popular ones
• Visual link explorer -> seo backlinks
• Wordcloud (realtime, get body content and generate)
• (Related) Feature vector analysis: look at the feature vector of a post, find other posts with similar percentages and where they link
• Chain links analysis: how many levels deep
• Echo chamber detection
• Find related subreddits by looking where they link the most
• Thread brigading detection based on sentiment

Technical Notes:

The dataset contains post id. The content of the post can be retrieved by the following API call: https://www.reddit.com/comments/commentIDhere/.json

Week 3

Meeting 19/02

• Discussed high level paper prototyping for 2 views
• Discussed architecture of the solution and how we will implement it: use Python (Flask) with Pandas for the data processing. Frontend will be up to the implementation teams per view, including D3 and Bokeh for interactive views.
• Discussed what to ask Georgi for next day and get initial design approved.
• Started working on data processing with Pandas to create an API to retrieve the data

Week 4

Meeting 26/02

• Make functional prototype by next week
• Visualization design
• Navigate over time in discreet time intervals on the bottom, support playing animation over time
• Main screen displays graph of interactions between subreddits, where line thickness and color represent different features. Optionally the placement of the graph nodes could convey additional information.
• Hover or click on subreddit shows a radar plot for a given subreddit, showing relationships between these features
• After meeting: continued work on API and started with visualization skeleton first screen

Team Meeting 27/02

• Finalized static API to return data for frontend and began working on producing results in the backend
• Created frontend skeleton structure with D3.js

Week 5

Meeting 05/03

• Prototype looking fine.
• Important to focus on design: colors, user usability/interaction
• Combine the invidual parts of the prototype and design this nicely
• Fix the bar chart with time line soon

Week 6

Meeting 11/03

• Progress was fine
• Having a complete demo ready for next week
• Prepare some guidance for the user
• Use an appropriate color scheme
• Prepare the user stories
• Add feedback actions, like zoom in, highlight selected nodes etc
• Check the app for possible delays
• Bar charts need to be refined and integrated
• Final presentation, report, and video content was discussed
  • motivations
  • how our vizes are different from a regular graph
  • identify passive elements (e.g. background) and active elements (e.g nodes, seach bar)
  • justify color use, element positions, font used, etc.
  • what are the findings of our vizes
  • what we have archived
  • how components communicate with each other

Week 7