componentLikeButton

The like button can be embedded by other websites. Entities within Metalcon also have a like button. Once a user clicks a like button the system will share this information with his social environment and subscribe the user to information provided by this entity.

Requirements

• Fans: share information with social environment
• Fans: beginner friendly (metalcon already knows what content people surfed on in the past)
• Band / Venue: wants to know fans
• Band / Venue: Promotion
• University: usage behavior / high scaling system (handling many http requests is an interesting research question)

Page metrics from other websites

based on google indices

metal.de: 368.000 pages

• based on their media factsheet
  • 352.000 PageImpressions / month -> 10000 per Day -> 10 per second

metal-hammer.de: 158.000 pages

• factsheet
• 4.918.812 PageImpressions / month -> 170000 per Day -> 120 per second

metal-inside.de: 83.000 pages powermetal.de: 437.000 pages metal1.info: 20.000 pages

requirements

• logging http access
• interaction with like button (like something retrieve friends who like!)
  • retrieval: as often as http logging (only if user cookie is set)
  • create: vary rare
• interaction with news feed
• building a strong (almost realtime) recommender system: http://ssc.io/deploying-a-massively-scalable-recommender-system-with-apache-mahout/

components

• data storage
• entry point (load balancer)
• stupid recommender
  • (who of my friends likes this entities?)
  • who in general likes this page (how many)
• AI recommender
  • (you might also like … (friend, band, city, web site,...))

open questions

• how many estimated requests will have to be handled (read/write/disk access)
• what are the different domains/modules/services within this component
• on which services do the like-button rely on
• concerning security
  • what are common attack vectors
  • how to prevent them

Features

• tracking users on different sites which implemented our metalcon like-button
• display like button with personal information
  • obtain User ID
  • gather context specific information

If user presses the like-button

• assign entity to users "preferences"
• maybe update newsstream of users friends

Technologies

Responsible Developer

• Patrik