Problem Statement and Metrics

LinkedIn feed ranking

1. Problem statement

Design a personalized LinkedIn feed to maximize long-term user engagement. One way to measure engagement is user frequency, i.e, measure the number of engagements per user, but it’s very difficult in practice. Another way is to measure the click probability or Click Through Rate (CTR).

On the LinkedIn feed, there are five major activity types:

• Connections (A connects with B)
• Informational
• Profile
• Opinion
• Site-specific
• Intuitively different activities have very different CTRClick Through Rate. This is important when we decide to build models and generate training data.

Category	Example
Connection	Member connector follows member/company, member joins group
Informational	Member or company shares article/picture/message
Profile	Member updates profile, i.e., picture, job-change, etc.
Opinion	Member likes or comments on articles, pictures, job-changes, etc.
Site-Specific	Member endorses member, etc.

2. Metrics design and requirements

Metrics

Offline metrics

• The Click Through Rate (CTR) for one specific feed is the number of clicks that feed receives, divided by the number of times the feed is shown.

$CTR = \frac{number\_of\_clicks}{number\_of\_shown\_times}$ ...