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Follows

Follow & Unfollow

The source feed should have a group that has “following” activity selector enabled, for example the built-in timeline group. The target feed should have a group that has “current” activity selector enabled, for example the built-in user group.

# Follow a user
response = self.client.feeds.follow(
    source=f"{self.USER_FEED_TYPE}:{self.test_user_id}",
    target=f"{self.USER_FEED_TYPE}:{self.test_user_id_2}",
)

# Unfollow
unfollow_response = self.client.feeds.unfollow(
    f"{self.USER_FEED_TYPE}:{self.test_user_id}",
    f"{self.USER_FEED_TYPE}:{self.test_user_id_2}",
)

Trying to follow a feed that is already followed will result in an error. Similarly, trying to unfollow a feed that is not followed, will result in an error.

When unfollowing a feed, all previous activities of that feed are removed from the timeline.

Querying Follows

# Query follows
response = self.client.feeds.query_follows(
    limit=10,
    filter={
        "source_feed": f"{self.USER_FEED_TYPE}:{self.test_user_id}"
    }
)

Follows Queryable Built-In Fields

nametypedescriptionsupported operationsexample
source_feedstring or list of stringsThe feed ID that is following$in, $eq{ source_feed: { $eq: 'messaging:general' } }
target_feedstring or list of stringsThe feed ID being followed$in, $eq{ target_feed: { $in: [ 'sports:news', 'tech:updates' ] } }
statusstring or list of stringsThe follow status$in, $eq{ status: { $in: [ 'accepted', 'pending', 'rejected' ] } }
created_atstring, must be formatted as an RFC3339 timestampThe time the follow relationship was created$eq, $gt, $gte, $lt, $lte{ created_at: { $gte: '2023-12-04T09:30:20.45Z' } }

Follow Requests

Some apps require the user’s approval for following them.

# Sara needs to configure the feed with visibility = followers for enabling follow requests
feeds.get_or_create_feed(
    feed_group="user",
    feed_id="sara",
    user_id="sara",
    data={"visibility": "followers"}
)

# Adam requesting to follow the feed
feeds.get_or_create_feed(
    feed_group="timeline",
    feed_id="adam",
    user_id="adam"
)

# Create follow request from adamTimeline to saraFeed
follow_response = feeds.follow(
    source="timeline:adam",
    target="user:sara"
)
print(follow_response["follow"]["status"])  # pending

# Sara accepting
feeds.accept_follow(
    source="timeline:adam",
    target="user:sara",
    follower_role="feed_member"  # optional
)

# or rejecting the request
feeds.reject_follow(
    source="timeline:adam",
    target="user:sara"
)

Push Preferences on Follow

When following a feed, you can set push_preference to control push notifications for future activities from that feed:

  • all - Receive push notifications for all activities from the followed feed
  • none (default) - Don’t receive push notifications for activities from the followed feed

Note: The push_preference parameter controls future notifications from the followed feed, while skip_push controls whether the follow action itself triggers a notification.

Examples: Push Preferences vs Skip Push

Understanding the difference between push_preference and skip_push:

// Scenario 1: Follow a user and receive notifications for their future activities
await timeline.follow("user:alice", {
  push_preference: "all", // You'll get push notifications for Alice's future posts
});

// Scenario 2: Follow a user but don't get notifications for their activities
await timeline.follow("user:bob", {
  push_preference: "none", // You won't get push notifications for Bob's future posts
});

// Scenario 3: Follow a user silently
await timeline.follow("user:charlie", {
  skip_push: true, // Charlie won't get a "you have a new follower" notification
  push_preference: "all", // But you'll still get notifications for Charlie's future posts
});

// Scenario 4: Silent follow with no future notifications
await timeline.follow("user:diana", {
  skip_push: true, // Diana won't know you followed her
  push_preference: "none", // And you won't get notifications for her posts
});

Follow Suggestions

Stream provides intelligent follow suggestions to help users discover feeds they might want to follow based on their activity and social graph.

# Get follow suggestions for a user
suggestions = client.feeds.get_follow_suggestions(
    feed_group_id="user",
    limit=10,
    user_id="john"
)

print(f"Algorithm used: {suggestions.algorithm_used}")
print(f"Duration: {suggestions.duration}")

for suggestion in suggestions.suggestions:
    print(f"Suggested feed: {suggestion.fid}")
    print(f"Name: {suggestion.name}")
    print(f"Description: {suggestion.description}")
    print(f"Follower count: {suggestion.follower_count}")
    print(f"Recommendation score: {suggestion.recommendation_score}")
    print(f"Reason: {suggestion.reason}")
    print(f"Algorithm scores: {suggestion.algorithm_scores}")

Response Fields

The follow suggestions response includes:

  • suggestions: Array of suggested feeds to follow
    • feed: Feed identifier
    • name: Feed name
    • description: Feed description
    • visibility: Feed visibility setting
    • member_count: Number of members
    • follower_count: Number of followers
    • following_count: Number of feeds this feed follows
    • created_at: When the feed was created
    • updated_at: When the feed was last updated
    • recommendation_score: Combined recommendation score (0-1)
    • reason: Human-readable reason for the suggestion
    • algorithm_scores: Individual algorithm scores
  • algorithm_used: The algorithm used to generate suggestions
  • duration: Request processing time

Algorithm Types

Stream’s follow suggestions use a sophisticated multi-algorithm approach with weighted scoring:

  • popularity (Weight: 0.3): Based on follower count and engagement

    • Calculates normalized follower count relative to the most popular feed in your app
    • Score = min(follower_count / max_follower_count, 1.0)
    • Helps surface trending and popular content
  • friend-of-friend (Weight: 0.7): Based on social connections and mutual follows

    • Analyzes how many of your followed feeds also follow the suggested feed
    • Score = mutual_follows / your_total_follows
    • Leverages social proof and network effects
  • combined: Uses multiple algorithms with weighted scoring

    • Final score = (popularity_score × 0.3 + friend_of_friend_score × 0.7) / total_weight
    • Provides balanced recommendations combining popularity and social relevance

Note: Additional algorithms will be added in future releases to provide even more sophisticated recommendations.

Scoring System

The recommendation system uses a sophisticated scoring mechanism:

  1. Individual Algorithm Scores: Each algorithm calculates a score from 0.0 to 1.0
  2. Weighted Combination: Scores are combined using configurable weights
  3. Normalization: Final scores are normalized to ensure fair comparison
  4. Filtering: Only feeds with positive combined scores are included
  5. Ranking: Results are sorted by combined score in descending order

Features

  • Excludes feeds already followed by the user
  • Excludes user’s own feeds
  • Sophisticated algorithm to find feeds to follow
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