Propagates promotional content through a social network using graph-walk and engagement signals, so promotions reach interested users via organic social connections rather than via broadcast targeting that ignores network topology.
Patent Overview
- Inventor
- Ramanathan V. Guha
- Assignee
- Google LLC
- Filed
- 2009-06-30
- Granted
- 2016-10-11
- Application Number
- US 12/495,729
The Challenge
The Challenge
Promotional content distribution traditionally relies on broadcast targeting: pick demographics, push the message. Social networks add a richer model: trusted connections endorse and share, propagating content through the graph. The system needed to leverage network topology for promotional propagation while respecting authenticity and user consent.
- Broadcast Targeting Ignores Network Topology — Demographic targeting hits a wide audience but misses the social context in which content travels. Network-based propagation reaches interested users through their trusted connections.
- Endorsement Carries More Weight Than Ads — When a trusted friend shares promotional content, it lands differently than an interruption ad. Network propagation harnesses this trust dynamic.
- Propagation Must Respect Authenticity — Manufactured propagation (paying for shares without disclosure) breaks user trust. The system must distinguish authentic propagation from manufactured cascades.
- Users Must Consent To Propagation — Surfacing promotional content via friends requires friend consent. The system needs consent mechanisms and transparent disclosure of promotional propagation.
- Engagement Signals Refine Propagation — Which propagation paths produce engagement and which produce dismissal informs future propagation decisions. The system learns from outcomes.
Innovation
How The System Works
The patent identifies promotional content, walks the social graph from authentic seed users, scores potential recipients by interest and connection strength, propagates content via consenting users along high-affinity paths, captures engagement feedback, and refines propagation as engagement patterns emerge.
- Identify Promotional Content — Content marked or detected as promotional enters the propagation pipeline. Authentic creator endorsement is the starting point.
- Determine Seed Users — Seed users are creators, brand-affiliated users, or organically engaged users who have demonstrated authentic interest. They become the starting points for propagation.
- Walk Social Graph — From seeds, walk outbound social connections. Per connection, score affinity using engagement history, declared interests, and topical alignment.
- Score Recipient Affinity — Per potential recipient, the affinity score combines connection strength to seed plus topical interest in content. High-affinity recipients are preferred.
- Respect Consent And Disclosure — Recipients must have consented to promotional content from connections. Surfaced promotional content includes clear promotional disclosure.
- Surface Through Propagation Paths — Top-affinity recipients receive the content via their feed or notifications. Surfacing format includes attribution to the propagating connection.
- Capture Engagement And Iterate — Engagement (click, share, dismiss) per propagation path feeds back into affinity scoring. The system learns which propagation patterns work.
Graph-Native Promotion
The patent's load-bearing idea is to use social-graph topology as the primary distribution dimension for promotional content. Connections drive reach; affinity drives selection; engagement validates the pattern.
Propagation Through Trusted Connections
Trusted friend endorsement outperforms broadcast targeting. Network-native propagation respects the social context in which users actually consume content.
- Seed-Based Initiation — Authentic seed users start propagation. Manufactured cascades from synthetic sources are filtered out before they begin.
- Affinity-Scored Recipients — Per recipient, affinity combines connection strength and topical interest. High-affinity users receive the content; low-affinity users are excluded.
- Consent And Disclosure — Recipients must consent to promotional content from connections. Surfaced content includes clear promotional disclosure.
Technical Foundation
Technical Foundation
The patent specifies the promotional content detector, the seed-user identifier, the graph-walk engine, the affinity scorer, the consent and disclosure layer, and the engagement feedback pipeline.
- Promotional Content Detector — Identifies promotional content via markers, owner declarations, and learned classifiers. Output is per-content promotional status.
- Seed User Identifier — Identifies authentic seeds: creators, brand-affiliated users, organically engaged users. Synthetic or manipulation-pattern users are excluded.
- Graph Walk Engine — From seeds, walks the social graph efficiently. Walk depth and breadth are bounded to keep latency manageable.
- Affinity Scorer — Per recipient, scores affinity using connection strength, engagement history, declared interests, and topical alignment.
- Consent And Disclosure Layer — Respects per-recipient consent settings. Promotional surface includes clear disclosure of promotional nature.
- Feedback Pipeline — Engagement signals per propagation path feed back into affinity scoring. The system refines continuously.
The Process
The Process
The propagation pipeline runs as a continuous stream from new promotional content to recipient surfacing. Engagement feedback shapes future propagation in near-real-time.
- Promotional Content Enters System — Content marked or detected as promotional enters the propagation pipeline. Quality and authenticity gates apply.
- Identify Seeds — Seed users for the content are identified. Authentic seeds start the propagation; manufactured ones are excluded.
- Walk Graph — From seeds, the engine walks the social graph identifying potential recipients within reachable distance.
- Score Affinities — Per potential recipient, affinity is scored. Sort by affinity.
- Apply Consent Filter — Recipients without consent for promotional propagation are excluded. Surviving recipients become candidates for surfacing.
- Surface To Top Candidates — Content surfaces to top-affinity consenting recipients with promotional disclosure. Surfacing format respects per-platform conventions.
- Capture Engagement — Per-recipient engagement logs. Feedback shapes future propagation paths and affinity scoring.
Quality Control
Quality Control
Wrong propagation produces spam-feeling experiences. The patent specifies safeguards.
- Authentic Seed Validation — Seeds must clear authenticity checks. Synthetic or manipulation-pattern seeds are blocked from initiating propagation.
- Consent Enforcement — Recipient consent is mandatory. Without consent, promotional content cannot surface through the propagation path.
- Disclosure Strictness — Promotional surfacing always includes disclosure. Hidden propagation breaks user trust and is structurally forbidden.
- Affinity Threshold — Low-affinity recipients are excluded. Better to under-distribute than to spam uninterested users.
- Engagement-Driven Backoff — Recipients who consistently dismiss promotional propagation get reduced exposure. Per-user backoff respects expressed disinterest.
Real-World Application
Social-graph propagation primitives appear across Google's social products historically (Google+) and influence modern feed-distribution patterns in Discover, social-network integration features, and brand-related surfacing in search.
- Graph-walk Distribution Method — Content propagates through social graph rather than broadcast targeting. Network topology drives reach.
- Affinity-gated Recipient Selection — Per-recipient affinity scoring filters who sees the content. Low-affinity users are excluded.
- Consent-required User Control — Recipient consent is mandatory. Without consent, propagation cannot reach the user.
Why Social Endorsement Outperforms Broadcast
Content shared by a trusted connection earns more engagement than the same content displayed via broadcast ads. The patent operationalizes this dynamic at scale.
Why Authentic Communities Compound For Brands
Brands that earn authentic engaged communities seed propagation paths that broadcast targeting cannot match. Investment in real audience relationship pays off in graph-native distribution.
<\/section>What This Means for SEO
What This Means for SEO
The patent propagates promotional content through a social graph by walking from authentic seed users along high-affinity, consenting paths and refining on engagement. SEO implication: social distribution rides network topology and trusted endorsement, so building real engaged communities seeds reach that broadcast targeting cannot replicate.
- Trusted Endorsement Outperforms Broadcast — Content shared by a trusted connection earns more engagement than the same content pushed via broadcast. Invest in genuine advocacy and shareable content over interruptive promotion, because the propagation model rewards endorsement, not exposure.
- Authentic Seed Users Start The Walk — Propagation walks the graph from authentic seeds, not bot accounts. Real, recognized voices in your space are the seeds that initiate reach. Cultivating relationships with credible community members is the entry point to graph-native distribution.
- Affinity Selects Recipients — The system scores potential recipients by interest and connection strength along high-affinity paths. Content tightly matched to a community's genuine interests propagates further because affinity is the selection criterion. Generic content travels poorly through the graph.
- Engagement Feedback Refines Reach — Captured engagement refines propagation as patterns emerge. Early engagement signals whether content keeps spreading or stalls. Front-loading quality and relevance so the first recipients engage extends downstream reach.
- Consent Gates Propagation — Content propagates via consenting users. Sharing depends on people choosing to pass it along, which makes shareworthiness the constraint. Build content people are willing to attach their name to, not content that merely seeks reach.
- Communities Are A Distribution Asset — Brands with authentic engaged communities seed propagation paths broadcast targeting cannot match. Treat community-building as infrastructure for distribution, since the graph rewards relationship depth with reach.
- Network-Native Beats Demographic Targeting — The model leverages topology rather than demographic buckets. Distribution that respects how users actually connect outperforms picking demographics and pushing. Map and engage the real network around your topic instead of buying broad exposure.