Rigorous frameworks for understanding how human discourse becomes retrievable authority in machine-mediated discovery.
Our research bridges academic theory with practical application, providing operational models for organizations navigating the shift from traditional search to AI-mediated discovery.
Published Papers
Foundational Paper
The Index–Thread Model
A Systems Framework for Discourse-Mediated Discovery
This paper introduces the Index–Thread Model, a systems framework for analyzing how human discourse becomes retrievable authority in machine-mediated discovery. We propose a three-layer architecture: Thread (trust formation), Index (machine retrieval), and Connection (structural mediation). Unlike traditional models that optimize these layers in isolation, we argue that durable discovery requires designing for the Connection Layer.
A Diagnostic Framework for Survivability Assessment
This paper presents a diagnostic framework for evaluating content and community efforts against the survivability criteria defined in the Index–Thread Model. The Connection Layer Audit provides scoring rubrics across five dimensions, gap identification methods for diagnosing structural weaknesses, and prioritization matrices for allocating improvement resources.
A Systematic Approach to Identifying Where Decisions Are Debated
Before you can participate in the Thread Layer, you must know where it exists for your category. Discourse mapping is the systematic identification of environments where your target audience debates solutions, evaluates alternatives, and forms opinions that influence purchasing decisions. This paper provides a methodology for discourse mapping: platform identification techniques, community evaluation criteria, signal detection methods, and monitoring infrastructure requirements.
How Communities Detect and Reject Commercial Participation
Online communities have developed sophisticated detection mechanisms for commercial participation that function like biological immune systems: they identify foreign bodies, trigger rejection responses, and develop memory for future encounters. This paper examines the specific triggers that activate community rejection, the patterns that mark content as commercial, and the behaviors that allow genuine participation to pass through undetected.
How Silent Readers Use Community Content to Make Decisions
Most online community members never post. They read threads, weigh what they find, make decisions, and leave without a trace. These lurkers account for 90% or more of most community audiences, yet their behavior stays hidden. This paper examines how silent readers discover content, judge credibility, build trust across sources, and reach decision thresholds.
When you respond to a community discussion matters as much as what you say. Early responses shape the conversation and accumulate visibility. Late responses get buried. This paper examines the temporal dynamics of community participation: how thread velocity affects response strategy, platform-specific timing patterns, and the relationship between response timing and retrieval probability.
Why People Add "Reddit" to Google Searches and What It Means
A distinct search behavior has emerged over the past decade: users appending "reddit" to their Google queries to surface community discussions instead of traditional results. This modifier behavior represents a deliberate bypass of algorithmically-ranked content in favor of peer discourse. This paper examines the Reddit search modifier phenomenon: its prevalence across categories, the trust dynamics it reveals, its growth trajectory, and its implications for how information credibility is assessed online.
How Reddit Forms Collective Opinions on Products and Companies
Reddit communities form collective opinions with remarkable speed. Within hours of a product launch, pricing change, or company controversy, a discernible "Reddit opinion" often emerges and solidifies. This consensus then persists in community memory and influences how the topic is discussed in future threads. This paper examines the dynamics of consensus formation on Reddit: how quickly opinions crystallize, what factors predict whether a thread will reach consensus or remain contested, the role of early comments in shaping final sentiment, and whether established consensus can be shifted by new information.
How Reddit Threads Accumulate Views Over Months and Years
Reddit threads exhibit two distinct traffic patterns: an initial burst of community attention followed by a long tail of search-driven views that can extend for years. While the initial burst receives most strategic attention, the long tail often delivers more cumulative views and influences more decisions over the thread's lifespan. This paper examines the long tail phenomenon: which thread characteristics predict sustained search traffic, how Google's treatment of Reddit content has evolved, what distinguishes evergreen threads from ephemeral ones, and how the long tail affects the value calculation for community participation.
How Reddit Moderators Distinguish Helpful Participation from Spam
Reddit moderators serve as gatekeepers between commercial interests and community discourse. Their decisions about what constitutes acceptable participation versus removable spam shape which voices reach community audiences. This paper examines how Reddit moderators evaluate potentially promotional content, drawing on a survey of 40 moderators across diverse subreddit categories. The findings reveal consistent patterns: moderators evaluate intent through behavioral signals rather than content alone, prioritize engagement history over content quality, and distinguish creators from marketers based on reciprocity and community investment.
Generative Engine Optimization (GEO) has emerged as a distinct discipline focused on earning citations within AI-generated responses rather than rankings in traditional search results. Reddit occupies a disproportionate role in this landscape: across all major AI platforms, Reddit's citation share grew at least 73% from October 2025 to January 2026, with 24% of all Perplexity citations coming from Reddit alone. This paper examines the mechanisms across the full AI pipeline — from training data ingestion through retrieval-augmented generation to citation selection.
Reddit marketing defies conventional measurement. The activities that generate value — answering questions, sharing experience, participating in discussions — don't produce the tracking signals marketing teams rely on. This paper proposes a measurement framework that replaces traditional campaign attribution with a portfolio of input metrics, leading indicators, intermediate outcomes, and business-level signals specifically designed for community-mediated discovery.
A Structural Comparison of Trust, Cost, and Decision Influence
Marketing teams allocating budget between Reddit participation and paid channels are making the comparison with mismatched frameworks. This paper provides a structural comparison of Reddit organic marketing against five common paid alternatives across five dimensions: trust formation mechanism, decision influence architecture, cost structure and scalability, durability and decay, and competitive dynamics.
Reddit's algorithm determines what over 116 million daily active users see, which comments rise to prominence, and which contributions disappear into collapsed threads. This paper provides a current analysis of how Reddit distributes visibility at three levels: the feed (which posts reach users), the thread (how comments are sorted and displayed), and the discovery system (how content surfaces through search, recommendations, and AI retrieval).
Reddit is not a single community. It is a network of over 100,000 active communities, each with distinct norms, cultures, and trust hierarchies. This paper examines the mechanisms through which Reddit reputation transfers across subreddit boundaries, identifying four types of authority signals — profile-visible, behavioral, content, and community-bridged — and analyzing how each operates in cross-subreddit contexts.
Reddit has become one of the most influential platforms in the consumer decision-making process — not through advertising, but through community discussion. This paper examines how Reddit threads influence purchasing behavior, analyzing the types of purchase-relevant discussions, the mechanisms through which they shape decisions, and the specific role Reddit plays at each stage of the buyer's journey.
What Makes Reddit Comments Retrievable by Search and AI
Between the moment a Reddit comment is posted and the moment its information reaches a user through Google search, AI-generated response, or another user's reference, the content passes through multiple compression events. This paper examines the characteristics determining whether Reddit content survives compression — analyzing search extraction, AI synthesis, and social relay — and provides practical design principles for creating contributions that maintain their value through the full discovery pipeline.