The Astroturfing of Ohio Kratom Comments

Evidence of coordinated template campaigns, repeated advocacy language, and organized messaging that call the raw comment count into question.

Methodology

This analysis examined all 2,370 public comments submitted to the Ohio Board of Pharmacy regarding the proposed scheduling of mitragynine (kratom) as a Schedule I controlled substance. The complete public record was obtained through a public records request.

Data Processing
The official comment record was converted into a structured dataset suitable for computational analysis. Each comment was extracted, normalized, and reviewed using a reproducible workflow implemented in Python.

Text normalization included:

  • removal of formatting artifacts introduced during document conversion
  • conversion to lowercase
  • removal of punctuation
  • normalization of whitespace
  • preservation of substantive comment text for analysis

No comments were excluded based on viewpoint.

Computational Analysis
Rather than relying solely on exact duplicate detection, the comments were analyzed using multiple complementary techniques designed to identify coordinated messaging.

Phrase Fingerprinting
The analysis searched for repeated 10- to 25-word language sequences appearing across multiple submissions. This approach identified recurring advocacy language even when submitters modified surrounding text. For example, repeated sequences containing phrases such as:

  • “Say no to fake kratom reefer madness…”
  • “1980s boomer war on drugs…”
  • “money grab by corrupt bureaucrats…”

were automatically detected through repeated phrase analysis.

Paragraph Similarity Analysis
Each comment was divided into individual paragraphs. Paragraphs were normalized and compared using TF-IDF vectorization and cosine similarity to identify highly similar text blocks reused across multiple comments. Unlike exact duplicate detection, this method detects reused advocacy paragraphs even when introductions, conclusions, or minor wording changes differ.

Template Family Identification
Comments were also evaluated for recurring advocacy themes. Rather than asking whether two comments were identical, the analysis identified recurring messaging families including:

  • chronic pain narratives
  • regulation instead of prohibition
  • natural leaf versus synthetic 7-hydroxymitragynine (7-OH)
  • black market and fentanyl arguments
  • Kratom Consumer Protection Act advocacy
  • pharmaceutical corruption allegations
  • repeated technical pharmacology discussions

Template families were identified using recurring language patterns, repeated paragraphs, and shared policy narratives.

Repeated Technical Language
Special attention was given to repeated scientific and pharmacological discussions. The analysis identified multiple comments containing highly similar explanations involving:

  • G-protein biased agonism
  • β-arrestin signaling
  • respiratory ceiling effects
  • partial agonism

These technical passages appeared across multiple submissions despite otherwise different comment structures.

Interpretation
The purpose of this analysis was not to determine whether individual commenters sincerely held their views. Instead, the objective was to determine whether the public record reflected thousands of independently written submissions or a smaller number of recurring advocacy templates distributed across numerous comments. Because coordinated campaigns frequently encourage supporters to personalize introductions while retaining common advocacy language, exact duplicate detection alone underestimates coordinated messaging. The combination of phrase fingerprinting, paragraph similarity analysis, and template-family identification provides a more complete picture of recurring advocacy patterns within the record.

Limitations
This methodology identifies repeated language, recurring advocacy templates, and highly similar paragraphs. It does not determine the origin of a comment or whether a commenter wrote independently without assistance. Similarity analyses may also underestimate coordinated messaging when comments are extensively rewritten or paraphrased. Accordingly, the results should be interpreted as evidence of recurring messaging patterns within the public comment record rather than proof of the source of any individual submission.

Evidence of Coordinated Template Campaigns

Our independent computational analysis identified numerous recurring advocacy templates distributed throughout the Ohio Board of Pharmacy comment record. Rather than relying solely on exact duplicate detection, the analysis examined repeated language blocks, shared paragraphs, and recurring advocacy themes. This approach identified several organized messaging campaigns.

Reefer Madness Campaign

The analysis identified 86 comments containing the repeated “Reefer Madness” advocacy template. Representative language included:

The analysis also identified 376 repeated phrase windows originating from this same underlying template, demonstrating extensive reuse of the same advocacy language across multiple submissions.

Repeated Technical Advocacy

Multiple comments reused nearly identical technical discussions concerning:

Paragraph-level similarity analysis identified numerous highly similar technical paragraphs that appeared across different comments despite modifications to introductions and conclusions.

Recurring Advocacy Themes

These recurring themes frequently appeared in combination, producing families of comments with different personal introductions but substantially similar policy arguments.

The strongest evidence of coordinated advocacy is not limited to identical comments. It is the repeated appearance of reusable advocacy templates, recurring technical paragraphs, repeated uncommon phrases, and standardized policy narratives distributed across numerous submissions.

The Numbers in Context

The raw comment count—2,370 submissions—overwhelmingly opposed the ban. However, the computational analysis reveals that a substantial portion of these comments derive from organized template campaigns rather than independent, unique testimony.

While the exact classification of every comment is complex, the evidence of coordinated template campaigns is clear and extensive.

Repeated Advocacy Language

Beyond identical copy-pasting, the analysis identified extensive reuse of advocacy language:

These are not isolated examples; they represent recurring advocacy templates that appear across numerous submissions with minor personalization.

Worthington, Ohio Cluster & Fabricated Identities

Hundreds of comments originated from Worthington, Ohio, the home of a kratom retail store chain CEO who was quoted stating his advocacy strategy: “We have a list of everything for people to contact. The Statehouse, DeWine's office, the Board of Pharmacy, and just kind of just keep being a pain and, like, show them, 'Hey, we're not going away.'” These comments share identical talking points, language, and conspiracy narratives.

One comment was submitted under the name “Colonel Charles A. Jones” claiming to be the Superintendent of the Ohio State Highway Patrol—a fabricated identity. The actual Colonel of the OSHP would not submit a public comment in this manner. This is an attempt to create false law enforcement authority for an advocacy position.

Support vs. Oppose: Authenticity Patterns

Oppose Comments

  • Recurring template language: ~92%
  • Genuine-appearing unique narratives: ~8%

1,786+ of 1,941 oppose comments contain repeated advocacy language or templates

Support Comments

  • Recurring template language: ~12%
  • Genuine-appearing unique narratives: ~66%

Support comments are predominantly authentic personal testimonies from grieving families and healthcare professionals

The Bottom Line

The Ohio Board of Pharmacy received 2,370 comments on the proposed kratom ban. Of these:

This is not a public hearing. This is a manufactured public relations campaign designed to deceive regulators into believing there is widespread opposition to a public health measure. The astroturfing is so extensive that it overwhelms the genuine voices of families who have lost loved ones to kratom.

The industry does not want you to know that the vast majority of opposition to kratom bans is manufactured, not organic.

If you support honest public discourse, you must expose this deception. The public deserves to know who is really behind these comments and why they are trying so hard to hide it.