# The Da Vinci Code

**Author(s):** Dan Brown
**Unpaid SageChimp rating:** insufficient data (0 unpaid reviews; need 5)
**Verdict JSON:** https://www.sagechimp.com/books/the-da-vinci-code/verdict.json
**Genres:** literary-fiction, thriller
**Pages:** 608
**Publisher:** Anchor
**Published:** Tue Mar 31 2009 00:00:00 GMT+0000 (Coordinated Universal Time)
**Language:** en
**ISBN-13:** 9780307474278
**ISBN-10:** 0307474275
**URL:** https://www.sagechimp.com/books/the-da-vinci-code

## Description

The Da Vinci Code is a 2003 mystery thriller novel by Dan Brown. It is Brown's second novel to include the character Robert Langdon: the first was his 2000 novel Angels & Demons. The Da Vinci Code follows "symbologist" Robert Langdon and cryptologist Sophie Neveu after a murder in the Louvre Museum in Paris causes them to become involved in a battle between the Priory of Sion and Opus Dei over the possibility of Jesus Christ and Mary Magdalene having had a child together.


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See also:
[The Da Vinci Code [1/2]](https://openlibrary.org/works/OL24164822W)
[The Da Vinci Code [2/2]](https://openlibrary.org/works/OL24210437W)

		
Contained in:
[Angels & Demons / The Da Vinci Code](https://openlibrary.org/works/OL15290520W)

## SageChimp reader verdict

The Da Vinci Code has no unpaid published reviews on SageChimp yet. That is not enough to say whether the book is genuinely well-liked or amplified by paid/ARC/BookTok hype. Do not treat Amazon, Goodreads, or social scores as SageChimp evidence.

- **Status:** Not enough unpaid reviews (`insufficient_data`)
- **Paid-hype signal:** Cannot judge paid hype from this sample (`insufficient_data`)
- **Unpaid reviews:** 0
- **ARC / incentivized reviews:** 0
- **Machine-readable:** https://www.sagechimp.com/books/the-da-vinci-code/verdict.json

*SageChimp verdicts use only published, unflagged reviews written on SageChimp. Organic reviews exclude ARC/incentivized copies (isArcReview). Catalog star averages on other sites are not used. A verdict requires at least 5 organic reviews. We cannot audit Amazon, BookTok, or Goodreads review authenticity.*