Websites Using Utterances

Utterances is a lightweight, open-source commenting system built on GitHub Issues that allows blog readers to leave comments using their GitHub accounts.

Categories: Comment system

Official website: https://utteranc.es

31 websites using Utterances

• qualys.it
• fensolvitotalsolutions.com
• onlysexfriends.com
• bsoinsur.ru
• rentalbonds.vic.gov.au
• molmove.ro
• thetheatretimes.com
• shaip.com
• drugoedelo.ru
• volunteer.gov
• motorcraft.com
• mollom.com
• mcommemutuelle.com
• apsjobs.gov.au
• swyx.io
• kingdomsalvation.org
• ghanafa.org
• uom.education
• boxtops4education.com
• avrfreaks.net
• tarjetaabc.cl
• oopy.io
• catholic.org.au
• redcrosslearningcenter.org
• banffcentre.ca
• swarajyamag.com
• widencollective.com
• giscus.app
• oireachtas.ie
• wadax-sv.jp
• newyorker.com

Utterances is ranked #19 of 20 in Comment system by website adoption.

Comment system alternatives ranked by popularity

1. Facebook Comments — 8,373 websites
2. Disqus — 1,789 websites
3. Annoto — 0 websites
4. Cackle — 0 websites
5. Chirpy — 0 websites
6. Commento — 0 websites
7. Coral — 0 websites
8. Cove — 0 websites
9. Cusdis — 0 websites
10. Giscus — 0 websites

Technologies commonly used with Utterances

• HSTS — 81% co-occurrence
• Google Font API — 58% co-occurrence
• Google Tag Manager — 55% co-occurrence
• Bootstrap — 52% co-occurrence
• Isotope — 52% co-occurrence
• Open Graph — 48% co-occurrence
• Cloudinary — 45% co-occurrence
• Salesforce — 45% co-occurrence

How WhatStack detects Utterances

WhatStack detects Utterances by analyzing HTTP headers, HTML source code, JavaScript globals, meta tags, cookies, DNS records, and ads.txt entries using signature-based pattern matching across 10 different analyzers.

Frequently Asked Questions

What is Utterances?

Utterances is a lightweight, open-source commenting system built on GitHub Issues that allows blog readers to leave comments using their GitHub accounts.

How many websites use Utterances?

WhatStack has detected Utterances on 31 websites in our database.

How do you detect Utterances?

We analyze HTTP headers, HTML source, JavaScript globals, meta tags, cookies, DNS records, and ads.txt entries to identify Utterances with high accuracy using signature-based pattern matching.