Conference factories - are you being scammed?: Predatory conferences - part two
Following on from Lou's post last week, today you can learn how to spot being scammed over conferences.
In part one, I looked at why predatory conferences are not just a researcher problem, but a you problem. Now let’s look at what the researchers are saying and how you can easily flag inconsistencies or areas of further research to make a more informed decision. Don’t let predatory conferences borrow your organisation’s credibility; you may never completely recover from the negative brand impact.
What the research community is already seeing
Researchers are sharing their experiences openly in real time. The pattern recognition from people who deal with this regularly is sharp and consistent. From r/academia on Reddit, on a specific conference under scrutiny:
“It’s common for predatory conferences to list renowned keynote speakers who themselves have no clue that their name is used there.”
“No known society, scam.”
“If you had to find them it’s a scam. If they contact you it’s a scam.”
From r/AskAcademia, on paper acceptance timelines:
“Next day acceptance is usually a red flag.”
One researcher posted after receiving an acceptance the same day:
“I applied for an international conference and my paper got accepted the next day, I am not sure about the integrity of the conference.”
The community response was immediate and unambiguous.
On what actually attending one is like:
“I attended a dodgy conference as an undergrad. Not an outright scam in that the conference did exist and we presented a talk and got some experience. But...”
Now that “but” is telling, as you know, there is always a story to come. A study published in Learned Publishing tracked emails received by one researcher over roughly eight years of PhD and postdoctoral work:
1,280 spam emails in total
17% (220) of them were conference invitations
The first arrived three months after they registered for a legitimate international conference. The moment a researcher publishes or registers publicly, they go on to lists.
How a scoring mechanism can work
When we built the suspect event flagging tool, we weighted the criteria to prioritise academic governance and publication integrity above everything else. Visual polish is increasingly meaningless as a signal, particularly now that AI can generate convincing content at scale. The framework has automatic disqualifiers that no other score can override. Since you could use multiple language learning models (LLMs) like ChatGPT, Gemini, Claude and You, the most effective way to do this is to create a “Master Auditor Prompt” that you can paste into these tools, or use to build a “GPT” in OpenAI or a “Gem” in Gemini. For the architectural strategy, you cannot simply give a URL to an LLM and expect a perfect score because many predatory sites block “web crawlers.” Instead, you must instruct the AI to perform a multi-step reasoning chain (Chain of Thought) using its browsing capabilities.
Proceedings and publication quality: highest weight
Are papers published by a recognised academic publisher with unique DOIs?
Are proceedings indexed in Scopus or Web of Science, not just Google Scholar, which is a web crawler rather than a curated index?
Claiming Google Scholar indexing as a prestige marker is itself a red flag that we penalise heavily
Programme committee: high weight
Are committee members recognised experts in the specific subject area?
Can you verify their involvement on their own university profile pages?
We may want to contact named committee members directly
As one Reddit commenter noted:
“I can’t find solid confirmation from universities or speakers that they are actually participating.”
That absence of confirmation is data to include.
Peer review process: high weight
Is the review process clearly described with a realistic timeline?
Minimum four to six weeks for genuine review.
Acceptance within 24 hours automatically results in this category failing. As one community member put it: “Two weeks is an impossible timeline for proper reviews.”
Organiser transparency: meaningful weight
Is the organiser a professional society, university, established non-profit, or a conference factory?
Is a physical office address provided rather than a PO box or virtual office?
Historical records: meaningful weight
Is there a searchable archive of past papers, not just photographs?
Is there continuity of previous editions?
“Very little online presence or history of previous editions” is consistently cited as a signal by researchers
Reputation and indexing: meaningful weight
Is the event endorsed by a recognised academic or professional body?
Are proceedings indexed in credible databases rather than just claimed to be?
Fee structure: moderate weight
Are fees transparent and in line with comparable events in the field?
Legitimate conferences do not charge presenters more than attendees
Marketing practices: lower weight
Unsolicited flattery, “Dear Eminent Scholar” emails and aggressive follow-up are consistent markers
Not definitive alone, but they contribute to the picture
Website quality: lowest weight
Grammar errors, broken links, http rather than https, a subdomain URL, images of the wrong city
These matter but carry low weight because AI now generates polished-looking content that masks everything else
Automatic failure triggers: these override everything else
Listed committee members have no record of the event on their own university profiles
Acceptance promised in fewer than seven days
Google Scholar claimed as the primary indexing standard
Unrelated fields combined in the same programme
No specific venue named, only a city
Any one of these removes a conference from consideration regardless of how it scores elsewhere.
AI has made detection harder
The grammar error giveaway that once made predatory conferences relatively easy to flag is no longer reliable. This needs to be said clearly because it changes the nature of the work.
The Ex Ordo team noted in their 2026 guide that the fake conference problem “has been multiplied with the impact of ChatGPT and other AIs on research integrity”. A Virginia Tech study submitted five papers written entirely by ChatGPT-4 to 256 suspected predatory publishers. Those papers were accepted or published by 55 of them with no meaningful review.
For conference evaluation, this means fake speaker bios generated at scale, committee pages with invented or scraped names, testimonials that read as genuine delegate feedback and acceptance emails in fluent, polished English. The infrastructure for fake academic events is now automated, and it scales in ways handcrafted scams never could.
Nature reported in late 2025 that 21% of manuscript reviews for a major international AI conference were AI-generated. This is not a niche edge case, it really is structural.
It also connects to something I have been writing about more broadly. In my earlier Scholarly Futures piece on why the click is now a legacy metric, I explored how AI is reshaping the discovery and verification of research. The same logic applies when AI agents are doing the initial filtering and recommendation work: content that appears authoritative without being verifiable is precisely what predatory operators are optimising for. As the 2025 Edelman Trust Barometer Special Report noted, what shows up in AI is shaped by reputation, relevance, credibility and clarity. Your conference associations are part of that signal.
Before you commit budget or a speaker to any event
Just take 10 minutes to do a quick sense check, or better yet, copy and paste our list of scoring categories listed in this post or the example prompt and get your AI tool to do the hard work for you:
✓ Search the organiser name and the word “predatory” together before anything else.
✓ Check to see whether there is mention in Reddit or social media channels of the conference or organiser. Reddit’s AI will give a nice summary of discussions.
✓ Check Retraction Watch to see whether a publisher associated with the conference has a history of integrity failures. The Hijacked Journal Checker within Retraction Watch is also worth checking for cloned or stolen conference identities.
✓ If you have access to research integrity tools like DataSeer and Clear Skies, use them to help identify any specific flags of note.
✓ Verify that past proceedings are indexed in Scopus or Web of Science, and who published them.
✓ Check whether any speakers are your authors or on an editorial board, contact a named keynote speaker directly and ask if they are actually involved.
✓ Ask for references from previous sponsors. Legitimate events can have them readily available.
✓ Use Think. Check. Attend., a free structured checklist built specifically for this (Like Think. Check. Submit but for conferences).
✓ For a more comprehensive check, Cabells Predatory Reports is the most rigorously maintained subscription database.
The advice circulating in academic communities is worth taking at face value:
“Generally, I only bother with conferences that are directly advertised by a society or association that is well established as legitimate”.
Ask researchers in your target discipline which conferences they actually attend and trust. Their judgment is the most reliable filter you have.
That was our biggest takeaway: support society and member body conferences and align your brand with their trusted brand. Their revenue goes straight back to the communities you want to reach and benefit.
The researchers we all want to engage are navigating this every single day. Every flattering invitation from an unknown organiser with a suspiciously broad programme is a judgment call they have to make. When we do the same due diligence, it helps the whole ecosystem. When we do not, we make it harder for everyone.
Trust is the only digital asset that actually matters. Surely that must be worth protecting?
Example AI prompt to use and evolve
Try this prompt out in your own AI tool - note this asks to use Google Search as the default search engine, as it was created with Gemini - enhance, develop and build this out. This is only a screening prompt to flag and score based on what we determined to be important in the current landscape, so we take no responsibility or liability for any decisions made using the prompt or tool. Further research by you is always required.
I tested this prompt out on two Royal Society of Chemistry events, one of which was actually a course and the other a conference. I used ChatGPT ‘Thinking’ mode, and it gave the Summer School event a credibility score of 93/100 and the conference 90/100, and both had caveats based on the criteria the prompt stated as part of the scoring included inclusion of conference proceedings. It was interesting watching the logic it wrote on the screen whilst working through the process.
# OBJECTIVE
Perform a weighted, evidence-based audit of an academic conference URL provided by the user to determine its scholarly legitimacy. Disregard aesthetic presentation; prioritize live, verifiable academic and administrative data using your Google Search execution capabilities.
# MANDATORY SEARCH & VERIFICATION WORKFLOW
Upon receiving the URL, you must execute the following live search steps before generating a score:
1. Domain & Entity Search: Determine the legal entity owning the domain. Classify them as either an established non-profit scholarly society/university or a private for-profit “Conference Factory.”
2. Committee Verification: Select three random names from the event’s “Organizing Committee.” Run a search cross-referencing them against their official University faculty profiles. Verify if they list this specific event on their CV or service page.
3. Publication History: Identify the official publisher of past proceedings (e.g., Springer, IEEE, Elsevier, RSC). Search for a valid past volume or sample DOI.
4. Indexing Audit: Check if the conference proceedings are actively indexed in the Scopus Source List or Clarivate Web of Science (CPCI).
- CONSTRAINT: Treat claims of “Google Scholar Indexing” as a negative indicator/red flag.
# SCORING SYSTEM (100 TOTAL POINTS)
- Publication Integrity [50 pts]:
- 50 pts: Confirmed major academic publisher + indexed DOI archive.
- 25 pts: Published in a known but low-impact, non-indexed journal.
- 0 pts: Self-published by the organizer or hidden behind a paywall.
- Academic Governance [30 pts]:
- 30 pts: Committee consists of verifiable, active faculty in this exact niche.
- 0 pts: Committee is unverified, missing, or features faculty from unrelated fields.
- Logistical Transparency [20 pts]:
- 20 pts: Named physical venue (specific hotel or campus) + physical office address.
- 0 pts: Vague location (e.g., “Paris, France”) without a contracted venue.
# AUTOMATIC PENALTIES (APPLY ON DETECTION)
- -50 pts: Misrepresenting partnerships with universities or claiming “unwitting” committee members.
- -30 pts: Promised abstract/peer-review turnaround time of under 7 days.
- -20 pts: “Scope Bloat” (hosting wildly unrelated disciplines under a single umbrella event).
# OUTPUT GENERATION REQUIREMENTS
Return the assessment cleanly using the following headers:
### 📊 Credibility Score: [X/100]
### 🏷️ Classification: [Highly Credible | Credible | Questionable | Predatory]
### 🔍 Evidence Log
- [Publisher status found]
- [Indexing status found]
- [Committee member verification details]
### ⚠️ Detected Red Flags
- [List any penalties applied here]
Test and explore to decide what’s next
Predatory conferences are not just bad events but credibility traps.
A logo, speaker name or sponsorship fee is never neutral, it signals trust. In a research ecosystem under significant pressure, trust matters more than ever. Taking 10 minutes to check who is really behind a conference is not over-cautious, it should be part of your basic brand protection toolkit, and your ethical strategy for researcher and community protection.
If the event is credible, the checks will only strengthen your confidence. If it is not, you have saved more than the budget but have protected the reputation you spent so long building.
Our tool provides an AI-generated risk assessment based on publicly available data. It should be used as a screening tool, but the final decision to submit remains your responsibility. We created it with Google, so it searches data live in Google Search, test it out now and add a conference URL. Why not test one of your own conferences to raise any flags that need addressing.
https://ib-confscore-824288119402.europe-west2.run.app
References
Predatory conferences
Ex Ordo (2026). How to Spot a Fake Conference: 9 Red Flags, exordo.com/blog/9-signs-this-is-a-fake-conference
Tomlinson, O.W. (2022). Analysis of predatory emails in early career academia. Learned Publishing. Published online 11 November 2022, doi.org/10.1002/leap.1500
Rajakumar, H.K. (2025). Seductive emails, dangerous consequences. Postgraduate Medical Journal, 101(1192), 177–179, academic.oup.com/pmj/article/101/1192/177/7908183
AI and predatory publishing
Nature (2025). Major AI conference flooded with peer reviews written fully by AI, nature.com/articles/d41586-025-03506-6
Burgiss, L. et al. (2024). Predatory Publication of AI-Generated Research Papers. NLP and AI for Cyber Security Conference, Lancaster, aclanthology.org/2024.nlpaics-1.1/
Reddit AI summary on predatory conference discussions - https://www.reddit.com/answers/28b8a912-0e94-4a00-a73f-f78d70ef8dc3/?q=predatory+academic+conference&source=SERP&upstreamCID=17396b15-3560-466c-a54c-279f96d99ed9&upstreamIID=52c524e3-dfe6-40e8-b8e7-15e6eef2dc85&upstreamQ=predatory+academic+conference&upstreamQID=e4b2653f-157a-40c6-88e8-4c3397e27744
Checking tools
Cabells Predatory Reports, cabells.com/solutions/predatory-reports
Retraction Watch, retractionwatch.com
Scopus, scopus.com
Think. Check. Attend., thinkcheckattend.org
Web of Science, webofscience.com
Reddit threads referenced
r/academia, reddit.com/r/academia/comments/1rzmr2z/has_you_tell_if_a_conference_is_fake_legit_or/
r/AskAcademia, reddit.com/r/AskAcademia/comments/1szulu7/fake_conference/
Test events
Royal Society of Chemistry (2026). Medicinal chemistry summer school 2026, rsc.org/events/find-an-event/medicinal-chemistry-summer-school-2026
Royal Society of Chemistry (2026). Directing biosynthesis VIII, rsc.org/events/find-an-event/directing-biosynthesis-viii
Further reading
Lou Peck (2026). The Great Decoupling: Why the Click is a Legacy Metric in 2026. Scholarly Futures, scholarlyfutures.substack.com/p/the-great-decoupling-why-the-click
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