Skip to content
BITIG
Main menu

Understanding disinformation early.

BITIG studies public digital content with AI and human review, and makes manipulation risks visible at an early stage.

  1. Public content
  2. Filtering
  3. Early signal
  4. Human review
Fig. 1Noise in public content is filtered out and AI brings early signals forward; the final judgement belongs to experts.

Our name

bitig — Old Turkic for “inscription, document, book”.

A name for the lasting written word. We ask the same question for the digital age: how do we tell reliable information from fast-spreading manipulation?

The problem

In the digital world, the hardest thing to undo is a lie that has already spread.

Traditional fact-checking starts after content has spread. But disinformation is more than false information: it is manipulation aimed at the specific sensitivities of specific groups.

Spread

How does a lie spread?

Disinformation rarely reaches the mainstream at once. It usually passes through the same four stages. BITIG looks at the first two, where a correction still works.

  1. Spark

    A claim appears in a small community.

  2. Sensitivity

    The claim attaches to a group's fear, anger or identity.

  3. Amplification

    Accounts share it, reframe it and spread it to new audiences.

  4. Mainstream

    The claim reaches a wide audience; a correction now comes too late.

BITIG focuses here

Traditional fact-checking starts here

Fig. 2An example of how a claim spreads: each square stands for a group of people it has reached.

Approach

Beyond “true or false”

BITIG asks of every piece of content: whom could it affect, and through which sensitivity?

  1. Public data

    Only publicly available content on chosen topics is studied.

  2. Filtering

    Duplicates, noise and off-topic content are removed.

  3. AI analysis

    Language models screen public content; items showing signs of manipulation undergo in-depth analysis.

  4. Cognitive risk score

    Each topic is scored for its potential social impact and the sensitivities it could exploit.

  5. Human review

    Experts review the results; every error becomes a new example for the system.

Fig. 3Content passes through five stages; every error the experts find returns to the system as a new example.

Principles

  • Public content only
  • No individual profiling
  • Minimal data
  • Human review of every result
  • Sensitivity to context, irony and slang

Project

AI-Supported Disinformation Detection and Analysis System

Run at Ankara University, the project started in September 2026 and runs for 12 months. The system is first tested in a narrow, controlled pilot, then widened step by step.

Institution
Ankara University
Duration
12 months · 2026–2027
Field
Social sciences
Department
Computer Education and Instructional Technology

Work

  • Analysis system

    A research system that shows manipulation risks in public content at an early stage.

  • Crisis simulations

    Controlled scenarios that measure how resilient the information space is to generative AI misuse during a crisis.

  • Digital awareness

    Workshops and meetings that help young people recognise manipulation.

Roadmap

From narrow to wide

The system is first tested in a small, controlled pilot; the scope widens as results are validated.

  1. Now

    Pilot

    A narrow, controlled pilot at Ankara University, 2026–2027.

  2. Goal

    Expansion

    More universities, institutions and topics.

  3. Goal

    International

    Research partners from other countries, and other languages.

Fig. 4Each square is a study area; the filled square is today's pilot.

Event

Launch event

BITIG project launch

Public presentation of the project

When
Where
Ankara Kent Konseyi (city council)
Hacı Bayram Mah. Atatürk Bulvarı No: 18, Opera – Altındağ / Ankara

Attendance by invitation.

The project was launched on 24 October 2026 at Ankara Kent Konseyi.

Get involved

Be part of this work

  • Researchers

    Joint work on method, data ethics and evaluation.

  • Institutions

    Pilot areas, crisis simulations and in-house workshops.

  • Students

    Digital awareness workshops and volunteering at events.

Get in touch

Questions

Does BITIG decide what is true?

No. BITIG does not label content true or false; it brings early signals of manipulation risk to experts. The final judgement is always human.

Do you collect my personal data?

Only publicly available content on chosen topics is studied. No individual is profiled, no user is tracked, and data is kept to a minimum.

Is BITIG a company?

No. BITIG is a research project at Ankara University.

Which languages does it cover?

The method is not tied to one language. The pilot starts in a single language; extending it to other languages is the goal.

Contact

Academic and institutional collaboration

Contact us about academic collaboration, institutional meetings or press enquiries.

info@bitig.co