Science-driven next-generation feedback tracking system (SDFTS)

Main funder

Funds granted by main funder (€)

279 000,00

Project timetable

Project start date: 01/03/2018

Project end date: 29/02/2020


The objective of the project is to investigate the commercialization potential of our methods and tools for the identification of fake user accounts and misinformation detection at social media sites, based on the observed patterns of user activity at these sites.
The goal of this project is to find a customer base for a new service, informed by our research, which will provide the following capabilities: automated detection of fake/stolen identity activity online, unbiased aggregation of feedback of real users/consumers, and targeted information collection in social media tailored to individual customer needs.
1. Understand the business potential of the technology that detects and assesses the risks that fake identity presence and sponsored activity might pose to the reputation, market success, and/or informedness of individuals, social groups and firms:
a. Identify potential customer segments (e.g., political activists, social media sites, news outlets, e-commerce sites, recommendation and consumer report services, security agencies) and understand the specifics of their needs and expectations of such technology,
b. Determine the optimal composition and prioritize the features to be included in services and products supported by such technology,
c. Set the cost structure and pricing model parameters for offering new services and products to customers.
2. Develop a product prototype – currently envisioned as an online service platform (Software as a Service), – identify the needs for its further development, maintenance and support, and present it to several potential customers as a pilot marketing campaign.
Expected Concrete Results:
1. A list of key functions, based on most common customer needs.
2. Newly patented methods, algorithms.
3. A minimally viable, proof-of-concept type product.
4. Business/pricing model.
5. A list of interested customers.

Principal Investigator

Primary responsible unit

Last updated on 2020-26-10 at 10:52