Master data

Investigating the longitudinal effects of different strategies in multistakeholder recommendation scenarios with agent-based simulation
Description:

This project focuses on recommender systems with a particular emphasis on investigating the longitudinal interactions between the different stakeholders of such systems, i.e., users and recommendation service providers. Users are generally interested to receive recommendations that match their needs and interests. Recommendation providers, on the other hand, strive to sustain a business by providing recommendations that are both helpful for users and at the same time serve the organization’s goals. This work employs agent-based modelling to simulate longitudinal dynamics of recommendation systems. Understanding these dynamics shall help to build future recommender systems that are effective in the long term and support the decision-making process of recommendation service providers.

Keywords: Recommender systems, Agent-based Modeling and Simulation, Trust
Short title: Longitudinal Effects of Recommenders
Period: 15.11.2019 - 30.10.2022
Contact e-mail: dietmar.jannach@aau.at
Homepage: -

Employees

Categorisation

Project type Current focus of work
Funding type Other
Research type
  • Fundamental research
  • Applied research
Subject areas
  • 102 - Computer Sciences
  • 502 - Economics
Research Cluster
  • Humans in the Digital Age
Gender aspects Genderrelevance not selected
Project focus
  • Science to Science (Quality indicator: n.a.)
working groups
  • DECIDE (Decision-making in a digital environment)

Funding

No available funding programs

Cooperations

No partner organisations selected