Tanja Pavleska

Dr. Tanja Pavleska

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
2 January 2023 in Software and Systems Modeling
Verified
Journal Article
Closed access
PDF file
MMMassimiliano Masi
Massimiliano Masi
GSGiovanni Paolo Sellitto
Giovanni Paolo Sellitto
HAHelder Aranha
Helder Aranha
Tanja PavleskaTanja Pavleska
Tanja Pavleska

19 November 2019
Verified
Book Chapter
Closed access
PDF file
Tanja PavleskaTanja Pavleska
Tanja Pavleska
HAHelder Aranha
Helder Aranha
MMMassimiliano Masi
Massimiliano Masi
EGEric Grandry
Eric Grandry
GSGiovanni Paolo Sellitto
Giovanni Paolo Sellitto

31 August 2020
Verified
Book Chapter
Closed access
PDF file
Tanja PavleskaTanja Pavleska
Tanja Pavleska
HAHelder Aranha
Helder Aranha
MMMassimiliano Masi
Massimiliano Masi
GSGiovanni Paolo Sellitto
Giovanni Paolo Sellitto

15 November 2012 in Systemic Practice and Action Research
Verified
Journal Article
Closed access
PDF file
Tanja PavleskaTanja Pavleska
Tanja Pavleska
BJBorka Jerman-Blažič
Borka Jerman-Blažič

3 October 2016 in Behaviour & Information Technology
Verified
Journal Article
Closed access
Tanja PavleskaTanja Pavleska
Tanja Pavleska
BBBorka Jerman Blažič
Borka Jerman Blažič
The advent of social networks opened a myriad opportunities for merging the social character of trust with the technical possibilities offered by the Internet and its availability as a mobile service. While most of the computational trust models aim to detect trustworthy entities, much less attention is paid to how these models are perceived by the users who are the core of the system. This paper delves into the workings of online trust systems under user bias and analyses the user behaviour through biases defined by Prospect theory. By performing empirical study on an existing system, we are able to demonstrate that there is a huge discrepancy between the aim of implementation of the online trust models and the users’ perception of those models. Understanding of this relation by the system designers can reduce complexity and improve the user experience and the system performance. The results imply that the tendency of the users to exhibit cognitive biases is not only the cause, but also the effect from the trust system design. These results and the analysis are then used to propose to the system designers a methodology for user bias identification and mitigation in the form of a Choice architecture for trust systems.

30 November 2025 in Advanced Engineering Informatics
Verified
Journal Article
Open access
Tanja PavleskaTanja Pavleska
Tanja Pavleska