# Expressing Trust with Temporal Frequency of User Interaction in Online Communities

## TL;DR

This paper introduces a novel trust model for online communities that relies solely on implicit temporal interaction data, demonstrating its effectiveness in mimicking existing reputation systems without requiring private user information.

## Contribution

The study applies the DIBRM model to Reddit and MathOverflow, showing it can replicate reputation behaviors using only temporal interaction data, reducing privacy concerns.

## Key findings

- DIBRM effectively mimics Reddit and MathOverflow reputation behaviors.
- Temporal interaction data suffices for trust modeling without private info.
- The approach enhances privacy while maintaining trust dynamics.

## Abstract

Reputation systems concern soft security dynamics in diverse areas. Trust dynamics in a reputation system should be stable and adaptable at the same time to serve the purpose. Many reputation mechanisms have been proposed and tested over time. However, the main drawback of reputation management is that users need to share private information to gain trust in a system such as phone numbers, reviews, and ratings. Recently, a novel model that tries to overcome this issue was presented: the Dynamic Interaction-based Reputation Model (DIBRM). This approach to trust considers only implicit information automatically deduced from the interactions of users within an online community. In this primary research study, the Reddit and MathOverflow online social communities have been selected for testing DIBRM. Results show how this novel approach to trust can mimic behaviors of the selected reputation systems, namely Reddit and MathOverflow, only with temporal information.