# Investigating the Effect of Attributes on User Trust in Social Media

## TL;DR

This paper proposes a trust model for social media content based on stability, quality, and credibility, validated through conjoint analysis with 348 responses, highlighting the relative importance of each dimension.

## Contribution

It introduces a new trust model incorporating multiple attributes and evaluates their importance using conjoint analysis, providing insights into user trust factors in social media.

## Key findings

- Credibility is the most important dimension at 35%.
- Quality has the highest importance at 41%.
- The trust model is validated with 348 responses.

## Abstract

One main challenge in social media is to identify trustworthy information. If we cannot recognize information as trustworthy, that information may become useless or be lost. Opposite, we could consume wrong or fake information with major consequences. How does a user handle the information provided before consuming it? Are the comments on a post, the author or votes essential for taking such a decision? Are these attributes considered together and which attribute is more important? To answer these questions, we developed a trust model to support knowledge sharing of user content in social media. This trust model is based on the dimensions of stability, quality, and credibility. Each dimension contains metrics (user role, user IQ, votes, etc.) that are important to the user based on data analysis. We present in this paper, an evaluation of the proposed trust model using conjoint analysis (CA) as an evaluation method. The results obtained from 348 responses, validate the trust model. A trust degree translator interprets the content as very trusted, trusted, untrusted, and very untrusted based on the calculated value of trust. Furthermore, the results show different importance for each dimension: stability 24%, credibility 35% and quality 41%.