Social web permits users to acquire information from anonymous people around the world. This leads to a serious question about the trustworthiness of the information and the sources. During the last decade, numerous models were proposed to adapt social trust to social web. These models aim to assist the user in becoming able to state his opinion about the acquired information and their sources based on their trustworthiness. Usually, opinions can be based on two mechanisms to acquire knowledge: evaluating previous interactions with the source (individual knowledge), and word of mouth mechanism where the user relies on the knowledge of his friends and their friends (collective knowledge). In this paper, we are interested in the impact of using each of these mechanisms on the performance of trust models. Subjective logic (SL) is an extension of probabilistic logic that deals with the cases of lack of evidence. It supplies framework for modelling trust on the web. We use SL in this paper to build and compare two trust models. The first one gives priority to individual opinions, and uses collective opinions only in the case of absence of individual opinions. The second considers only collective opinions permanently, so it always provides the most complete knowledge that leads to improving the performance of the model.