Large knowledge graphs, such as Wikidata, have immense potential to present all shades of thought and diverse opinions in global public discourse. Understanding and identifying different viewpoints form the basis for research and information systems in various knowledge domains. Hence, this study aims to assess the level of inclusion and representation of multiple viewpoints in Wikidata. This paper proposes a new semi-automatic approach for assessing multiple viewpoint representation within Wikidata, focusing on six inherent mechanisms. The preliminary results reveal that the percentage of items with explicitly presented multiple viewpoints is relatively small compared to the overall number of items in the knowledge base. Wikidata and other large knowledge graphs are widely used as training data and ground truth knowledge bases for AI algorithms and smart decision-making systems. Therefore, building knowledge graphs by ethical principles of inclusion and diversity of viewpoints is a crucial issue.