Providing a Framework for Evaluating the Quality of User-generated Content in Social Media

Although with the increasing use of social media, the impact of user-generated content on customer decision-making has increased, no comprehensive research has been done to evaluate the quality of user-generated content on social media so far. Therefore, the purpose of this study is to provide a framework for evaluating the quality of user-generated content on social media. In the first stage of the research, the dimensions and indicators of the quality of user-generated content have been identified and extracted using the meta-synthesis method. The statistical population includes a collection of articles in the related fields collected by a library survey through the Internet. In the second stage, Shannon’s entropy-based approach has been used to prioritize the dimensions and indices extracted, based on the frequency of the obtained codes. According to the results from meta-synthesis, six main categories, 13 dimensions and 207 indicators have been presented as the final framework, which include the following: “content” (including textual and audio-visual dimensions), “validity” (including user credentials and information source credentials), “presentation” (including structure and form dimensions), “integrity” (including accuracy and security dimensions), “background” (including time and demographic dimensions) and “performance” (including usefulness, cognitive and socio-emotional dimensions). This study tries to inform managers and those active in the field of e-commerce, of how to create effective content so that it can benefit them from the new technology of social commerce.