<![CDATA[The use of Social Network Sites (SNS) is increasing to find information during the social restrictions imposed due to the COVID-19 pandemic. The information available on SNS will help individuals understand the situation as it occurs and review preventive measures. However, the information available in several sources can be risky and have a negative impact on SNS users to affect the psychological well-being of users and encourage the emergence of information anxiety. This study aims to identify the factors that can encourage the emergence of information anxiety in SNS users during the COVID-19 pandemic by looking at the effects of two overload factors, namely system feature overload and information overload using the Covariance-based Structural Equation Modeling (CB-SEM) analysis method. The results of the study prove that only one of the two research hypotheses that can be accepted, namely information overload affects information anxiety in users, while the system feature overload hypothesis affects information anxiety in SNS users is rejected. Therefore, this shows that information overload has been proven to encourage the emergence of information anxiety, while system feature overload has not been proven to encourage the emergence of information anxiety in SNS users during the COVID-19 pandemic.]]>
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