Instagram influencers attributes and parasocial relationship: A dataset from Qatar

Abstract

The dataset investigates how social media influencers’ attributes affect followers’ parasocial relationship. It also examines the mediating role of the parasocial relationship between the social media influencers’ attributes and behavioral intentions. A snowballing sampling technique was used to target Instagram users in Qatar. 574 valid responses were analyzed using Partial least squares structural equation modeling (PLS-SEM). The data provides descriptive information about the essential Instagram influencers among users in Qatar. It also gives new insight into the influencers’ characteristics that will impact consumer behavior the most. The dataset could be very helpful for brands and marketers in Qatar in choosing the most effective influencers. The dataset presents a real value for researchers examining social media consumers behavior specifically in GCC countries context or conducting cross-national comparative studies.

Keywords

• Social media influencer
• Parasocial relationship
• Purchase intention
• WOM
• Partial least squares structural equation modeling PLS-SEM