Social activity and structural centrality in online social networks

• 26,000 members of an online network are analyzed by using structural equation modeling.
• The relation between members’ activities and structure measurements is investigated.
• Activity data can be simply observed by analyzing message counts and/or status updates.
• Results indicate that activity data leads to the identification of important members.
• Such knowledge helps marketers to implement effective viral marketing campaigns.

It has become well known that the knowledge about key network members is essential for doing business successfully through online social networking sites. As of now, most studies targeted at identifying key members have used network structural centrality measures. Little emphasis has been placed on member activities to identify key members in a network; even though gathering and utilizing such data is relatively easier than estimation of structural centrality positions. Using a structural equation model on an Internet social networking site data, this study finds that the personal activity status of key members is highly correlated with their structural centrality measures. Managerial implications, limitations, and further research issues are also addressed.