Driving Demand By Managing Network Structure And Network Communication

This paper evaluates how network communication impacts the dynamic evolution of network structures and subsequently online success within an online social network. Current research has already investigated how different structural elements of a social network impact online success. This study aims to extend these findings by investigating the interplay between the content of network communication, network structure and network success. Our data covers 441 personal networks of music artists with dynamic information on music popularity, communication activity as well as network structure. We study the ego-network of music fans connected to the artist by obtaining measures of degree centrality, ego-network density and ego betweenness. We further differentiate four types of networking activities- friendship requests, song uploads and sending comments. Additionally, we coded the communication content within the network along four different categories, i.e. factual information, relationship building, self-revelation and appeal. For statistical inference, we apply quasi maximum likelihood estimation to model the dynamic impact of communication and networking activities on online success. Our results provide substantive insights into the relationship between communication, network structure and network success. First, we show that the communication content can directly impact and sustain online success. Therefore, we extend recent research findings by emphasizing the importance of communication content over and above the volume of communication. In particular, firms should especially align their communication to relationship building, self-revelation and appeals. Second, artists are able to achieve long-term impact on success by shaping their network structure as the network structure in turn drives demand. Specifically, self-revelation and relationship building contribute to network growth as well as to network density, whereas sending information can negatively impact network size evolution