Network Size and Content Generation on Social Media Platforms

Abstract

Social media has been increasingly integrated into firm operations. Past literature documented the operational value of the content generated by social media users but paid little attention to the users’ incentives to generate and share content. We fill in the gap by linking a user’s social network to her content contribution. Specifically, we distinguish the role of the followee network (the group of people being followed by the user) from the role of the follower network. When a user follows more people, she may spend more time in consuming content than generating content (the substitution effect); she may gain more conflicting information from her followees, obfuscating her incentives to generate content (the information overload effect). Conversely, gathering more information from her followees may facilitate her own content generation (the information sharing effect). Through different identification strategies using multiple datasets from two influential social media platforms, we find that the effects of followees and followers are asymmetric in signs and different in magnitudes. Most notably, a user generates less content with a larger followee network, especially when she faces more time constraints. Our findings suggest social media platforms and companies leveraging social media in their operations incorporate network analytics to promote their user engagement.

Managing contributor performance in knowledge‐sharing communities: A dynamic perspective

“…Third, the value of social information in operations and management, such as using social information to launch remedial actions in healthcare operations (Gour et al, 2022), predict retail sales (Cui et al, 2018), promote conversion and sales rates (Rong et al, 2022), and enhance the management Production and Operations Management of digital platforms (Lu et al, 2021, Wang et al, 2021, Wei et al, 2021Yan, 2020), has received significant attention in recent years. Our study contributes to this stream of research by the value of different types of social information in influencing contributors' performance.…”

“…Similarly, Moqri et al (2018) proposed that following others can increase the chance of a user's being exposed to useful information and, thus, increase contribution levels, but found the effect to be insignificant in the empirical analysis. Wei et al (2021) and Feng et al (2013), on the other hand, suggested that the behavior of followees decrease the contribution probability of a user because it becomes more difficult to synthesize information (information overload) and to provide valuable information (information redundancy). In the organizational context, Leonardi (2015) pointed out that employees can use the enterprise's social networking technology to observe the behavior of others and, thus, gain meta-knowledge (i.e., who knows what and who knows whom).…”

“…Wei et al. (2021) and Feng et al. (2013), on the other hand, suggested that the behavior of followees decrease the contribution probability of a user because it becomes more difficult to synthesize information (information overload) and to provide valuable information (information redundancy).…”

Social Media Moderations, User Ban, and Content Generation: Evidence from Zhihu

“…That is, a Zhihu user can follow and be followed by other users. In this research, we name the user who follows another user in a following relation as the "follower" and the other party the "followee" [29]. The followee's activities on the site, e.g., posting and answering questions, will show up on the follower's news feed.…”

Augmenting fake content detection in online platforms: A domain adaptive transfer learning via adversarial training approach

“…1 Similarly, in early 2020, Twitter started to flag what it judged to be inappropriate content related to COVID‐19. 2 Without proper quality control, the value of the platforms will be reduced (Choi et al., 2018; Cui et al., 2018; Wei et al., 2021; Yan & Pedraza‐Martinez, 2019). Hence, content screening will be one of the most crucial processes of the backend operations for platforms, especially those specializing in content provision.…”