Analysis of viral advertisement re-posting activity in social media

Abstract

More and more businesses use social media to advertise their services. Such businesses typically maintain online social network accounts and regularly update their pages with advertisement messages describing new products and promotions. One recent trend in such businesses’ activity is to offer incentives to individual users for re-posting the advertisement messages to their own profiles, thus making it visible to more and more users. A common type of an incentive puts all the re-posting users into a random draw for a valuable gift. Understanding the dynamics of user engagement into the re-posting activity can shed light on social influence mechanisms and help determine the optimal incentive value to achieve a large viral cascade of advertisement. We have collected approximately 1800 advertisement messages from social media site VK.com and all the subsequent reposts of those messages, together with all the immediate friends of the reposting users. In addition to that, approximately 150000 non-advertisement messages with their reposts were collected, amounting to approximately 6.5 M of reposts in total. This paper presents the results of the analysis based on these data. We then discuss the problem of maximizing a repost cascade size under a given budget.