Mining Lurkers in Online Social Networks

This chapter opens the brief by introducing the readers to its research subject. The chapter provides main motivations and implications for studying a number of problems related to the theme of this brief, which will be elaborated in the subsequent eight chapters. The chapter also clarifies the target audience of scope of this brief, and finally provides acknowledgements. Research in Web and network sciences has witnessed a large body of studies traditionally focusing on online users that take on either a “positive” or a “negative” role, i.e., influencers, experts, trendsetters, on the one side, and spammers, trolls, bogus users, on the other side. While the importance of studying these central figures has been widely recognized, less attention has been paid to the fact that all largescale online social networks (OSNs) are characterized by a participation inequality principle. This principle is commonly expressed by a hypothetical “1:9:90” rule [1] stating that while only about 1% of users (which include influential users, opinion leaders, etc.) create the vast majority of social content, and another 9% are occasional contributors (i.e., they may post, comment, or like from time to time), the remaining 90% of users just observe ongoing discussions, read posts, watch videos, and so on. In other words, the real audience of OSNs does not actively contribute; rather, it takes on a silent role. Clearly, the actual proportions vary from network to network (e.g., [2, 4, 7]), but this disequilibrium between the niche of super contributors and the crowd of silent users is common to all large-scale OSNs. As a fundamental premise, this kind of users should not be trivially regarded as totally inactive users, i.e., registered users who do not use their account to join the OSN. Actually, a silent user can be perceived as someone who gains benefit from others’ information and services without giving back to the OSN. For this reason, such users are also called lurkers. Understanding and mining lurkers is very arduous. The definition of lurker itself is multifaceted [5], as the meanings and interpretations of lurking may range from negative ones (e.g., lurkers might be seen as a menace for the cyberspace when they maliciously feed on others’ intellects) to neutral (e.g., when they are seen as harmless and reflect a subjective reticence to actively join the OSN) to even positive © The Author(s), under exclusive license to Springer Nature Switzerland AG 2018 A. Tagarelli, R. Interdonato, Mining Lurkers in Online Social Networks, SpringerBriefs in Computer Science, https://doi.org/10.1007/978-3-030-00229-9_1 1