Understanding lurkers in online communities: A literature review
Introduction
The “silent groups” in the online communities, usually known as lurkers, comprise the majority of community members. The famous “90-9-1” principle states that in a collaborative websites, such as an online community, 90% of the participants only read content, 9% of the participants edit content and 1% of the participants actively create new content (Arthur, 20 July 2006). The number may be different but it has been widely proved that the majority of the content in an online community is created by the minority of the users. One of the founders of Wikipedia once performed a study and found that over 50% of all the edits were done by only 0.7% of the users (Swartz, 2006). In a recent investigation of the content of four separate digital health social networks, researchers indicated that the top 1% most active users created 73.6% of posts on average, the next 9% of the population accounted for an average of 24.7% of posts, and the remaining 90% of the population posted 1.7% of posts on average (van Mierlo, 2014). Actually, every participant of the online communities, active or silent, read more postings than they wrote (Ebner, Holzinger, & Catarci, 2005). The difference between posters and lurkers is that posters make contributions to the community by sending messages occasionally, while lurkers stay silent most of the time.
Even though lurkers comprise such a large proportion of website users, researchers have paid little attention to the lurking phenomenon until recent years. Surveys have been conducted in online communities (Bishop, 2007), email-based discussion list (Nonnecke & Preece, 2000), the social network service (Rau, Gao, & Ding, 2008) and online learning courses (Beaudoin, 2002, Küçük, 2010) to discover the underlying reasons for lurking and methods to encourage lurkers to post. Different models have been proposed to explain lurking behavior, and these models identified many factors that influence online performance, such as community culture, users’ personality and the relationship between users and the group (Du, 2006, Fan et al., 2009, Kollock, 1999, Leshed, 2005, Nonnecke, 2000, Nonnecke and Preece, 2001, Tedjamulia et al., 2005).
Some of the studies considered lurkers to be free-riders and conveyed a negative attitude toward lurkers (Kollock and Smith, 1996, Morris and Ogan, 1996, Rheingold, 2000, Wellman and Gulia, 1999). The sustainability of an online community requires fresh content and timely interactions, but the lurkers are considered to just benefit from observing others’ interaction and contribute little value to the community (van Mierlo, 2014). Besides, if there are too many lurkers in a knowledge-based community, the knowledge may not be representative of average web users ((Nielsen, 2011). As a result, even though a proper amount of lurkers are acceptable for large online communities, too many lurkers would impair the vitality of the community.
However, other studies argued that most lurkers were not selfish free-riders who use the common good without making any contribution (Nonnecke et al., 2006, Nonnecke, Preece, et al., 2004, Wichmand and Jensen, 2012). On the contrary, lurking is not only normal but also is an active, participative and valuable form of online behavior (Edelmann, 2013). Many lurkers thought of themselves as community members, and lurking was an important way for them to join a community (Nonnecke et al., 2006). Nineteen inactive students in an online course said they felt they were learning just as much or more from reading others’ comments than from writing their own (Beaudoin, 2002). Lave and Wenger (1999) regarded lurking behavior in a community of practice as a form of cognitive apprenticeship, which can be perceived as legitimate peripheral participation. In an online community, peripheral members are less visible, but they benefit more from knowledge exchange and contribute as much as non-peripheral members (Zhang & Storck, 2001).
This study reviewed 71 literatures on the behaviors of internet users in online communities and built an integrated model to explain the motivational factors of online behaviors, thereby providing explanations of lurking and strategies to encourage posting. The objective of this study was to gain an overall understanding of lurkers and determine answers to the following four questions: how can lurkers be identified? What drives online behaviors? Why do people lurk, and how to promote posting?
Section snippets
How to identify lurkers
The Jargon Dictionary (2001) defines a lurker as: “One of the ‘silent majorities’ in an electronic forum, one who posts occasionally or not at all but is known to read the group’s postings regularly.” This definition describes two features of lurkers, seldom posting and regularly reading messages, but it does not set a quantitative standard of lurkers. Previous studies have identified lurkers in different ways: the members who never post in an online community (Neelen and Fetter, 2010, Nonnecke
What drives online behaviors
Understanding the factors that drive online participation helps to explain the reasons for lurking and develop strategies to motivate posting. Previous studies have identified many factors that influence online behaviors, such as environmental influences (Fan et al., 2009, Tedjamulia et al., 2005), personal characteristics (Bishop, 2007, Du, 2006, Han et al., 2007) and organizational commitment (Bateman, Gray, & Butler, 2006). An integrated model of motivational factors of online behaviors was
Why lurkers lurk
Both lurkers and posters join online communities for similar reasons, i.e. to obtain answers to their questions, but they act in different ways to fulfill their goals (Nonnecke, Preece, et al., 2004), e.g. posters post and lurkers lurk. Based on the motivation model, the reasons for lurking can be classified into four categories, which are environmental influence determined by the online community (such as bad usability design) (Nonnecke, Preece, Andrews, Voutour, 2004), personal preference
How to promote posting
Lurkers are further classified into active lurkers, who either spread information and knowledge gained from the online community to others or apply such information and knowledge in organizational activities, and passive lurkers, who only read for their own use (Takahashi et al., 2003, Walker et al., 2013, Willett, 1998). In addition, active lurking could be further divided into active lurking for propagation, active lurking for practical use (Takahashi et al., 2003) and active lurker for
Conclusions
This study reviewed the literature on online behaviors and aimed to provide an overall understanding of lurkers and lurking behaviors. First, different methods to identify lurkers were discussed. An integrated model of motivational factors of online behaviors was subsequently proposed. In this model, the factors that influence online behaviors included the nature of the online community, individual characteristics, the degree of commitment and quality requirement. Accordingly, the reasons for
Acknowledgement
This study was funded by National Science Foundation China grant #71188001 and #70971074.
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