The mobile services industry is growing rapidly, and more people are now adopting new mobile Web services. According to the reports of the International Telecommunication Union (Sanou, 2015), there were > 7 billion mobile cellular subscriptions worldwide in 2015, up from < 1 billion in 2000. Globally, 3.2 billion people are using the Internet and 2 billion of these users are from the developing countries. Further, a huge amount of data is increasingly being placed at the forefront of this communication due to the explosion of data coming from a wide array of technologies and greater/explosive Web content consumption (Chen, 2016; Garth, 2014). As the evolution of the mobile services industry proceeds even further, more value can be extracted by understanding the usage patterns of individual consumers or specific groups. Studying specific groups and their influence from this gigantic and complex database, particular mobile Web services, is an important topic that has attracted the attention of a variety of marketing researchers. Traditionally, people seek the opinion and advice of their peers regarding various decisions they make. This behavior gives rise to a certain set of individuals in social networks, referred to by many as opinion leaders (Sharara et al., 2011). Considering the importance of these specific people or groups in social networks, previous studies have shown they have various titles (e.g., opinion leaders, key players and influential people; to be consistent, we suggest calling them as “opinion leaders”). In this paper, we use that term to refer to any influential group in the traditional social networks (Momtaz et al., 2011). From a marketer perspective, the early work that targeted women’s clothing fashion opinion leaders in media planning by Eric Vernette (2004) concluded that “the media planner can benefit from choosing opinion leaders as a specific media target because this will indirectly secure a free audience and can boost the impact of the advertising message” (p. 105). In this regard, opinion leaders potentially spread their messages through word-of-mouth to affect other users’ behavior. Today, mobile services not only include voice and text messaging, but also provide computer-like applications, such as document viewers, Internet browsing, and multimedia for consumers to use and communicate with other users. In addition, social changes have been unprecedentedly quick, and individual communications with others has become more frequent through the use of the mobile social networks (Turkle, 2015). Those mobile user patterns are more complex than those of the previous computer-mediated systems. In this way, the exponential growth of mobile Web services provides opinion leaders with a wide range of social influence. Meanwhile, marketers have always tried to develop communication strategies to meet the accuracy needs of mobile Web service content among the opinion leaders who informally influence the attitudes or behavior of other common people through product- or service-related conversation, referred to as “electronic word-of-mouth” communication. The study by Lu, Tseng, and Yu (2011) further suggested that mining usage patterns can help the discovery of specific (sub)groups, then used in applications like targeted specific favorite advertising and/ or personalization of content. Presumptively, mining Web content usage patterns can analyze the most suitable information to offer and serve as content preference mechanism to meet the needs of opinion leaders based on their actual mobile behavior (Lu and Tseng, 2009).