Modeling Social Influence in Mobile Messaging Apps

Social influence is the behavioral change of a person because of the perceived relationship with other people, organizations and society in general. With the exponential growth of online social network services especially mobile messaging apps, users around the world are logging in to messaging apps to not only chat with friends but also to connect with brands, browse merchandise, and watch content. Mobile chat apps boast a number of distinct characteristics that make their audiences particularly appealing to businesses and marketers, including their size, retention and usage rates, and user demographics. The combined user base of the top four chat apps is larger than the combined user base of the top four social networks. Therefore, it makes great sense to analyze user behavior and social influence in mobile messaging apps. In this paper, we focus on computational aspects of measuring social influence of groups formed in mobile messaging apps. We describe the special features of mobile messaging apps and present challenges. We address the challenges by proposing a temporal weighted data model to measure the group influence in messaging apps by considering their special features, with implementation and evaluation in the end.