38,161 research outputs found
Modeling Paying Behavior in Game Social Networks
Online gaming is one of the largest industries on the Internet, generating tens of billions of dollars in revenues annually. One core problem in online game is to find and convert free users into paying customers, which is of great importance for the sustainable development of almost all online games. Although much research has been conducted, there are still several challenges that remain largely unsolved: What are the fundamental factors that trigger the users to pay? How does users? paying behavior influence each other in the game social network? How to design a prediction model to recognize those potential users who are likely to pay? In this paper, employing two large online games as the basis, we study how a user becomes a new paying user in the games. In particular, we examine how users' paying behavior influences each other in the game social network. We study this problem from various sociological perspectives including strong/weak ties, social structural diversity and social influence. Based on the discovered patterns, we propose a learning framework to predict potential new payers. The framework can learn a model using features associated with users and then use the social relationships between users to refine the learned model. We test the proposed framework using nearly 50 billion user activities from two real games. Our experiments show that the proposed framework significantly improves the prediction accuracy by up to 3-11% compared to several alternative methods. The study also unveils several intriguing social phenomena from the data. For example, influence indeed exists among users for the paying behavior. The likelihood of a user becoming a new paying user is 5 times higher than chance when he has 5 paying neighbors of strong tie. We have deployed the proposed algorithm into the game, and the Lift_Ratio has been improved up to 196% compared to the prior strategy
Towards Economic Models for MOOC Pricing Strategy Design
MOOCs have brought unprecedented opportunities of making high-quality courses
accessible to everybody. However, from the business point of view, MOOCs are
often challenged for lacking of sustainable business models, and academic
research for marketing strategies of MOOCs is also a blind spot currently. In
this work, we try to formulate the business models and pricing strategies in a
structured and scientific way. Based on both theoretical research and real
marketing data analysis from a MOOC platform, we present the insights of the
pricing strategies for existing MOOC markets. We focus on the pricing
strategies for verified certificates in the B2C markets, and also give ideas of
modeling the course sub-licensing services in B2B markets
Modeling the relationship between network operators and venue owners in public Wi-Fi deployment using non-cooperative game theory
Wireless data demands keep rising at a fast rate. In 2016, Cisco measured a global mobile data traffic volume of 7.2 Exabytes per month and projected a growth to 49 Exabytes per month in 2021. Wi-Fi plays an important role in this as well. Up to 60% of the total mobile traffic was off-loaded via Wi-Fi (and femtocells) in 2016. This is further expected to increase to 63% in 2021. In this publication, we look into the roll-out of public Wi-Fi networks, public meaning in a public or semi-public place (pubs, restaurants, sport stadiums, etc.). More concretely we look into the collaboration between two parties, a technical party and a venue owner, for the roll-out of a new Wi-Fi network. The technical party is interested in reducing load on its mobile network and generating additional direct revenues, while the venue owner wants to improve the attractiveness of the venue and consequentially generate additional indirect revenues. Three Wi-Fi pricing models are considered: entirely free, slow access with ads or fast access via paid access (freemium), and paid access only (premium). The technical party prefers a premium model with high direct revenues, the venue owner a free/freemium model which is attractive to its customers, meaning both parties have conflicting interests. This conflict has been modeled using non-cooperative game theory incorporating detailed cost and revenue models for all three Wi-Fi pricing models. The initial outcome of the game is a premium Wi-Fi network, which is not the optimal solution from an outsider's perspective as a freemium network yields highest total payoffs. By introducing an additional compensation scheme which corresponds with negotiation in real life, the outcome of the game is steered toward a freemium solution
How to Ask for a Favor: A Case Study on the Success of Altruistic Requests
Requests are at the core of many social media systems such as question &
answer sites and online philanthropy communities. While the success of such
requests is critical to the success of the community, the factors that lead
community members to satisfy a request are largely unknown. Success of a
request depends on factors like who is asking, how they are asking, when are
they asking, and most critically what is being requested, ranging from small
favors to substantial monetary donations. We present a case study of altruistic
requests in an online community where all requests ask for the very same
contribution and do not offer anything tangible in return, allowing us to
disentangle what is requested from textual and social factors. Drawing from
social psychology literature, we extract high-level social features from text
that operationalize social relations between recipient and donor and
demonstrate that these extracted relations are predictive of success. More
specifically, we find that clearly communicating need through the narrative is
essential and that that linguistic indications of gratitude, evidentiality, and
generalized reciprocity, as well as high status of the asker further increase
the likelihood of success. Building on this understanding, we develop a model
that can predict the success of unseen requests, significantly improving over
several baselines. We link these findings to research in psychology on helping
behavior, providing a basis for further analysis of success in social media
systems.Comment: To appear at ICWSM 2014. 10pp, 3 fig. Data and other info available
at http://www.mpi-sws.org/~cristian/How_to_Ask_for_a_Favor.htm
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