ESTIMATION OF PEER INFLUENCE EFFECT IN ONLINE GAMES USING MACHINE LEARNING APPROACHES

Peer influence, which means that an individual can directly influence his friends to be similar with him, is very important in social network analysis. However, peer influence effects are often confounded with latent homophily caused by unobserved similar characteristics. Scholars have designed randomized experiments or established mathematical models to control the latent homophily to get a more accurate effect of peer influence. However, the randomized experiments cannot utilize the valuable second-hand data and the mathematical models are always complex and time-consuming. In this paper, we propose a novel approach based on machine learning to estimate the peer influence effect. First, we use machine learning or deep learning algorithms to get node embeddings which imply the structural information of the nodes in a social network. Then we use the embeddings to act as a proxy variable of unobserved homophily factors in OLS regression models. To verify the feasibility of our approach, we design a simulation experiment. Finally, we implement our method to an empirical study and find that peer influence exists in online game social networks and using node embeddings as a proxy variable in regression can help estimate a more accurate peer influence effect

Scalable Inference of Customer Similarities from Interactions Data using Dirichlet Processes

Under the sociological theory of homophily, people who are similar to one another are more likely to interact with one another. Marketers often have access to data on interactions among customers from which, with homophily as a guiding principle, inferences could be made about the underlying similarities. However, larger networks face a quadratic explosion in the number of potential interactions that need to be modeled. This scalability problem renders probability models of social interactions computationally infeasible for all but the smallest networks. In this paper we develop a probabilistic framework for modeling customer interactions that is both grounded in the theory of homophily, and is flexible enough to account for random variation in who interacts with whom. In particular, we present a novel Bayesian nonparametric approach, using Dirichlet processes, to moderate the scalability problems that marketing researchers encounter when working with networked data. We find that this framework is a powerful way to draw insights into latent similarities of customers, and we discuss how marketers can apply these insights to segmentation and targeting activities

The influence of fashion blogger credibility, engagement and homophily on intentions to buy and e-WOM. Results of a binational study

Purpose – The study aims to contribute to the knowledge on the role of the fashion bloggers in the product adoption process in both advanced and emerging markets. Specifically, the study investigates the impact of credibility, engagement and homophily on intentions to buy fashion products recommended by the blogger. Design/methodology/approach – The empirical research builds on an online survey with a sample of 402 consumers (189 Italian and 213 Taiwanese). The proposed model was tested through structural equationmodeling. Findings – Results showed that homophily and the fashion blogger credibility positively influenced the engagement within the blog. Moreover, perceived similarity with the other blog’s followers (homophily) and a higher engagement with the blog both translated in a stronger intention to buy the sponsored products and to spread a positive word-of-mouth about the fashion blogger. Practical implications – The study has practical implications since it identifies strategic suggestions for both companies that create partnerships with famous fashion bloggers and bloggers who have turned their diary-style websites into a business. Originality/value – The study contributes to a better understanding of the influence exerted by blog engagement on intentions to follow blogger’s recommendations. The study also examines credibility and homophily as antecedents of engagement, which have not been extensively researched in the past with respect to blogs

Effects of fashion blogger credibility, engagement and risk-taking behaviour on followers' shopping intentions. A study of Italian consumers

The present study investigates the impact of blogger credibility, homophily, engagement and risk-taking behaviour on readers’ shopping intentions. Despite the growing relevance of these issues, past studies have neglected the relevance of a joint analysis of such dimensions. To fill this gap, the study proposes and tests a model that explains blog followers’ intentions to buy products sponsored by the fashion blogger. Results from a survey on Italian consumers show that blogger credibility and homophily have a significant effect on blog engagement, which, in turn, positively affects both e-word-of-mouth and purchase intentions toward blogger’s sponsored products. Finally, theoretical and practical implications of the findings are discussed

Will they come and will they stay? Online Social Networks and news consumption on external websites

This study explores the role of online engagement, homophily and social influence in explaining traffic and news consumption by social network users at an external news website. The authors jointly model visits and page views for a panel of users who registered with the news site using their Facebook accounts. In their model, the authors account for homophily using a latent space approach, and account for endogeneity, heterogeneity, and unobservable correlates. The results show that measures of an individual’s activity on Facebook are positively associated with that individual’s actions at the news site. In addition, knowing what a user’s Facebook friends do at the content website provides insights into a focal user’s behavior at that website, as visitors with friends who visit external news sites are more likely to visit the news website studied. In addition, news consumption (not just visits) also depends on friend’s actions but such an impact varies with the individual’s underlying browsing mode. We highlight the importance of social influence in news consumption and further show that homophily bias in news consumption is similar to prior research in other categories. Our study also highlights that visitors’ past browsing patterns are important predictors of future content consumption, although social network information significantly improves prediction beyond the effect of such more traditional behavioral metrics. Finally, we find that Managers can use readily available data for both prediction and targeting

Predicting mobile advertising response using consumer colocation networks

Building on results from economics and consumer behavior, the authors theorize that consumers' movement patterns are informative of their product preferences, and this study proposes that marketers monetize this information using dynamic networks that capture colocation events (when consumers appear at the same place at approximately the same time). To support this theory, the authors study mobile advertising response in a panel of 217 subscribers. The data set spans three months during which participants were sent mobile coupons from retailers in various product categories through a smartphone application. The data contain coupon conversions, demographic and psychographic information, and information on the hourly GPS location of participants and on their social ties in the form of referrals. The authors find a significant positive relationship between colocated consumers' response to coupons in the same product category. In addition, they show that incorporating consumers' location information can increase the accuracy of predicting the most likely conversions by 19%. These findings have important practical implications for marketers engaging in the fast-growing location-based mobile advertising industry

The Effect of Social EWOM on Consumers’ Behaviour Patterns in the Fashion Sector

The study described in this chapter aimed to enhance knowledge on the influence of electronic word of mouth (eWOM) on consumer’s decision-making processes. eWOM emerged as a key driver in consumers’ decision-making processes given its greater impact on purchasing decisions compared to other communication channels. Specifically, the study focused on the reviews of fashion products on social networks (SNs) and built on the stimulus-organism-response (S-O-R) model in order to identify the determinants of social eWOM adoption and intention to buy the reviewed product. The survey method was used to gather data from 230 Italian consumers. Structural equation modelling was used to estimate the model proposed. Results revealed that when consumers seek information on fashion products, the user-friendliness of SNs and social cues (homophily and normative social influence) positively impact social eWOM (opinion-seeking), which in turn influences the intention to purchase the reviewed products. The study contributes both theoretically and empirically to the understanding of the role of social eWOM in influencing consumer behaviour. At the theoretical level, it supports the adequacy of the S-O-R model for explaining the consumer decision-making process in the context of social eWOM. From a managerial perspective, the findings highlight the importance of taking into consideration both structural (accessibility) and social relationship variables while developing social media marketing strategies

Long-range social influence in phone communication networks on offline adoption decisions

We use high-resolution mobile phone data with geolocation information and propose a novel technical framework to study how social influence propagates within a phone communication network and affects the offline decision to attend a performance event. Our fine-grained data are based on the universe of phone calls made in a European country between January and July 2016. We isolate social influence from observed and latent homophily by taking advantage of the rich spatial-temporal information and the social interactions available from the longitudinal behavioral data. We find that influence stemming from phone communication is significant and persists up to four degrees of separation in the communication network. Building on this finding, we introduce a new “influence” centrality measure that captures the empirical pattern of influence decay over successive connections. A validation test shows that the average influence centrality of the adopters at the beginning of each observational period can strongly predict the number of eventual adopters and has a stronger predictive power than other prevailing centrality measures such as the eigenvector centrality and state-of-the-art measures such as diffusion centrality. Our centrality measure can be used to improve optimal seeding strategies in contexts with influence over phone calls, such as targeted or viral marketing campaigns. Finally, we quantitatively demonstrate how raising the communication probability over each connection, as well as the number of initial seeds, can significantly amplify the expected adoption in the network and raise net revenue after taking into account the cost of these interventions

What drives me there? The interplay of socio-psychological gratification and consumer values in social media brand engagement

The social behavioral perspective is under-researched in the extant literature. This hinders the holistic understanding of social media brand engagement. This study examines the interplay of socio-psychological gratification variables (perceived homophily, perceived critical mass, and self-status seeking) and consumer values (personal, interpersonal, and fun) on consumer participation in social media brand engagement. The conceptual model in this study is situated on the principles of Uses and Gratifications, Critical Mass, Homophily, and Values theories. Based on an online survey of 713 Facebook users, we examine the model using structural equation modeling (with Amos 23.0). The analysis disclosed insights on the interplay of motivational factors that underlie social media brand engagement. Our findings suggest that socio-psychological gratification variables (perceived homophily, perceived critical mass, and self-status seeking) drive consumers’ engagement with brand pages and brand communities on social media. This relationship is strengthened by the consumer values. These insights serve as an important basis for researchers and practitioners to understand social media brand engagement and its outcomes