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Journal ArticleDOI

Social Ties and Word-of-Mouth Referral Behavior

01 Dec 1987-Journal of Consumer Research (The Oxford University Press)-Vol. 14, Iss: 3, pp 350-362
TL;DR: In this paper, the relational properties of tie strength and homophily were employed to examine referral behavior at micro and macro levels of inquiry, showing that weak ties displayed an important bridging function allowing information to travel from one distinct subgroup of referral actors to another subgroup in the broader social system.
Abstract: This article presents a network analysis of word-of-mouth referral behavior in a natural environment. The relational properties of tie strength and homophily were employed to examine referral behavior at micro and macro levels of inquiry. The study demonstrates different roles played by weak and strong social ties. At the macro level, weak ties displayed an important bridging function, allowing information to travel from one distinct subgroup of referral actors to another subgroup in the broader social system. At the micro level, strong and homophilous ties were more likely to be activated for the flow of referral information. Strong ties were also perceived as more influential than weak ties, and they were more likely to be utilized as sources of information for related goods.
Citations
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Proceedings ArticleDOI
24 Aug 2003
TL;DR: An analysis framework based on submodular functions shows that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models, and suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks.
Abstract: Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of "word of mouth" in the promotion of new products. Recently, motivated by the design of viral marketing strategies, Domingos and Richardson posed a fundamental algorithmic problem for such social network processes: if we can try to convince a subset of individuals to adopt a new product or innovation, and the goal is to trigger a large cascade of further adoptions, which set of individuals should we target?We consider this problem in several of the most widely studied models in social network analysis. The optimization problem of selecting the most influential nodes is NP-hard here, and we provide the first provable approximation guarantees for efficient algorithms. Using an analysis framework based on submodular functions, we show that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models; our framework suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks.We also provide computational experiments on large collaboration networks, showing that in addition to their provable guarantees, our approximation algorithms significantly out-perform node-selection heuristics based on the well-studied notions of degree centrality and distance centrality from the field of social networks.

5,887 citations


Cites background from "Social Ties and Word-of-Mouth Refer..."

  • ...Some of the earliest systematic investigations focused on data pertaining to the adoption of medical and agricultural innovations in both developed and developing parts of the world [8, 27, 29]; in other contexts, research has investigated diffusion processes for “word-of-mouth” and “viral marketing” effects in the success of new products [4, 7, 10, 13, 14, 20, 26], the sudden and widespread adoption of various strategies in gametheoretic settings [6, 12, 21, 32, 33], and the problem of cascading failures in power systems [2, 3]....

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Journal ArticleDOI
TL;DR: The problem of finding the most influential nodes in a social network is NP-hard as mentioned in this paper, and the first provable approximation guarantees for efficient algorithms were provided by Domingos et al. using an analysis framework based on submodular functions.
Abstract: Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of "word of mouth" in the promotion of new products. Recently, motivated by the design of viral marketing strategies, Domingos and Richardson posed a fundamental algorithmic problem for such social network processes: if we can try to convince a subset of individuals to adopt a new product or innovation, and the goal is to trigger a large cascade of further adoptions, which set of individuals should we target?We consider this problem in several of the most widely studied models in social network analysis. The optimization problem of selecting the most influential nodes is NP-hard here, and we provide the first provable approximation guarantees for efficient algorithms. Using an analysis framework based on submodular functions, we show that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models; our framework suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks.We also provide computational experiments on large collaboration networks, showing that in addition to their provable guarantees, our approximation algorithms significantly out-perform node-selection heuristics based on the well-studied notions of degree centrality and distance centrality from the field of social networks.

4,390 citations

Journal ArticleDOI
TL;DR: While on average recommendations are not very effective at inducing purchases and do not spread very far, this work presents a model that successfully identifies communities, product, and pricing categories for which viral marketing seems to be very effective.
Abstract: We present an analysis of a person-to-person recommendation network, consisting of 4 million people who made 16 million recommendations on half a million products. We observe the propagation of recommendations and the cascade sizes, which we explain by a simple stochastic model. We analyze how user behavior varies within user communities defined by a recommendation network. Product purchases follow a ‘long tail’ where a significant share of purchases belongs to rarely sold items. We establish how the recommendation network grows over time and how effective it is from the viewpoint of the sender and receiver of the recommendations. While on average recommendations are not very effective at inducing purchases and do not spread very far, we present a model that successfully identifies communities, product, and pricing categories for which viral marketing seems to be very effective.

2,361 citations


Cites background from "Social Ties and Word-of-Mouth Refer..."

  • ...ce of social networks on innovation and product diffusion. However, such studies have been typically limited to small networks and typically a single product or service. For example, Brown and Reingen [BR87] interviewed the families of students being instructed by three piano teachers, in order to find out the network of referrals. They found that strong ties, those between family or friends, were more li...

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Journal ArticleDOI
TL;DR: It is found that online conversations may offer an easy and cost-effective opportunity to measure word of mouth and it is shown that a measure of the dispersion of conversations across communities has explanatory power in a dynamic model of TV ratings.
Abstract: Managers are very interested in word-of-mouth communication because they believe that a product's success is related to the word of mouth that it generates. However, there are at least three significant challenges associated with measuring word of mouth. First, how does one gather the data? Because the information is exchanged in private conversations, direct observation traditionally has been difficult. Second, what aspect of these conversations should one measure? The third challenge comes from the fact that word of mouth is not exogenous. While the mapping from word of mouth to future sales is of great interest to the firm, we must also recognize that word of mouth is an outcome of past sales. Our primary objective is to address these challenges. As a context for our study, we have chosen new television (TV) shows during the 1999-2000 seasons. Our source of word-of-mouth conversations is Usenet, a collection of thousands of newsgroups with diverse topics. We find that online conversations may offer an easy and cost-effective opportunity to measure word of mouth. We show that a measure of the dispersion of conversations across communities has explanatory power in a dynamic model of TV ratings.

2,247 citations


Cites background or methods from "Social Ties and Word-of-Mouth Refer..."

  • ...Brown and Reingen (1987) used a similar methodology for piano teachers....

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  • ...Key words : word of mouth; diffusion of innovations; measurement; networks and marketing; new product research; Internet marketing History : This paper was received June 3, 2002, and was with the authors 13 months for 3 revisions; processed by Gary Lilien....

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  • ...Van den Bulte and Lilien (2001, 2003) and Anderson (1998) draw on the existence of survey-based data that were prepared for other purposes....

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  • ...Van den Bulte and Lilien (2001) question the primacy of WOM communication as a driver of product adoption....

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  • ...Similarly, the dataset used by Van den Bulte and Lilien (2001) contains data for each physician about the other physicians with whom he or she discussed medical practices....

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Journal ArticleDOI
TL;DR: The authors investigated the effects of word-of-mouth (WOM) communications and specific attribute information on product evaluations and found that a face-to-face WOM communication was more persuasive than a printed format.
Abstract: The effects of word-of-mouth (WOM) communications and specific attribute information on product evaluations were investigated. A face-to-face WOM communication was more persuasive than a printed format (experiment 1). Although a strong WOM effect was found, this effect was reduced or eliminated when a prior impression of the target brand was available from memory or when extremely negative attribute information was presented (experiment 2). The results suggest that diverse, seemingly unrelated judgmental phenomena—such as the vividness effect, the perseverance effect, and the negativity effect—can be explained through the accessibility-diagnosticity model.

2,145 citations