Mining knowledge-sharing sites for viral marketing
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Summary
This research optimize the amount of marketing funds spent on each customer, rather than just making a binary decision on whether to market to him, and takes into account the fact that knowledge of the network is partial, and that gathering that knowledge can itself have a cost.
- Type
- article
- Published
- 2002-07-23
- Cited by
- 1,853
- References
- 27
- OpenAlex
- https://openalex.org/W2056609785
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:5785954
Keywords
Viral marketing, Computer science, Probabilistic logic, Robustness (evolution), Knowledge sharing
References
- Data Mining for Direct Marketing: Problems and Solutions
- Networks in Marketing
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- The Small World Problem
- The PageRank Citation Ranking : Bringing Order to the Web
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- Information Value Theory
- Estimating campaign benefits and modeling lift
- Mining the network value of customers
- The Anatomy of a Large-Scale Hypertextual Web Search Engine
- Scale-free characteristics of random networks: the topology of the world-wide web
- Cobot in LambdaMOO: A Social Statistics Agent
- Extracting Large-Scale Knowledge Bases from the Web
- On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
- Referral Web: combining social networks and collaborative filtering
- Human behavior and the principle of least effort
- The Complete Database Marketer: Second Generation Strategies and Techniques for Tapping the Power of Your Customer Database
- Human behavior and the principle of least effort
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- Efficient Estimation of Influence Functions for SIS Model on Social Networks
- Mining Target Marketing Groups From Users' Web of Trust on Epinions
- Extracting Influential Nodes for Information Diffusion on a Social Network
- Etude, représentation et applications des traverses minimales d'un hypergraphe. (Representation and applications of hypergraph minimal transversals)
- Tools for large graph mining
- Feature Engineering for Supervised Link Prediction on Dynamic Social Networks
- Diffusion of Recommendation through a Trust Network
- Unifying Logical and Statistical AI
- Learning User-Specific Latent Influence and Susceptibility from Information Cascades
- Detecting Community Influence Echelons in Twitter Network
- cGraph: A Fast Graph-Based Method for Link Analysis and Queries
- An Effective Method of Discovering Target Groups on Social Networking Sites
- Pseudo-social network targeting from consumer transaction data
- Prediction in Social Media for Monitoring and Recommendation
- Implicit Affinity Networks
- Integrating Social Network Effects in Product Design and Diffusion
- Research on Statistical Relational Learning at the University of Washington
- Incremental Learning for Interaction Dynamics with the Influence Model
- A User Segmentation Model for Social Networking Websites (SNSs) ตัวแบบการแบ่งส่วนผู้ใช้งานเว็บไซต์สังคมออนไลน์
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