Word association norms, mutual information, and lexicography
Computational Linguistics
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Measures of distributional similarity
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Comments on "A New Product Growth for Model Consumer Durables"
Management Science
Social influence analysis in large-scale networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
A note on competitive diffusion through social networks
Information Processing Letters
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Understanding retweeting behaviors in social networks
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
A new perspective on Twitter hashtag use: diffusion of innovation theory
Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47
A data-based approach to social influence maximization
Proceedings of the VLDB Endowment
The Joint Inference of Topic Diffusion and Evolution in Social Communities
ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
We know what @you #tag: does the dual role affect hashtag adoption?
Proceedings of the 21st international conference on World Wide Web
Competitive contagion in networks
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Clash of the Contagions: Cooperation and Competition in Information Diffusion
ICDM '12 Proceedings of the 2012 IEEE 12th International Conference on Data Mining
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The spreading of innovations among individuals and organizations in a social network has been extensively studied. Although the recent studies among the social computing and data mining communities have produced various insightful conclusions about the diffusion process of innovations by focusing on the properties and evolution of social network structures, less attention has been paid to the interrelationships among the multiple innovations being diffused, such as the competitive and collaborative relationships between innovations. In this paper, we take a formal quantitative approach to address how different pieces of innovations socialize with each other and how the interrelationships among innovations affect users' adoption behavior, which provides a novel perspective of understanding the diffusion of innovations. Networks of innovations are constructed by mining large scale text collections in an unsupervised fashion. We are particularly interested in the following questions: what are the meaningful metrics on the network of innovations? What effects do these metrics exert on the diffusion of innovations? Do these effects vary among users with different adoption preferences or communication styles? While existing studies primarily address social influence, we provide a detailed discussion of how innovations interrelate and influence the diffusion process.