Predicting when an individual will adopt a new behavior is an important problem in application domains such as marketing and public health. This thesis examines the performance of a wide variety of social network based measurements proposed in the literature - which have not been previously compared directly. This research studies the probability of an individual becoming influenced based on measurements derived from neighborhood (i.e. number of influencers, personal network exposure), structural diversity, locality, temporal measures, cascade measures, and metadata.
Download count: 0
- Partial requirement for: M.S., Arizona State University, 2016Note typethesis
- Includes bibliographical references (pages 31-33)Note typebibliography
- Field of study: Computer science