Abstract: This document describes techniques for predicting spread of content across social networks. In various embodiments, user interactions with content posted to a social network are accessed during a first stage. The accessed user interactions are applied to a prediction model to predict future user interactions with the content during one or more subsequent stages.

Abstract: This document describes techniques for normalizing user responses by removing behavioral bias. In one or more implementations, a response normalization model is built from user responses to one or more events. The response normalization model clusters users into behavioral classification groups based on the user responses. The response normalization model can then be used to normalize user responses by removing behavioral bias from user responses.

Abstract: Determined seed groups herein improve content dissemination across a communication network connecting a plurality of users. Probabilities of each user in the plurality influencing remaining users in the plurality to observe the content are identified to select a first influential user from the plurality. The seed group size is established and a user of the plurality with a probability proximate to the probability of the first influential user is identified. Based on the seed group size, the probabilities of the remaining users in the plurality are unified with the probability of the first influential user to determine new probabilities of the remaining users, and another user of the plurality with a probability proximate to the probability of the first influential user is identified. The method then provides for selecting the users identified as having probabilities proximate to the probability of the first influential user to establish the seed group.

Abstract: This document describes techniques for normalizing user responses by removing behavioral bias. In one or more implementations, a response normalization model is built from user responses to one or more events. The response normalization model clusters users into behavioral classification groups based on the user responses. The response normalization model can then be used to normalize user responses by removing behavioral bias from user responses.

Abstract: This document describes techniques for predicting spread of content across social networks. In various embodiments, user interactions with content posted to a social network are accessed during a first stage. The accessed user interactions are applied to a prediction model to predict future user interactions with the content during one or more subsequent stages.

Abstract: Determined seed groups herein improve content dissemination across a communication network connecting a plurality of users. Probabilities of each user in the plurality influencing remaining users in the plurality to observe the content are identified to select a first influential user from the plurality. The seed group size is established and a user of the plurality with a probability proximate to the probability of the first influential user is identified. Based on the seed group size, the probabilities of the remaining users in the plurality are unified with the probability of the first influential user to determine new probabilities of the remaining users, and another user of the plurality with a probability proximate to the probability of the first influential user is identified. The method then provides for selecting the users identified as having probabilities proximate to the probability of the first influential user to establish the seed group.

Abstract: The invention relates to a method of estimating market share for a communication service provider comprising collecting periodic packet data usage from a plurality of websites including details of the communication service provider used to access the websites; determining the market share of a communication service provider at the plurality of websites; and extrapolating the market share of the communication service provider at the plurality of websites to estimate the market share. Another method of estimating change in market share for communication service providers is also disclosed. The method comprises of collecting periodic packet data usage for a user from at least one user device which includes data on the communication service provider or providers used to access the internet from that device.

Abstract: Apparatus and methods for measuring consumer experience through an optimal user panel within predetermined error rate, or any other categorization for wireless domain. The data is collected at the panel member's wireless device. Categorization of data is based on but not limited to, product groupings and market segments. To minimize the cost of the method while having the estimate of consumer experience within aforesaid error rates, the panel members are chosen such that they can provide the most informative data of usage for the parameters that effect consumer experience, such as wireless network usage, usage of applications, sequence thereof among others. The focal point of data collection will be to trace the failure rate in the wireless network, devices, application among others. Thus we can apply suitable statistical models of prediction, such as but not limited to Poisson distribution and Empirical Bayes technique. Thus an optimal and more accurate quantitative measure of the estimate is made.