MULTI-SOURCE MODELING FOR NETWORK PREDICTIONS

摘要

Techniques are described for analyzing time series data associated with one or more networks, such as social networks, and based on the analysis determining a one or more predictive models. The time series data describe a number and/or frequency of published items on the network(s), and the predictive model(s) may be employed to predict the future number and/or frequency of published items associated with the category. The time series data may also describe a number and/or frequency of followers of a user in the network(s), republications of published items, and/or other types of data, and the model(s) may be developed that predict the future changes (e.g., trends) of such metrics in the network(s). The model(s) for a particular category may be further based on additional sources of data, including but not limited to financial data, weather data, environmental data, event data, news data, demographic data, and so forth.