Abstract: According to some embodiments, an event having an association with a financial instrument may be identified. The event may then be classified into at least one of a plurality of predefined event classes, each predefined event class being associated with a set of similar events. Media data associated with media coverage of the event may be retrieved and data elements may be extracted from the media data, wherein the data elements include at least one quantified communication parameter including at least one of a short term media coverage volume, a publication weight, a tonal balance, and an impact of available photographs. A prediction of the upcoming media coverage of the event may be generated, including a predicted volume and tonality of the upcoming media coverage, wherein said prediction is generated using a modeling computer system, a numerical model, said extracted data elements, and information about said predefined event class.

Abstract: According to some embodiments, natural language processing may be employed on media data to discover events pertaining to—and, including changes in—ownership (including mergers and acquisitions) and supplier/client relationships between corporations (and other entities) in such a manner that the system may maintain and automatically update a computerized model of the events and the attendant relationship between the entities, including but not limited to monitoring risk to corporate reputation across the supply chain.

Abstract: According to some embodiments, an event having an association with a financial instrument may be identified. The event may then be classified into at least one of a plurality of predefined event classes, each predefined event class being associated with a set of similar events. Media data associated with media coverage of the event may be retrieved and data elements may be extracted from the media data, wherein the data elements include at least one quantified communication parameter including at least one of a short term media coverage volume, a publication weight, a tonal balance, and an impact of available photographs. A prediction of the upcoming media coverage of the event may be generated, including a predicted volume and tonality of the upcoming media coverage, wherein said prediction is generated using a modeling computer system, a numerical model, said extracted data elements, and information about said predefined event class.

Abstract: A financial methodology for the analysis of events' impact on media coverage and business, and predictive indications of movements of stock prices (or other financial instruments) triggered by media and business impact is described. The methodology is based on a numerical approach suitable for processing by a computer. It takes into account data outside the traditional realm of finance, such as public sensitivity to certain classes of events, and the correlation between media coverage and stock price performance during the course of an event.

Abstract: The methodology draws from three disciplines, namely public relations, social network analysis and computer-based information extraction. The analysis permits the visualization of how various people, organizations, products, subjects, key messages etc. are linked/form a network dynamic in media coverage. This type of analysis can assist corporations and other organizations to understand, plan and measure the effectiveness of communication.

Abstract: A financial methodology for examining, explaining and predicting the spread between analyst targets and stock prices, by analyzing how investor confidence is impacted by media coverage and correlating this to the spread. The methodology is based on a quantitative approach suitable for numerical processing. It measures the confidence along several categories, and allows for industry benchmarking.