Abstract: A method and system. The method includes receiving datacenter context input information, processing the datacenter context input information, and outputting the cost-versus-datacenter-quantity information. The processing the datacenter context input information may generate the cost-versus-datacenter-quantity information. The cost-versus-datacenter-quantity information is a total datacenter cost to run an application versus a quantity of datacenters used to run the application.

Abstract: A method of identifying targeted content includes deploying a plurality of internet bots configured to interact with content sources using predetermined patterns and profiles, wherein each individual internet bot of the plurality of internet bots includes at least one characteristic that is unique relative to the rest of the plurality of internet bots, collecting cause and effect data related to cause and effect of user interactions with content sources, receiving the cause and effect data collected by the plurality of internet bots, correlating user interactions with content sources using the cause and effect data collected by the plurality of internet bots, and identifying, how content is targeted to users by content sources from the correlating.

Abstract: Approaches presented herein enable tailoring messages to enhance sharing and resonance based on a community fingerprint and a key influencer. More specifically, a message to be directed to members of an online social community is received. Members of the social community who influence the social community and their likelihood to re-share messages are identified. A re-share fingerprint for the identified influencer is generated that maps the influencer's likelihood to re-share content. A communications fingerprint of the community is also created using an amalgamation of the communication patterns and styles of individual members of the community. The received message is optimized to most effectively target the message to the online social community and to solicit a desired response from the community based on the community communication fingerprint. The optimized message can then be forwarded to the online social community.

Abstract: A method of identifying targeted content includes deploying a plurality of internet bots configured to interact with content sources using predetermined patterns and profiles, wherein each individual internet bot of the plurality of internet bots includes at least one characteristic that is unique relative to the rest of the plurality of internet bots, collecting cause and effect data related to cause and effect of user interactions with content sources, receiving the cause and effect data collected by the plurality of internet bots, correlating user interactions with content sources using the cause and effect data collected by the plurality of internet bots, and identifying, how content is targeted to users by content sources from the correlating.

Abstract: A computer-implemented for delivering tailored content to an individual includes: obtaining, by a computer system, communications of the individual; obtaining, by the computer system, a communication fingerprint for the individual based on analysis of the communications of the individual; tailoring, by the computer system, a message to the individual using the communication fingerprint; and delivering the message to the individual. Using sentiment analysis combined with a unique communication fingerprint for an individual advantageously provides for a more tailored, and thus more effective, communication to the individual.

Abstract: Approaches presented herein enable tailoring messages to enhance sharing and resonance based on a community fingerprint and a key influencer. More specifically, a message to be directed to members of an online social community is received. Members of the social community who influence the social community and their likelihood to re-share messages are identified. A re-share fingerprint for the identified influencer is generated that maps the influencer's likelihood to re-share content. A communications fingerprint of the community is also created using an amalgamation of the communication patterns and styles of individual members of the community. The received message is optimized to most effectively target the message to the online social community and to solicit a desired response from the community based on the community communication fingerprint. The optimized message can then be forwarded to the online social community.

Abstract: Approaches presented herein enable tailoring messages to enhance sharing and resonance based on a community fingerprint and a key influencer. More specifically, a message to be directed to members of an online social community is received. Members of the social community who influence the social community and their likelihood to re-share messages are identified. A re-share fingerprint for the identified influencer is generated that maps the influencer's likelihood to re-share content. A communications fingerprint of the community is also created using an amalgamation of the communication patterns and styles of individual members of the community. The received message is optimized to most effectively target the message to the online social community and to solicit a desired response from the community based on the community communication fingerprint and the re-share fingerprint of the influencer. The optimized message can then be forwarded to the online social community.

Abstract: A computer-implemented for delivering tailored content to an individual includes: obtaining, by a computer system, communications of the individual; obtaining, by the computer system, a communication fingerprint for the individual based on analysis of the communications of the individual; tailoring, by the computer system, a message to the individual using the communication fingerprint; and delivering the message to the individual. Using sentiment analysis combined with a unique communication fingerprint for an individual advantageously provides for a more tailored, and thus more effective, communication to the individual.

Abstract: A computer-implemented for delivering tailored content to an individual includes: obtaining, by a computer system, communications of the individual; obtaining, by the computer system, a communication fingerprint for the individual based on analysis of the communications of the individual; tailoring, by the computer system, a message to the individual using the communication fingerprint; and delivering the message to the individual. Using sentiment analysis combined with a unique communication fingerprint for an individual advantageously provides for a more tailored, and thus more effective, communication to the individual.

Abstract: Approaches presented herein enable tailoring messages to enhance sharing and resonance based on a community fingerprint and a key influencer. More specifically, a message to be directed to members of an online social community is received. Members of the social community who influence the social community and their likelihood to re-share messages are identified. A re-share fingerprint for the identified influencer is generated that maps the influencer's likelihood to re-share content. A communications fingerprint of the community is also created using an amalgamation of the communication patterns and styles of individual members of the community. The received message is optimized to most effectively target the message to the online social community and to solicit a desired response from the community based on the community communication fingerprint and the re-share fingerprint of the influencer. The optimized message can then be forwarded to the online social community.

Abstract: A method and system. The method includes receiving datacenter context input information, processing the datacenter context input information, and outputting the cost-versus-datacenter-quantity information. The processing the datacenter context input information may generate the cost-versus-datacenter-quantity information. The cost-versus-datacenter-quantity information is a total datacenter cost to run an application versus a quantity of datacenters used to run the application.

Abstract: A computer-implemented for delivering tailored content to an individual includes: obtaining, by a computer system, communications of the individual; obtaining, by the computer system, a communication fingerprint for the individual based on analysis of the communications of the individual; tailoring, by the computer system, a message to the individual using the communication fingerprint; and delivering the message to the individual. Using sentiment analysis combined with a unique communication fingerprint for an individual advantageously provides for a more tailored, and thus more effective, communication to the individual.

Abstract: An approach for responding to a threat in a networked computing environment (e.g., a cloud computing environment) is provided. In an embodiment, a set of associations to a virtual machine (VM) instance are established, each association indicating a relationship between the VM instance and a related VM instance. Each of the associations in the set of associations is assigned a strength attribute. When a threat is detected in a VM instance, a first preventative measure is performed on a first related VM instance, the strength of which is determined based on the strength attribute that corresponds to the association between the VM instance and the first related VM instance. A second preventative measure is performed on a second related VM instance, the strength of which is based on the strength attribute that corresponds to the association between the VM instance and the second related VM instance.

Abstract: An approach for responding to a threat in a networked computing environment (e.g., a cloud computing environment) is provided. In an embodiment, a set of associations to a virtual machine (VM) instance are established, each association indicating a relationship between the VM instance and a related VM instance. Each of the associations in the set of associations is assigned a strength attribute. When a threat is detected in a VM instance, a first preventative measure is performed on a first related VM instance, the strength of which is determined based on the strength attribute that corresponds to the association between the VM instance and the first related VM instance. A second preventative measure is performed on a second related VM instance, the strength of which is based on the strength attribute that corresponds to the association between the VM instance and the second related VM instance.