Abstract: Disclosed is a system and method to collect data from a plurality of data sources to quantify the sentiment of users and predict objective outcomes. The method includes the step of collecting sentiment data from the first data sources associated with the user to determine an opinion of the user pertaining to products, and services through a sentiment analysis module. The method includes the step of collecting action data from the second data sources associated with the user to determine the behavior of the user through a behavioral analysis module. The second data sources include social media platforms, digital shopping platforms, and native applications. The method includes the step of collecting demographic data of the user from the third data sources to determine the profile of the user through a demographic profiling module. The third data source comprising a telecom server.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Personally identifiable information is not collected. The sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. The first or second activity information can include a cookie, which can be used to identify a node in a social graph as being representative of a particular person or user. When a match is not found, a fingerprinting approach can be performed using attributes, such as device identifiers: IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, or behavioral patterns.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Personally identifiable information is not collected. The sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. The first or second activity information can include a cookie, which can be used to identify a node in a social graph as being representative of a particular person or user. When a match is not found, a fingerprinting approach can be performed using attributes, such as device identifiers; IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, or behavioral patterns.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Personally identifiable information is not collected. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. Building of the social graph can include creating an edge in the social graph that is representative of a particular category type. Based on the social graph, personalized digital content can be selected.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Personally identifiable information is not collected. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. For example, the sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. Building of the social graph can include creating or updating an edge in the social graph that is representative of a particular category type.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Personally identifiable information is not collected. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. Building of the social graph can include creating an edge in the social graph that is representative of a particular category type. Based on the social graph, personalized digital content can be selected.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. Interest of a node can be inferred based on edges between first-degree and second-degree nodes.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Personally identifiable information is not collected. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. For example, the sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. Building of the social graph can include creating or updating an edge in the social graph that is representative of a particular category type.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. Interest of a node can be inferred based on edges between first-degree and second-degree nodes.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. A technique can include a sender sending a first link to at least one recipient. When a first node representative of the sender in a social graph is not identified and after receiving the activity information, creating a second node to represent the sender in the social graph. The social graph can be updated based on a recency of the sharing activity.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. Building of the social graph can include creating an edge in the social graph that is representative of a particular category type. Based on the social graph, personalized digital content can be selected.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. For example, the sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. Building of the social graph can include creating or updating an edge in the social graph that is representative of a particular category type.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. A technique can include a sender sending a first link to at least one recipient. When a first node representative of the sender in a social graph is not identified and after receiving the activity information, creating a second node to represent the sender in the social graph. The social graph can be updated based on a recency of the sharing activity.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. The system includes receiving activity information, identifying nodes in a social graph related to the activity information, and updating weights of edges based on the activity information.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. Building of the social graph can include creating an edge in the social graph that is representative of a particular category type. This includes identifying nodes in a social graph corresponding to sharing activity and adjusting weights associated with edges.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. Building of the social graph can include creating an edge in the social graph that is representative of a particular category type. Based on the social graph, personalized digital content can be selected.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. For example, the sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. Building of the social graph can include creating an edge in the social graph that is representative of a particular category type.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. Building of the social graph can include creating an edge in the social graph that is representative of a particular category type. This includes identifying nodes in a social graph corresponding to sharing activity and adjusting weights associated with edges.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. A technique can include a sender sending a first link to at least one recipient. When a first node representative of the sender in social graph is not identified and after receiving the activity information, creating a second node to represent the sender in the social graph.

Abstract: A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Sharing activity between two users will affect ads or content that both users will be presented while surfing the Web. This sharing activity includes sending of links, sending of videos, sending of files, cutting and pasting of content, sending text messages, and sending of e-mails. The system includes receiving activity information, identifying nodes in a social graph related to the activity information, and updating weights of edges based on the activity information.