HK1160266A - System and method for online advertising using user social information - Google Patents

Description

System and method for online advertising using user social information

Technical Field

The present invention relates generally to computer systems, and more particularly to an improved system and method for online advertising using user social information.

Background

Traditionally, there are two internet advertising market segments. One is text advertisement chunking and the other is banner chunking. Text advertising services are conducted primarily through sponsored search auctions (sponsored search auctions) and content matching techniques. Sponsored search auctions are a widely used mechanism for selling online advertisements using internet search engines. Each time a user enters a search term into a search engine, a sponsored search auction allocates advertising space in the user's search results. There are billions of separate online sponsored search auctions conducted each day. Content matching is also a widely used mechanism for selling online advertisements by matching advertisements to content published on the internet. Each time a user requests published content, advertising space may be allocated in the content provided in response to the user's request.

For example, in an online search advertisement, keywords of a user query may be auctioned to an advertiser (advertiser) that is the highest bidder with a sufficient budget. In content matching, page content may be aggregated into keywords, and advertisements may be matched to content using the highest payment amount provided by an advertiser for keywords representing that content.

For banner advertisement blocking, behavioral targeting techniques have been used in which both a user and an advertisement are mapped into a category, and then advertisements in the same category as the user will be provided to the user. Unfortunately, the classifications may be defined by marketers relying on their experience rather than by the user's experience and social interest. Further, the categories may be defined with a hierarchy that may focus on a vertical area, such as travel or shopping, and thus may unnecessarily limit the selection of advertisements within the vertical area without considering the user's widespread interest.

There is a need for a way to provide advertisements that are more relevant to the interests of the user. Such systems and methods should consider the user's experience and social interests to provide more relevant advertisements.

Disclosure of Invention

The invention provides a system and a method for online advertising using user social information. An advertisement demand engine may be provided for using user social information and online behavior to select advertisements to provide to a user for display. In general, advertisements that were previously selected by some user or other users belonging to a network constructed using social information and online behavior may be sent to users belonging to the same network in response to a request to provide advertisements. An advertisement correlation engine may be provided for correlating one advertisement with another advertisement or clustering (cluster) correlated advertisements, and a social network engine may be provided for building multiple networks of correlated users from social network information and online behavior to provide one or more advertisements to users for display at the time of online advertising.

To provide advertisements using user social information and online behavior, multiple networks representing user relationships may be constructed from the social information and online behavior, which may be updated with additional online behavior. In one embodiment for applying user social information in online advertising to provide advertising to other users, a request to provide a first advertisement to a first user belonging to a network constructed from social information and online behavior of a plurality of users may be received and the first advertisement may be sent to the first user. The first user may click on the first advertisement and the network may be updated with an event that the first user clicked on the first advertisement. A request may be received to provide a second advertisement to a second user belonging to the same network constructed from social information and online behavior of a plurality of users. The network may be searched to find an advertisement clicked on by the user, and a first advertisement clicked on by a first user may be sent to a second user.

In another embodiment for applying user social information in online advertising to provide a plurality of advertisements to a user, a request may be received to provide a first advertisement to a first user belonging to a network constructed from social information and online behavior of a plurality of users. A list of advertisements selected by users in the network may be determined and this list of advertisements may be ranked, for example, sequentially by a score (score) of a weighted edge (weighted edge) connecting the user to the first user in the network. One or more advertisements may then be sent from the ranked list of advertisements to the first user.

In yet another embodiment, a request may be received to provide a first advertisement to a first user belonging to a plurality of networks constructed from social information and online behavior of a plurality of users. A list of advertisements selected by users in the plurality of networks may be determined and this list of advertisements may be ranked, for example, sequentially by a score of weighted edges connecting users to the first user in the plurality of networks. One or more advertisements may then be sent from the ranked list of advertisements to the first user. Subsequently, in response to a request to provide a second advertisement to a second user belonging to a plurality of networks constructed from social information and online behavior of the plurality of users, one or more advertisements may be provided to the second user from the ranked list of advertisements.

The present invention may support many applications for online advertising using user social information. For example, an online search advertising application may use the present invention to utilize user social information to select a list of advertisements for a web page placement location that is displayed with the user's query results. Alternatively, an online content application may use the present invention to utilize user social information to select a list of advertisements for a web page placement location to display with content requested by a user. Similarly, an email application may use the present invention to utilize user social information to select a list of advertisements to be displayed with a message from an inbox requested by a user, or an e-commerce application may use the present invention to utilize user social information to select a list of advertisements to be displayed with product information requested by a user. For each of these online applications, the list of advertisements may be selected by the present invention for display to the user using the user social information.

Other advantages will become apparent from the following detailed description taken in conjunction with the accompanying drawings, in which:

drawings

FIG. 1 is a block diagram generally representing a computer system into which the present invention may be incorporated;

FIG. 2 is a block diagram generally representing an exemplary architecture of system components for online advertising using user social information, in accordance with an aspect of the present invention;

FIG. 3 is a flowchart generally representing the steps undertaken in one embodiment for building a plurality of networks representing user relationships based on social networking information and online behavior, in accordance with an aspect of the present invention;

FIG. 4 is a flow diagram that generally represents the steps undertaken in one embodiment for applying user social information in online advertising to provide advertising to other users in accordance with an aspect of the present invention;

FIG. 5 is a flow diagram that generally represents the steps undertaken in one embodiment for applying user social information in online advertising to provide multiple advertisements to a user, in accordance with an aspect of the present invention; and

FIG. 6 is a flow diagram that generally represents the steps undertaken in one embodiment for applying user social information in online advertising to provide multiple advertisements to multiple users in accordance with an aspect of the present invention.

Detailed Description

Example operating Environment

FIG. 1 illustrates suitable components in an example embodiment of a general purpose computing system. This example embodiment is only one example of suitable components and is not intended to suggest any limitation as to the scope of use or functionality of the invention. Neither should the configuration of the components be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary embodiments of the computer system. The invention is operational with numerous other general purpose or special purpose computing system environments or configurations.

The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in local and/or remote computer storage media including memory storage devices.

With reference to FIG. 1, an exemplary system for implementing the invention may include a general purpose computer system 100. Components of computer system 100 may include, but are not limited to, a CPU or central processing unit 102, a system memory 104, and a system bus 120 that couples various system components including the system memory 104 to the processing unit 102. The system bus 120 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus also known as Mezzanine bus.

Computer system 100 may include a variety of computer readable media. Computer readable media can be any commercially available media that can be accessed by computer system 100 and includes both volatile and nonvolatile media. For example, computer-readable media may include volatile and nonvolatile computer storage media implemented in any method or technology for storage of information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by computer system 100. Communication media may include computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery media. The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. For example, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media.

The system memory 104 includes computer storage media in the form of volatile and/or nonvolatile memory such as Read Only Memory (ROM)106 and Random Access Memory (RAM) 110. A basic input/output system 108(BIOS), containing the basic routines that help to transfer information between elements within computer system 100, such as during start-up, is typically stored in ROM 106. In addition, RAM 110 may contain operating system 112, application programs 114, other executable code 116, and program data 118. RAM 110 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by CPU 102.

The computer system 100 may also include other removable/non-removable, volatile/nonvolatile computer storage media. By way of example only, FIG. 1 illustrates a hard disk drive 122 that reads from or writes to non-removable, nonvolatile magnetic media and storage 134, storage 134 may be an optical or magnetic disk drive that reads from or writes to removable, nonvolatile storage media 144 such as an optical or magnetic disk. Other removable/non-removable, volatile/nonvolatile computer storage media that can be used in the exemplary computer system 100 include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like. The hard disk drive 122 and storage device 134 are typically connected to the system bus 120 through an interface, such as a storage interface 124.

The drives and their associated computer storage media discussed above and illustrated in FIG. 1, provide storage of computer readable instructions, executable code, data structures, program modules and other data for the computer system 100. In FIG. 1, for example, hard disk drive 122 is illustrated as storing operating system 112, application programs 114, other executable code 116, and program data 118. A user may enter commands and information into the computer system 100 through input devices 140 such as a keyboard and pointing device, commonly referred to as a mouse, trackball or touch pad, electronic digitizer or microphone. Other input devices may include a joystick, joystick (game pad), satellite dish, scanner, or the like. These and other input devices are often connected to the CPU 102 through an input interface 130 that is coupled to the system bus, but may be connected by other interface and bus structures, such as a parallel port, game port or a Universal Serial Bus (USB). A display 138 or other type of video device is also connected to the system bus 120 via an interface, such as a video interface 128. In addition, output devices 142, such as speakers and printers, may be connected to the system bus 120 through an output interface 132 or similar computing device.

The computer system 100 may operate in a networked environment using the network 136 to network one or more remote computers, such as a remote computer 146. The remote computer 146 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer system 100. The network 136 shown in FIG. 1 may include a Local Area Network (LAN), a Wide Area Network (WAN), or other types of networks. Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets and the Internet. In a networked environment, executable code and applications may be stored in the remote computer. By way of example, and not limitation, FIG. 1 illustrates remote executable code 148 as residing on remote computer 146. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used. Those skilled in the art will also appreciate that many of the components of computer system 100 may be implemented in a system-on-a-chip architecture, including memory, external interfaces, and an operating system. System-on-a-chip implementations are common for special purpose handheld devices such as mobile phones, digital music players, personal digital assistants, and the like.

Online advertising using user social information

The present invention relates generally to systems and methods for online advertising using user social information. In general, advertisements that were previously selected by a user or other users belonging to a network constructed using social information and online behavior may be sent to users belonging to the same network in response to a request to provide advertisements. To provide advertisements using user social information and online behavior, multiple networks representing user relationships may be built from the social information and online behavior, and these networks may be updated with additional online behavior. In various embodiments, a network may be searched for one or more advertisements selected by users in the network, and the advertisements may be ranked sequentially, for example, by a score of weighted edges in the network connecting those users to the users to be served advertisements. One or more of these advertisements may then be sent to the user to be served the advertisements in the ranked list of advertisements. In particular, advertisements may be assigned to web page placement locations and provided to users for display in online advertisements. As used herein, a web page placement location may refer to a location on a web page designated for placement of an advertisement for display.

It will be appreciated that the present invention may support many online advertising applications for online advertising using user social information. For example, an online search advertising application may use the present invention to utilize user social information to select a list of advertisements for a web page placement location that is displayed with the user's query results. Or an online content application may use the present invention to utilize user social information to select a list of advertisements for a web page placement location that is displayed with the content requested by the user. It will be appreciated that the various block diagrams, flow charts and scenarios described herein are merely examples, and that there are many other scenarios to which the present invention will apply.

Turning to FIG. 2 of the drawings, a block diagram is shown that generally represents an example architecture of system components for online advertising using user social information. Those skilled in the art will appreciate that the functions implemented in the various blocks shown in the figures may be implemented as separate components or the functions of several or all of the blocks may be implemented in a single component. For example, the functionality of the social network engine 218 may be included in the same component as the ad demand engine 212. Alternatively, the functionality of the ad demand engine 212 may be implemented as a separate component from the ad serving engine 210. Further, those skilled in the art will appreciate that the functions implemented in the blocks illustrated in the figures may be performed in a single computer or may be distributed across multiple computers for execution.

In various embodiments, the client computer 202 may be operatively coupled to one or more servers 208 through the network 206. Client computer 202 may be a computer such as computer system 100 of FIG. 1. The network 206 may be any type of network, such as a Local Area Network (LAN), a Wide Area Network (WAN), or other types of networks. The Web browser 204 is executable on the client computer 202 and may include functionality for receiving a request for content, which may be input by a user, and for sending the request to a server to obtain the requested content. In general, the web browser 204 can be any type of interpreted or executable software code, such as kernel components, applications, scripts, libraries, objects that utilize methods, and the like. In various embodiments, other applications may be used to send requests for content, including email applications that request messages from an inbox, e-commerce applications that request product information, online search advertising applications that request search results for queries, and the like.

The server 208 may be any type of computer system or computing device, such as the computer system 100 of FIG. 1. In general, server 208 may provide services for processing requests for content and may include services for providing listings for advertisements that accompany requested content. In particular, the server 208 may include an advertisement serving engine 210 for serving advertisements, an advertisement demand engine 212 for serving a list of one or more advertisements for accompanying requested content, an advertisement correlation engine 214 for correlating advertisements, and a social network engine 218 for building a network of correlated users from social network information and online behavior. The ad correlation engine 214 may include an ad clustering engine 216 for clustering ads. The social network engine 218 may include a user behavior correlation engine 220 for associating a user with another user by applying user profile information, such as contacts, buddy lists, and other extrinsic social network information, and applying user online behavior, such as user-selected advertisements. The social network engine 218 may also include a network clustering engine 222 for merging networks of associated users. Each of these modules may also be any type of executable software code, such as a kernel component, an application program, a linked library, an object that utilizes a method, or other type of executable software code.

The server 208 may be operatively coupled to a database of information, such as a storage 224, and the storage 224 may include a list 226 of any type of advertisements 228 and a network 230 of users 232. In one embodiment, the advertisement 228 may be displayed according to the web page placement location 234. The web page placement location 234 may include a Uniform Resource Locator (URL)236 of the web page, a location 238 for displaying advertisements on the web page, and a target ID 240, the target ID 240 for providing a reference to a user target or group that may be defined by a characteristic network that may match web page visitors. In various embodiments, the goals may be defined by demographic information including gender, age, or surfing behavior. In various embodiments, the user network may coexist with existing chunking methods, including demographics-based chunking methods.

Those skilled in the art will also appreciate that many of the components of the computer system 100 and system components for online advertising using user social information shown in FIG. 2 may be implemented in a system-on-chip architecture that includes memory, an external interface, an operating system, and an advertisement rendering engine. System-on-a-chip implementations are common for special purpose handheld devices such as mobile phones, digital music players, personal digital assistants, and the like.

There are many applications that can use the present invention for online advertising using user social information. For example, an online search advertising application may use the present invention to utilize user social information to select a list of advertisements for a web page placement location that is displayed with the user's query results. Alternatively, an online content application may use the present invention to utilize user social information to select a list of advertisements for a web page placement location that are displayed with content requested by a user. Similarly, an email application may use the present invention to select a list of advertisements to be displayed with a message from an inbox requested by a user using user social information, or an e-commerce application may use the present invention to select a list of advertisements to be displayed with product information requested by a user using user social information. For any of these online applications, a list of advertisements may be selected for display to the user by the present invention using the user social information.

FIG. 3 presents a flowchart generally representing the steps undertaken in one embodiment for building multiple networks representing user relationships based on social networking information and online behavior. At step 302, a plurality of networks representing user relationships may be constructed from social network information and online behavior. In one embodiment, extrinsic social networking information, such as contact lists, buddy lists, friend announcements, and the like, may be obtained for a user. Extrinsic social networking information may be used to construct a network map of a user. In various embodiments, an edge between a user and other users in a social network may be utilized to construct a bidirectional weighted graph. Information from online behavior may then be used to add users to the graph, add edges between users in the graph, and/or change weights assigned to edges between users in the graph. For example, a group of users may frequently browse a particular online photo service. New weighted edges between users in this group may be added or the weights of existing edges between users of the group may be changed.

At step 304, multiple networks may be updated with additional information from the online activity. For example, information from online behavior such as browsing photos in a particular photo service or clicking on the same advertisement may then be used to add users to the graph, add edges between users in the graph, and/or change weights assigned to edges between users in the graph. In one embodiment, the machine learning technique may obtain an association between users and the pages they have visited, and may give a higher weight to a connection between two users if they have visited more of the same or similar web pages.

The updated network representing user relationships based on social networking information and online behavior may then be clustered at step 306. In one embodiment, clustering of updated networks may be achieved using hierarchical clustering. In other embodiments, clustering of the updated network may be accomplished using a partition clustering algorithm. In various embodiments, two updated networks may be clustered together when there is a strong association between advertisements that are predicted based on the two networks.

Once the updated networks are clustered, the updated networks in the same cluster may be merged at step 308, and then multiple networks representing user relationships may be output at step 310. Many online applications may use the network to apply user social information to online advertisements.

FIG. 4 presents a flowchart generally representing the steps undertaken in one embodiment for applying user social information in online advertising to provide advertising to other users. At step 402, a first request to provide an advertisement to a first user belonging to a network representing user relationships based on social networking information and online behavior may be received. At step 404, a first advertisement may be sent in response to a first request to provide an advertisement to a first user.

At step 406, an indication that the first user clicked on the provided first advertisement may be received. At step 408, an event that the first user clicks on the provided first advertisement may be applied to update the first user's network representing user relationships in terms of social network information and online behavior. When a request to find another advertisement for another user connected to the first user in the same network is received, the network may be searched and the advertisement clicked on by the first user may be selected. At step 410, a second request to provide an advertisement to a second user belonging to the same network as the first user, the network representing user relationships based on social networking information and online behavior, may be received. In step 412, the network may be searched to find a user connected to the second user and the advertisements that the user clicked on. For example, the second user may be connected to the first user and may find a first advertisement that was previously clicked on by the first user. At step 414, the first advertisement may be transmitted in response to a second request to provide an advertisement to a second user.

FIG. 5 presents a flowchart generally representing the steps undertaken in one embodiment for applying user social information in online advertising to provide multiple advertisements to a user. At step 502, a first request to provide an advertisement to a first user belonging to a network representing user relationships based on social networking information and online behavior may be received. At step 504, a list of advertisements selected by other users in the same network may be determined. In one embodiment, a list of advertisements that were previously clicked on by other users in the network that are connected to the first user by a higher weighted edge may be selected.

Once the list of advertisements that were previously clicked on by users in the network is selected, the list of advertisements that were previously clicked on by other users in the network may be ranked in order by the score of the weighted edge connecting these other users to the first user at step 506. And at step 508, at least one advertisement in the ranked list of advertisements may be transmitted to the first user.

FIG. 6 presents a flowchart generally representing the steps undertaken in one embodiment for applying user social information in online advertising to provide multiple advertisements to multiple users. At step 602, a first request to provide an advertisement to a first user may be received, wherein the first user belongs to a plurality of networks representing user relationships according to social network information and online behavior. At step 604, a list of advertisements selected by other users in the plurality of networks may be determined. In one embodiment, a list of advertisements that were previously clicked on by other users in the plurality of networks that are connected to the first user by weighted edges may be selected.

Once a list of advertisements that have been previously clicked on by other users in the plurality of networks is selected, the list of advertisements that have been previously clicked on by other users in the plurality of networks may be ranked in order by the score of the weighted edges connecting the other users to the first user in the plurality of networks at step 106. At step 608, at least one advertisement in the ranked list of advertisements may be transmitted to the first user.

At step 610, a request to provide an advertisement to a second user may be received, where the second user belongs to a plurality of networks representing user relationships based on social networking information and online behavior. At step 612, the multiple networks may be searched to find a list of ranked advertisements that were clicked on by users connected to the second user. In one embodiment, a second user may be connected to the first user by a weighted edge, and a ranked list of advertisements selected for the first user that were previously clicked on by other users in the plurality of networks may also be selected for providing at least one advertisement to the second user. And at step 614, at least one advertisement in the ranked list of advertisements may be transmitted in response to a second request to provide advertisements to a second user.

Those skilled in the art will appreciate that the present invention may associate an advertisement with a user based on social networking information and online behavior through an indication of the user's interest in a particular advertisement, rather than through the user selecting a link to the advertisement. For example, in addition to showing interest in an advertisement by selecting a link to the advertisement, a user may also mouse over the link to the advertisement or a graphical advertisement to indicate interest. Alternatively, the impression conversion rate of the advertisement may be used. Further, different indications of user interest may be combined to generate a user interest score. Such scores may also be weighted with other factors such as revenue potential, placement goals, and the like.

Thus, the present invention can provide advertisements using user social information and online behavior. By providing more relevant advertisements to users, the click through rate of advertisements provided to users may be increased, and in turn, revenue from online advertisements may also enjoy a concurrent increase. Advantageously, the system and method are able to respond to changes in user interest in online advertisements by tracking user click history and updating the network of associated users based on social networking information and online behavior. The network may also be updated using an analysis of the user's web browser history. In addition to increasing revenue, providing advertisements in which a user is interested may also improve the user experience in many online advertising applications. Importantly, the system and method are well suited for different types of rich media advertisements, including video advertisements, internet TV, music advertisements, graphical advertisements, and text advertisements.

From the foregoing detailed description, it can be seen that the present invention provides an improved system and method for online advertising using user social information. An advertisement demand engine may be provided for selecting advertisements to provide to users for display using user social information and online behavior. A social networking engine may be provided for building a plurality of networks of associated users from social networking information and online behavior. These networks can be updated with additional online behavior. Advertisements that were previously selected by some user or other users belonging to a network constructed using social information and online behavior may be sent to users belonging to the same network in response to a request to provide advertisements. Many applications may use the present invention for online advertising using user social information, including: the online search advertising application uses the present invention to select a list of advertisements for placement of web pages, which is displayed together with the user's query result, using the user social information, or the online content application uses the present invention to select a list of advertisements for placement of web pages, which is displayed together with the content requested by the user, using the user social information. As a result, the system and method provide significant advantages and benefits needed for contemporary computing, and more particularly, for online applications.

While the invention is susceptible to various modifications and alternative constructions, certain illustrated embodiments thereof are shown in the drawings and have been described above in detail. It should be understood, however, that there is no intention to limit the invention to the specific forms disclosed, but on the contrary, the intention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention.

Claims (20)

1. A computer system for online advertising, comprising:

an advertisement demand engine to select one or more advertisements to display to a user using user social information and online behavior; and

a storage device operatively coupled to the advertisement demand engine for storing a plurality of networks of a plurality of users, each network constructed from social information and online behavior of at least some of the plurality of users.

2. The system of claim 1, further comprising an advertisement association engine operatively coupled to the advertisement demand engine for associating advertisements with previously served advertisements for display to a user.

3. The system of claim 2, further comprising an advertisement clustering engine operatively coupled to the advertisement correlation engine for clustering a plurality of correlated advertisements.

4. The system of claim 1, further comprising a social networking engine operatively coupled to the advertising demand engine for constructing a plurality of networks associated with the user based on social networking information and online behavior to provide the one or more advertisements to the user for display at the time of online advertising.

5. A computer-readable medium having computer-executable components comprising the system of claim 1.

6. A computer-implemented method for online advertising, comprising:

receiving a request for providing a first advertisement to a first user belonging to a network constructed from social information and online behavior of a plurality of users;

sending the first advertisement in response to a request to provide the first advertisement to the first user belonging to a network constructed from social information and online behavior of the plurality of users;

receiving a request for providing a second advertisement to a second user, the second user belonging to the network constructed from social information and online behavior of the plurality of users; and

providing the first advertisement for display to the second user in response to a request to provide an advertisement to the second user belonging to the network constructed from the social information and online behavior of the plurality of users.

7. The method of claim 6, further comprising receiving an indication that the first user selected the first advertisement.

8. The method of claim 7, further comprising updating the network constructed from social information and online behavior of the plurality of users in response to receiving the indication that the first user selected the first advertisement.

9. The method of claim 8, further comprising searching the network constructed from the social information and online behavior of the plurality of users for an advertisement in response to receiving a request to provide the second advertisement to the second user belonging to the network constructed from the social information and online behavior of the plurality of users.

10. The method of claim 9, further comprising selecting the first advertisement found by searching the network constructed from social information and online behavior of the plurality of users.

11. A computer-readable medium having computer-executable instructions for performing the method of claim 6.

12. A computer-implemented method for online advertising, comprising:

receiving a request for providing a first advertisement to a first user belonging to at least one network constructed from social information and online behavior of a plurality of users;

determining a list of advertisements selected by at least one user in the at least one network constructed from social information and online behavior of the plurality of users;

ranking a list of advertisements selected by at least one user in the at least one network constructed from social information and online behavior of the plurality of users; and

sending at least one advertisement in the ranked list of advertisements for display to the first user.

13. The method of claim 12, wherein determining a list of advertisements selected by at least one user in the at least one network constructed from social information and online behavior of the plurality of users comprises: selecting a list of advertisements previously clicked on by at least one user in a network connected to the first user by a weighted edge.

14. The method of claim 12, wherein determining a list of advertisements selected by at least one user in the at least one network constructed from social information and online behavior of the plurality of users comprises: selecting a list of advertisements previously clicked on by at least one user of the plurality of networks connected to the first user by a weighted edge.

15. The method of claim 12, wherein ranking the list of advertisements selected by at least one user in the at least one network constructed from social information and online behavior of the plurality of users comprises: ranking the list of advertisements previously clicked on by the at least one user in the at least one network sequentially by a score of the weighted edge connecting the at least one user to the first user.

16. The method of claim 12, wherein ranking the list of advertisements selected by at least one user in the at least one network constructed from social information and online behavior of the plurality of users comprises: ranking the list of advertisements previously clicked on by the at least one user in the plurality of networks sequentially by a score of the weighted edge connecting the at least one user to the first user.

17. The method of claim 12, further comprising receiving an indication that the first user selected the at least one advertisement.

18. The method of claim 12, further comprising updating a network constructed from social information and online behavior of the plurality of users in response to receiving an indication that the first user selected the at least one advertisement.

19. The method of claim 12, further comprising sending the at least one advertisement of the ranked list of advertisements to a second user for display in response to a second request to provide an advertisement to the second user.

20. A computer-readable medium having computer-executable instructions for performing the method of claim 12.