WO2018146637A1

WO2018146637A1 - A system and method for matching opinion leaders with advertisers over social networks

Info

Publication number: WO2018146637A1
Application number: PCT/IB2018/050830
Authority: WO
Inventors: Liav CHEN; Gidon DALAL
Original assignee: Moi Media Ltd.
Priority date: 2017-02-13
Filing date: 2018-02-12
Publication date: 2018-08-16

Abstract

The present invention provides a system and method for identifying subscribers of social networks as effective presenters to promote advertisements for specific subjects over said social networks, the method comprising of the following steps: •extracting information pertaining to subscribers of social networks, said information relating to at least one of: i. persons or groups which said subscribers follow, ii. the identity of persons who follow said subscribers, iii. the subscribers' name and personal details, iv. images of said subscribers, v. information residing in said subscribers' social network pages; • scoring items of the said extracted information; • grouping subscribers of the social network into cluster structures, according to the extracted information; • identifying prominent subscribers within each cluster as opinion leaders.

Description

A SYSTEM AND METHOD FOR MATCHING OPINION

LEADERS WITH ADVERTISERS OVER SOCIAL NETWORKS

FIELD OF THE INVENTION

[0001] The presented invention generally relates to the field of Social networking, and more specifically to the field of advertising through social networks.

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

[0002] This patent application claims priority from and is related to U.S. Provisional Patent Application Serial Number 62/458, 155, filed 13 February 2017, this U.S. Provisional Patent Application

incorporated by reference in its entirety herein.

SUMMARY OF THE INVENTION

[0003] The present invention provides a method for

identifying prominent subscribers of social networks as

effective presenters to promote advertisements for specific subjects over said social networks. The method comprising of the following steps:

• extracting information pertaining to subscribers of social

networks,

said information relating to at least one of:

i. persons or groups which said subscribers followthrough social

networks,

ii. the identity of persons who follow the said subscribers through social networks, iii. the said subscribers' name and personal details, iv. images of the said subscribers

v. images uploaded by the said subscribers to the social network, and

vi. information resident in the said subscribers' social network pages;

scoring items of the said extracted information according to criteria of relevance, distinctness and certainty;

grouping subscribers of the social network into cluster structures, according to the accumulated information;

identifying prominent subscribers within each cluster as opinion leaders, who are expected to be effective presenters in promoting advertisements for specific subjects;

continuously updating the social network subscribers' information within the said cluster structures. 04] According to some embodiments the present invention further enabling the matching of said prominent subscribers of social networks with advertisers who require the said prominent subscribers' services as presenters, to promote advertisements for specific subjects over social networks, said matching

comprising the steps of:

• Obtaining requirements for advertisement from an advertiser, said requirements including at least one of:

i. the subject of advertisement

ii. the extent of publicity

iii. the duration ofpublicity

• matching between the advertiser's requirements and

clusters of subscribers of social networks, and

selecting a cluster, ora list of clusters most fitting the advertiser's requirements,

• presenting the required service prominent subscribers of social networks within the said selected clusters, and prompting them to place a bid for their service as presenters to promote the said advertisement,

• accumulating the bids from all potential presenters to the advertiser, and enabling him to select a presenter from the list,

• contacting the selected presenter, and closing the deal between the advertiser and the presenter.

BRIEF DESCRIPTION OF THE DRAWINGS

[0005] For better understanding of the invention and to show how the same may be carried into effect, reference will now be made, purely by way of example, to the accompanying

drawings.

[0006] With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of the preferred

embodiments of the present invention only, and are presented in the cause of providing what is believed to be the most useful and readily understood description of the principles and

conceptual aspects of the invention. In this regard, no attempt is made to show structural details of the invention in more detail than is necessary for a fundamental understanding of the

invention, the description taken with the drawings making

apparent to those skilled in the art how the several forms of the invention may be embodied in practice. In the accompanying drawings:

[0007] Figure 1 depicts an overall, functional block diagram, presenting the Advertisement System, its main components and

its surrounding environment;

[0008] Figure 2 depicts a functional block diagram of the Profiler subsystem and its main components;

[0009] Figures 3&4 jointly depict a flow diagram, elaborating the process of clustering followers in a social network; and

[0010] Figure 5 depicts a flow diagram, elaborating the process of mediating between an advertiser and potential presenters.

DETAILED DESCRIPTION OF SOME EMBODIMENTS OF

THE INVENTION

[0011] Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not necessarily limited in its application to the details of construction and the arrangement of the components and/or methods set forth in the following description and/or illustrated in the drawings and/or the Examples. The invention is capable of other embodiments or of being practiced or carried out in various ways.

[0012] As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a "circuit," "module" or "system." Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.

[0013] Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0014] A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0015] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wire line, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0016] Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more

programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural

programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0017] Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

[0018] These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

[0019] The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other

programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

[0020] Following is a table of definitions of the terms used throughout this application.

[0021] Figure 1 depicts an overall, functional block diagram, presenting the Advertisement System 10, its main components and its surrounding environment.

[0022] The Advertisement System 10 is a computational system implemented as any combination of hardware and software. One preferable embodiment of the Advertisement System 10 is an online Server, with access to Social networks over the Internet.

[0023] The Advertisement System 10 interfaces Social Networks 100 to extract information regarding Social network subscribers'

characteristics, and the relation of followers among subscribers of the said social network.

[0024] The Profiler subsystem 1000 analyzes the said relationships between followers in the Social Network 100, Clusters the followers according to predefined logic, and stores the said cluster data in the

Storage module 6000.

[0025] The Advertisement System 10 interfaces users of two

distinct types - Advertisers 4000 and Presenters 5000;

• Advertisers 4000 are individuals or groups of individuals that are interested in advertising items such as goods and services over the Social Network 100.

• Presenters 5000 are leaders or groups of leaders that have been detected by the Profiler subsystem 1000 as prominent opinion leaders. Such Presenters 5000 normally possess a

substantial, relevant group of followers that may be interested in the services or goods proposed by specific Advertisers

4000.

[0026] The Advertisement System 10 mediates between

Advertisers 4000 and Presenters 5000. Through this mediation, the Advertisement System 10:

Obtains requirements for advertisements from an Advertiser 4000, including at least one of:

o The subject of advertisement (e.g. specific goods, services, public service announcements)

o The extent of publicity size to exposure (e.g.

Nation-wide or local or number of expected

followers)

o Type to target advertising crowd (age, demographic

related data social-economy state, gender, location, culture, etc.)

o The duration ofpublicity

Presents to the Advertiser 4000 a list of optional Presenters 5000 that bestfit the Advertiser's 4000 cause (e.g. a list of "gurus" in the field of robotics)

• Enables Advertisers 4000 to select Presenters 5000 from the said list, contact them and offer them the task of presenting for them.

• Offers Presenters 5000 the option to accept the said offer, and

receive payment for their services as presenters.

[0027] Figure 2 depicts a functional block diagram of the Profiler 1000 subsystem and its main components.

[0028] The Profiler 1000 subsystem is a component within the

Advertisement System 10. It analyzes the relationships between followers in the Social Network 100, Clusters the followers according to predefined logic, and stores the said cluster data in the Storage module 6000.

[0029] The Profiler 1000 subsystem interfaces the social network 100, and extracts information pertaining to user details and user follow relations by either one of two methods:

⁸ Presenting queries to the social network 100 databases, via

appropriate Application Program Interfaces (APIs) 1200, and analyzing the responses to those queries, and

• Employing Scraper 1300 modules (provided for example by Octatools (www.octatools.com) that continuously monitor the activity of Social network 100 subscribers.

[0030] The Extractor 1 100 module extracts raw information regarding specific social network subscribers' characteristics (e.g. Names, Nationality, Social Network pages), and their role as Followers or 'Leaders' in the Social network 100.

[0031] The Enrichers 1400 block may incorporate four sub-modules, each designed to further analyze and articulate specific aspects of the information gathered bythe Extractor 1 100 module. The said Enricher 1400 sub-module types include at least one of the following:

• A Name Enricher 1410

• A Personal details Enricher 1420

• An Image Enricher 1430, and

• A Social Media Enricher 1440

The function of each Enricher type is explained further below.

[0032] The Enrichment combination 1500 module integrates the data emitted by the Enrichers (1410, 1420, 1430, 1440). It scores each piece of information according to criteria of relevance, distinctness and certainty, as explained further below.

[0033] The Clustering module 1800 creates clusters of followers, according to the data accumulated by the Enrichment Combination module 1500, and the identity of the persons or groups that they follow, i.e. their 'Leaders'. The properties of these clusters will be presented to Advertisers 4000 during the mediation process between Advertisers 4000 and potential Presenters 5000.

[0034] Figures 3&4 jointly depict a flow diagram, elaborating the process of clustering followers in a social network. This clustering process serves as the basis for suggesting and prioritizing potential Presenters 5000 to specific Advertisers 4000.

[0035] The Scraper 1300 constantly monitors activity of subscribers on the social network 100 (e.g. Instagram). It extracts predefined characteristics of social network subscribers, as well as their leader- follower relations (step 3010).

[0036] The Scrapers 1300 propagate this data to the Extractor 1 100 module.

[0037] The Extractor 1 100 receives social network subscribers' characteristics and the followers' data by two means (step 3020):

1. From the Scrapers 1300, as explained above

2. By employing APIs 1200, to query the Social network 100 database.

[0038] The Extractor 1 100 accumulates data pertaining to each

follower (step 3030). This data includes at least one of the

following properties:

• The follower's full name

• The follower's personal details

• Images of the follower, or images uploaded by thefollower

• The follower's social media pages.

[0039] The Extractor 1 100 propagates thefollowers' data to the

plurality of Enrichers 1400 (step 3040), which includes at least one of thefollowing Enricher- types:

• Name Enricher 1410,

• Personal details Enricher 1420 ,

• Image Enricher 1430,

• Social media Enricher 1440.

[0040] The Name Enricher 1410 extracts information relating to

the specific follower's name, e.g. Full name and Nicknames

(step 3050).

[0041] The Personal details Enricher 1420 extracts information relating to the specific follower's personal details (step 3060), e.g.:

• Gender

• Age

• Language and dialect

• Residential address

• Education

• Profession

• Hobbies

[0042] The Image Enricher 1430 applies facial recognition software to extract information relating to images of the specific follower, or uploaded by the follower. This information may include, for example the identity of people presented in the images, their gender and age (step 3070).

[0043] The Image Enricher 1430 applies additional algorithms to extract additional information relating to images uploaded by the specific follower (step 3080), such as:

• The location and date in which the image was taken (e.g. in front of the Eifel tower, last Fall)

• Activities that are taking place in the image (e.g. skiing).

• The regular appearance of specific individuals in images

uploaded by the follower

[0044] The Social Media Enricher 1440 extracts information relating to specific followers' Social media sites (e.g.: a follower's Facebook site) (step 3090). This data includes, for example:

' Appearance of specific predefined keywords

• Properties relating to Facebook friends (e.g. their quantity, their relevance to specific subjects, how often they connect or chat) • Patterns of social-networking activity, e.g.: Does this follower post his/her opinion often? On what subjects? Do they do it from home, or "on the go"?

• Followers hobbies, e.g.: Does this follower practice a specific sport?

• Group membership, e.g.: Is this follower a member of the "Anti

Fur coalition" (rendering them an inappropriate audience for a fur coat advertisement)?

• Location, e.g.: of residence, school, workplace

• Consuming habits, e.g.: Does this follower often buy clothes

online?

• Interests, e.g.: Has this follower expressed interest in Astronomy by subscribing to NASA's website, or bidding for a telescope?

[0045] The Enrichment Combination module 1500 accumulates the data extracted bythepluralityof Enrichers (1410, 1420, 1430, 1440) per eachfolloweraccording to specific keys, and scores each piece of data according to a predefined logic (step 3100). For example, the key may be a common interest in swimming, for the purpose of advertising bathing suits, and the scoring may rely upon the following criteria:

1. Relevance: Follower's properties that are relevant to specific

keys, e.g.: followers that are members of a swimming-team group on Facebook.

2. Distinctness: Data that uniquely ascertains a specific property of the follower, e.g.: thefollower is not only listed as a member of the swimming team, but is also pictured standing on the winners' podium in a swimming contest.

3. Certainty: The level of validation forspecific pieces of data, e.g.

Does the face of the winner on the podium in the blurry image really belong to that follower?

[0046] The Clustering module 1600 creates clusters of followers

(step 31 10) according to:

1. The follower-specific data accumulated by the Enrichment

Combination module 1500, and

2. The identity of the persons or groups that they follow, i.e. their L©3cl©rs

[0047] The Clustering module 1600 analyses the effectiveness of leaders within each cluster, to identify prominent leaders that may serve as potential Presenters 5000 (step 3120). Criteria for defining leaders within the cluster as potential Presenters 5000 may be:

• Their relevance to specific subjects (e.g. shopping for clothes

online)

• The quantity of followers they have

• The nature of relation these leaders have with their respective

followers (e.g. do they chat much over the network?)

[0048] The Clustering module 1600 stores the clusters' data on the

Advertisement system's storage module 6000 (step 3130). It

continuously maintains and updates this information within the storage module with any new information regarding:

• Characteristics of followers, as obtained by the plurality of Enrichers 1400,

• Followers' relation to the individuals and groups that they

follow, i.e. their 'Leaders', and

• The relevance of said 'Leaders' as opinion leaders, and their

potency as potential Presenters 5000.

The properties of these clusters will be presented to Advertisers 4000 during the process of matching between Advertisers 4000 and potential Presenters 5000. [0049] Figure 5 depicts a flow diagram, elaborating the process of mediating between an advertiser and potential presenters. The action of mediation is performed by the Bidding 2000 module, which resides within the Advertisement system 10.

[0050] The process of mediation begins with an Advertiser 4000 presenting a requirement for an advertisement (step 4010) via the Advertisement system 10. The content of such a requirement includes at least one of the following:

• The subject of advertisement (e.g.: specific goods, services, public service announcements)

® The extent of publicity, exposure size (e.g. Nation-wide or local or number of expected followers )

® Type of target advertising crowd (age, demographic related data, social economy state, gender, location, culture, etc.)

• The duration of publicity (e.g. year-round or a few days)

[0051] The Bidding 2000 module matches between the Advertiser's requirements and specific clusters of social network subscribers. It applies predefined logic, to select a cluster, or a list of clusters most fitting the Advertiser's requirement (step 4020). Examples of criteria for such a selection are:

• Subject of the requirement (e.g. advertising the service of a pension advisor)

• Locale (e.g. language, dialect, cultural background, demographic related data, social economy state)

• Personal details (e.g. gender, age, education)

• Geographic location

[0052] The bidding module 2000 performs initial bidding (step 4030), i.e. it presents the required service to a list of potential Presenters 5000 and prompts them to place a bid (step 4040) for their service.

[0053] The bidding module 2000 accumulates the bids placed by the potential Presenters 5000, and presents them to the

Advertiser 5000 (step 4050).

[0054] The Advertiser 4000 selects a specific Presenter 5000 from the suggested list (step 4060).

[0055] According to one embodiment of the present invention, the identity of the Presenters is kept unrevealed to the Advertiser until the deal is closed. This serves to avoid having the Advertiser close the deal in the absence of the Advertisement system

In this embodiment, the Advertiser 4000 will select the Presenter 5000 from the said suggested list solely by their profiles and bids, without disclosing personal details or contact information.

[0056] The Bidding module 2000 contacts the Presenter 5000 to close the deal (step 4070). According to one embodiment, the Bidding module 2000 also takes care of transferring funds between the

Advertiser 4000 and Presenter 5000, optionally charging a fee from either one of them or both of them, for the process of mediation.

[0057] The Bidding module accumulates additional information regarding each such bidding process. Examples for such information include:

• Feedback from Advertisers 4000 and Presenters 5000 regarding the mediation process

• Feedback from Advertisers 4000 and Presenters 5000

regarding their content with each other's performance

• Popularity of specific Advertisers 4000 and Presenters 5000

• Prices for each type of service

This information is stored on the Storage module 6000, and may serve to refine the process of follower clustering.

Claims

1. A computerized method for identifying prominent subscribers of social networks as effective presenters to promote

advertisements for specific subjects over said social networks, the method comprising the following steps:

a. extracting information pertaining to subscribers of

social networks, said information relating to at least one of:

i. persons or groups which said subscribers follow

through social networks,

ii. the identity of persons who follow the said subscribers through social networks,

iii. the said subscribers' name and personal details, iv. images of the said subscribers

v. information residing in the said subscribers'

social network pages;

b. scoring items of the said extracted information according

to criteria of relevance, distinctness and certainty; c. grouping subscribers of the social networks into

cluster structures, according to the extracted

information; and

d. identifying prominent subscribers within each cluster as opinion leaders, who are expected to be effective presenters in promoting advertisements for specific subjects.

2. The method of claim 1 , further enabling the matching of said

prominent subscribers of social networks with advertisers who require the said prominent subscribers' services as presenters, to promote advertisements for specific subjects over social networks, said matching comprising the steps of: e. Obtaining requirements for advertisement from an

advertiser, said requirements including at least one of: i. the subject of advertisement;

ii. the extent of publicity;

iii. the duration of publicity;

f. matching between the advertiser's requirements and

clusters of subscribers of social networks, and

selecting a cluster, or a list of clusters most fitting the advertiser's requirements;

g. presenting the required service to prominent subscribers of social networks within the said selected clusters, and prompting them to place a bid for their service as potential presenters to promote the said advertisement;

h. accumulating a list of bids from all potential presenters,

presenting it to the advertiser, and enabling him to select a presenter from the list; and

i. contacting the selected presenter, and closing the deal

between the advertiser and the presenter.

3. A system for identifying prominent subscribers of social networks as effective presenters to promote advertisements for specific subjects over said social networks, comprising:

an advertisement system comprising a computer server connected via the internet to at least one social network,

comprising:

a profiler subsystem configured to relationships between followers in said at least one social network and cluster the followers according to predefined logic;

a bidding module configured to mediate between an advertiser and potential presenters, wherein said advertiser and said potential presenters communicate with said advertisement system; a storage.

4. The system of claim 3, wherein said profiler subsystem comprises at least one Application Program Interface for presenting queries to the at least one social network.

5. The system of claim 3, wherein said profiler subsystem comprises at least one scraper 1300 module for continuously monitor the activity of said at least one social network subscribers.

6. The system of claim 3, wherein said profiler subsystem comprises an extractor module configured to extract raw information regarding specific social network subscribers' characteristics and their role as Followers or 'Leaders' in said specific social network.

7. The system of claim 6, wherein said profiler subsystem comprises an enricher module communicating with said extractor module and configured to further analyze and articulate specific aspects of the information gathered by the extractor module.

8. The system of claim 7, wherein said enricher module comprises at least one of:

a personal details enricher;

an image enricher;

a social media enricher; and

a name enricher.

9. The system of claim 7, wherein said profiler subsystem comprises an enrichment combination module communicating with said enricher module and configured to integrate data emitted by said enricher module.

10. The system of claim 9, wherein said profiler subsystem comprises a clustering module communicating with said enrichment combination module and configured to create clusters of followers, according to data accumulated by said enrichment combination module and the identity of the persons or groups that they follow.

11. One or more computer-storage media embedded with computer- executable instructions, the embedded computer-executable instructions are executed by at least one processor for performing a method of claim 1 .