WO2019164354A1 - System and method for blockchain-based social network service - Google Patents

Abstract

Disclosed are a system and a method for blockchain-based social network service. According to one embodiment of the present invention, the system and the method for blockchain-based social network service have an effect of providing appropriate compensation for valuable data voluntarily made by a user.

Description

Blockchain based social network service system and method

The present invention relates to a blockchain-based social network service system and method.

Social Network Service (SNS) is an online service that creates and strengthens social relationships through free communication between users, information sharing, and networking. Companies that provide these services leverage the valuable data we create to build the richest wealth in human history. The data we use as a service is coming up with artificial intelligence and emerging as a new kind of asset. But most of us, the data producers, receive little or no benefit from it.

In this regard, Korean Patent No. 10-1216689 (registered on Dec. 21, 2012) discloses an SNS integrated management system and method.

The present invention aims to provide a blockchain-based social network service system and method that can provide appropriate compensation for valuable data that a user voluntarily creates.

Other objects of the present invention will become more apparent through the preferred embodiments described below.

According to an aspect of the present invention, a social network service providing method performed in a blockchain-based social network service system, the method comprising: receiving, by a social network service platform, user context data including location information from a user node; Evaluating the value for the user context data; And registering the user context data as a block confirmed in the blockchain, and providing a coin corresponding to the value of the user context data to the user node as a reward. .

The user context data may further include at least one of behavior information, a photo, a post, a hashtag, and a recommendation number.

In the value evaluation step, a data score for the user context data may be calculated and a reputation for the user node may be applied as a weight.

The reputation may be determined by a like score corresponding to a recommendation amount of another user for all user context data generated at the user node.

The reputation may be a result in which the reputation scores are arranged in order and the reputation scores are relatively distributed according to a normal distribution having a predetermined mean and standard deviation.

In the reward payment step, the reward may reflect the ratio of the data score to the unit time mining amount.

When a query based on the user context data is input from a company terminal, the social network service platform may query and mask a user node having a relatively high correlation with the query, and transmit the query to the company terminal that sent the query.

Payment using the coin may be required as a prerequisite for inputting the query to the company terminal.

The valuation step may include zoning a plurality of sectors based on location; Selecting a user node belonging to an intersection between any two sectors as a computing node; Calculating data scores of all user nodes belonging to the two sectors at the computing node; Calculating a reputation of all user nodes belonging to the two sectors at the computing node; Transmitting a calculation result value in which the reputation is reflected in the data score, to a verification node; And comparing and verifying the verification result value and the calculation result value self-calculated for all the user nodes in the verification node, and calculating the calculation node if the verification result value and the calculation result value are the same. If the verification result value and the calculation result value is not the same, a penalty may be given to at least one of the verification node and the calculation node that are incorrect in calculation.

The calculation by the calculation node may be performed in the public blockchain layer, and the calculation and verification by the verification node may be performed in the private blockchain layer.

The verification node may check whether there is a calculation error by comparing a verification result value with another verification node in the private blockchain layer.

The data score calculation step may calculate the data score DS _Nn using the following equation.

-LD is the number of location inputs, AD is the number of behavioral inputs, PIC is the number of photo inputs, TL is the number of text inputs, TAG is the number of hashtag inputs, LIK is the number of recommendations,

,

,

,

,

,

Is the data score ratio (weighted) for each contextual data-

Meanwhile, according to another aspect of the present invention, a blockchain-based social network service system, comprising: a user node for generating user context data including location information; Receiving the user context data from the user node, evaluating the value for the user context data, registering the user context data as a fixed block in a blockchain, and coining the user node in accordance with the value. A blockchain-based social network service system including an SNS platform for paying is provided.

The terminal further includes a company terminal for transmitting a query based on the user context data to the SNS platform, wherein the SNS platform inquires and masks a user node having a relatively high correlation with the query, and sends the company terminal to the query. Can be sent to.

Other aspects, features, and advantages other than those described above will become apparent from the following drawings, claims, and detailed description of the invention.

According to an embodiment of the present invention, there is an effect that can provide an appropriate compensation for the valuable data that the user voluntarily creates.

1 is a graph showing domestic SNS-related consumer complaints,

FIG. 2 is a diagram illustrating various stakeholders in a blockchain-based social network service ecosystem (ribin ecosystem) according to an embodiment of the present invention; FIG.

3 is an example of an advertisement that Facebook's likes do not help,

4 is a graph showing the size and forecast of the mobile advertising market,

5 is a view showing the problem to be solved in the mobile advertising market,

6 is a graph showing the market (expected) scale of e-commerce (unit: $ 1 billion),

7 is an architecture of a blockchain-based social network service (levin service) system according to an embodiment of the present invention;

8 is a graph showing the daily issue amount of bins issued by year;

9 is a cumulative issuance amount of bins for each year after the release (distribution) of the blockchain-based social network service (Rvern social network service) according to an embodiment of the present invention;

10 is a diagram illustrating a process of a blockchain-based social network service (leavin social network service) according to an embodiment of the present invention;

11 is a relative frequency distribution graph of the plate,

12 is a flowchart of a method for providing a blockchain-based social network service performed in a blockchain-based social network service system according to an embodiment of the present invention;

13 is a diagram showing the configuration of a blockchain-based social network service system according to an embodiment of the present invention.

As the present invention allows for various changes and numerous embodiments, particular embodiments will be illustrated in the drawings and described in detail in the written description. However, this is not intended to limit the present invention to specific embodiments, it should be understood to include all changes, equivalents, and substitutes included in the spirit and scope of the present invention.

When a component is referred to as being "connected" or "connected" to another component, it may be directly connected to or connected to that other component, but it may be understood that other components may be present in between. Should be. On the other hand, when a component is said to be "directly connected" or "directly connected" to another component, it should be understood that there is no other component in between.

Terms such as first and second may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. As used herein, the terms "comprise" or "have" are intended to indicate that there is a feature, number, step, action, component, part, or combination thereof described on the specification, and one or more other features. It is to be understood that the present invention does not exclude the possibility of the presence or the addition of numbers, steps, operations, components, components, or a combination thereof.

In addition, the components of the embodiments described with reference to the drawings are not limited to the corresponding embodiments, and may be implemented to be included in other embodiments within the scope of the technical spirit of the present invention. Even if the description is omitted, it is obvious that a plurality of embodiments may be reimplemented into one integrated embodiment.

In addition, in the description with reference to the accompanying drawings, the same components regardless of reference numerals will be given the same or related reference numerals and redundant description thereof will be omitted. In the following description of the present invention, if it is determined that the detailed description of the related known technology may unnecessarily obscure the subject matter of the present invention, the detailed description thereof will be omitted.

In addition, the terms “… unit”, “… unit”, “… module”, “… unit” described in the specification mean a unit that processes at least one function or operation, which means hardware or software or hardware and software. It can be implemented as a combination of.

Social network service (SNS) is used as a space for information sharing and communication between people, which is the basic purpose of the Internet. Since the rise and fall of many social networking services, Facebook, Instagram and Twitter have the most users as of 2018. The companies that run the service make money by analyzing the user's lifestyle, interests and personal information, and then providing advertisements to the service users. This revenue model has turned social network service companies into giants. For example, Facebook's 2016 advertising revenue was about $ 26.6 billion, or about 97.3% of Facebook's total sales. Facebook's operating profit, driven by advertising sales, is growing rapidly every year.

These social network services generate revenue by attracting users through content produced by content producers with time and effort, but there is a problem in that there is no return to content producers who have contributed the most to service growth. In addition, there are inconveniences that service users must be exposed to unwanted advertisements. After the introduction of smartphones, the mobile advertising market grew every year, reaching $ 143.3 billion worldwide in 2016. However, most of the advertising revenue was monopolized by ad brokers like Facebook and Google, and very few cases have been attributed to users exposed to the ad. In particular, recently, there has been a tendency that negative perceptions of users increase in unnecessary advertisements resulting from native advertisements.

1 is a graph showing domestic complaints related to SNS.

Referring to FIG. 1, it is shown that excessive commercial advertising is the biggest complaint of social network service users. Advertisement in the Internet space makes it possible to use various Internet services at a low cost. Therefore, considering the share of advertising in social network services, negative perception of advertising can have a negative effect on the service ecosystem.

Donation must be the most beautiful form of economic activity a human being can make. Many people in the world need donations and actually benefit a lot. Many donors use donation organizations such as the Red Cross and UNICEF, because donors generally cannot meet with their beneficiaries and make donations.

However, the cost of donation brokerage for various donor organizations has been socially controversial. CNN reported that during the 2010 earthquake in Haiti, the Red Cross raised more than $ 500 million in donations, but only used to build six houses. And recently, the fruit of love, one of Korea's donation foundations, has caused many donors to be disappointed by spending too much on Foundation funds.

Blockchain is a trust-based network technology that can eliminate or reduce the brokerage costs brought by brokerage agencies. Bitcoin proved that money can be kept secure without an intermediary that manages money, and Ethereum proved that smart contracts do not require an intermediary for the conclusion and implementation of a contract. Such blockchain technology has laid the foundation for minimizing or eliminating intermediary costs for advertising and donations. In the case of advertising, if the advertiser can directly select the target of the advertisement and pay the advertisement fee to the viewer, the advertisement can be performed more effectively by excluding the brokering gain obtained from the intermediary. In the case of donations, the foundation can be minimized by solving the problem that donors cannot select donors.

Hereinafter, the above-mentioned problem will be solved based on the coin, which is a blockchain-based social network service that can receive honest rewards according to an embodiment of the present invention, and coin, which is utilized in the ecosystem.

Lee and Bean provide a platform for advertising, donation and e-commerce. Levine is a social network service that evaluates the user's content and provides reasonable rewards to the bean. The beans produced here can be cashed through exchanges and used as currency in advertising and donations. Advertisers and donors can select advertising targets and beneficiary beneficiaries based on Libin-produced content. In addition, advertisers and donors can directly send advertisements and donations to the viewers and donors.

Livin provides an e-commerce service for buying relief goods or advertising items through Vienna. The user can directly purchase the item through the mined bean through his context data, and the bean obtained through the purchase of the item can be used again as an advertisement. In addition, relief goods can be purchased through donations received through donors through e-commerce. The amount of bins obtained from donations can be purchased as relief goods such as groceries, medical supplies, and educational goods, which will be supplied non-profit, unlike general goods.

2 is a diagram illustrating various stakeholders in a blockchain-based social network service ecosystem (ribin ecosystem) according to an embodiment of the present invention.

As shown in FIG. 2, the Levin social network service and the Levin platform are organically interlocked through an intermediary currency called bin to build an ecosystem. That is, operators who provide data to users who produce data, use the value to provide donations, advertisements, and data trading services, and provide goods or services can resell the value they produce. This is also in line with the philosophy of the Internet of values that is exchanged through the blockchain.

The most valuable resource of the modern age is information. In these times, the public should be able to disclose their information, gain trust in their honesty, and lead them to profit. The value of ribin and bean is to return the enormous profits generated from the consumption ecosystem to the actors of production and consumption rather than a few vested interests. Multinational digital dinosaur companies have been using their privacy indiscriminately to accumulate wealth and have not paid the parties for their privacy. This centralization of information has concentrated wealth on the part that controls the information, and most participants have suffered losses over the long term. But blockchain is a technology that leads to this decentralization. Lee Bin and Bean pay decentralized rewards to producers of information, thereby decentralizing the information and raising the legitimacy of the consumption ecosystem. Thus, Livin wants to implement decentralized consumer capitalism.

The relevant market status is as follows.

The following discusses the problems of the current advertising market and the donor market in Korea or around the world. Through this, the Levin social network service and platform will use existing problems as the calculation ground and suggest the fundamental problem solving method by achieving decentralization, the blockchain philosophy.

1) Donation Market

Many developed countries are making great efforts to make good donation policies. In the case of Korea, the donation trend, which had increased steadily until 2013, has been dampened. The reason is reported to come from the issue of transparency and trust in donor organizations. Most countries are registered and operated as donation organizations to receive tax benefits, and there is a lack of laws to secure public interest in the establishment of many donation organizations. In the case of Korea, it is based on the lack of documents and the degree of homepage. This is not only because there is a lack of clear standards for donor organizations, but because the review takes a lot of time and effort. Distrust of donor organizations has the problem that donors hesitate and donate, giving a negative image of donation to reduce donation.

It is a matter of trust in the use of donations made by donors. Haiti's case, mentioned earlier, is serious, but more specific. According to a 2014 South Korean news report, donations have been reported to be used as entertainment for Foundation employees. Donor developed countries like the United States have this problem. According to the 2016 Washington Post, Trump spent about $ 300,000 on Trump Foundation donations to solve his legal problem. This problem of transparency about where to use donations is more distrustful in countries where there is no obligation to disclose donation specifications.

Although various countries have made various efforts such as tax benefits for a long time to spread the donation culture, negative cases frequently occur due to institutional limitations. The fundamental solution to this problem is for donors to donate directly to beneficiaries. However, given the international donation environment, donors and beneficiaries are often too far apart from each other to communicate directly. In addition, many donor recipients do not have a bank account and there is no way to receive donations, and for this reason, donations are made after purchase with food or medicine, which produces another broker. Therefore, peer-to-peer donation platforms are in service in many African countries. One survey found that direct donations accounted for 33% of the total US donation. This is not a fundamental solution because it is only possible when donors and beneficiaries are close.

The LIVEEN donation platform using the blockchain according to the present embodiment provides a function of directly searching for donors meeting specific conditions based on data such as frequently living in a corresponding region. You can donate money by sending money directly from your empty wallet. The coin can be exchanged for localization through exchanges or groceries, medicines and toys through the donation mall, a non-profit shopping mall operated by the Foundation. The Vienna Foundation will run a nonprofit donation mall, and the funding will be raised from proceeds from the Levin advertising mall.

2) advertising market

The mobile advertising market has continued to grow at the same time as mobile phones.

3 is an example of advertising that Facebook's likes do not help, Figure 4 is a graph showing the size and prospect of the mobile advertising market, Figure 5 is a diagram showing the challenges to be solved in the mobile advertising market, 6 is a graph showing the market (expected) scale (unit: $ 1 billion) of electronic commerce.

Referring to Figure 4, it shows the market size and forecast of the mobile advertising market (unit: $ 1 billion). As the graph shows, the mobile advertising market has already exceeded $ 100 billion and continues to grow. Mobile advertisements are generally formed by random exposure to users using various Internet services. And in return for providing these services, companies are growing rapidly on a profit basis. However, these advertising revenues are dominated by brokerage agencies and Internet service providers who broker advertising platforms. This is true not only for search service providers like Google, but also for social network services like Facebook and Instagram.

Referring to FIG. 3, there is shown a public service advertisement telling us that 'likes' on Facebook do not help the producers of the data. This ad satirizes that there is no benefit to producers, even if they produce good content that attracts much empathy. In other words, service providers such as Facebook make huge profits by using data produced by users, but the benefits do not return to the producers of the data provided. As a result, advertisements of social network services are perceived negatively by users. However, advertising is an essential economic activity that is not only the economy of the Internet and mobile, but also a big pillar of the market economy. Considering this, it is necessary to create a just advertising ecosystem by improving the capital flow of the advertising market.

From the advertiser's point of view, the current advertising method is unreasonable because it cannot directly determine the effect of the advertisement. Advertisers pay a lot for advertising, but it's hard to see meaningful advertising results like sales growth. According to FIG. 4, the mobile advertising market is increasing year by year, but the rate of increase is gradually decreasing. One reason for this can be found in a marketing report in the United States. According to the report, mobile advertising is the most urgent task to address the issue of transparency in advertising contribution and lack of ad analysis tools. 5 shows what was investigated in this report. It can be inferred that the uncertainty of measuring advertising effectiveness is a barrier to the expansion of the advertising market. As a result, companies with large capitals are able to advertise aggressively, while local small businesses, venture capitalists and start-ups may be under pressure. In particular, there is a problem that local businesses do not have the proper advertising means. In the case of Internet or mobile advertising, it is difficult to identify the target of advertising because there are absolutely many users. Current local advertising, therefore, relies on the distribution of local newspapers, local television programs, and flyers. However, the mass media advertising has a limit that a lot of advertising costs.

For the purpose of improving the flow of advertising capital, a compensation advertising service (a service that pays a certain advertising fee when a viewer watches an advertisement) has appeared. For example, a domestic cash slide gives a virtual cyber money when an advertisement is watched on a lock screen of a mobile phone.

This cyber money can be exchanged for gift certificates such as coffee and food. In this service, the amount of compensation varies depending on the type of product, and in the case of a mobile application installed advertisement, about 35% of the advertising fee is given to the viewer who viewed the advertisement. Despite the low reward level, the service has been steadily increasing in users and generating high profits. However, it is hard to say that such cases are not only a small part of the mobile advertising market but also have a low reward level, resulting in a peer-to-peer advertisement.

The LIVEEN advertising platform according to the present embodiment may compensate the user for about 90% of the advertising fee. Based on the contextual data, advertisers can select the target audience of the customized direct advertisement, and they can set their own advertising costs. In this way, Livin can advertise rewards without an intermediary. Advertisers can not only tailor ads for their budget and ad viewers, but also reward ad viewers to reduce the stress on unwanted viewing. Levin users' contextual data is used as key data for personalized advertising to accurately determine the interests of the target audience. Reward-based customized advertising is expected to contribute greatly to improving negative perceptions of advertising. In addition, the Livin advertising platform can provide additional advertising analysis methods for advertisers. Lee Bin can directly purchase the products he watched through advertising through a service called advertising mall. In addition, the user can directly check the purchase rate, the time until the purchase decision or the number of times of viewing the advertisement. The LIVEEN platform will study ways to analyze advertising effectiveness and provide it as a marketing tool for advertisers.

3) Personal data trading market

Data is viewed by many global companies as a resource for future wealth. Recent advances in artificial intelligence technology accelerate this because data is a source for inference of artificial intelligence. Reflecting this, a variety of data markets have recently emerged that buy and sell such data. Especially in the case of personal data transactions, it is a social issue. Recently, the BBC announced that an accident occurred in Uber where 2.7 million data were leaked. Uber paid $ 100,000 and recovered it to prevent damage to personal data transactions in the illegal market. The illegal data trading market is expected to reach about $ 150 million by 2020. Legal data transactions are also socially problematic. In addition to the view that the use and transactions of Google and Facebook's personal data can lead to legal problems, they are often resold by data brokers in the name of agreeing to provide third-party data. Homeplus, one of South Korea's major marts, earned about $ 9 million by selling personal data collected in the name of the sweepstakes to the insurer for about $ 4 per person. And Apple, a global company, made $ 73 million in sales of personal information for Chinese customers. These cases are very frequent around the world.

Personal data breaches occur most often when third-party intermediaries attempt to unfairly benefit. That is, from selling to others (or businesses / institutions) who need to have personal data collected for the sale of goods or services, and from the vendor's poisoning of the proceeds. To overcome these problems, there are attempts to trade your own data, excluding data brokers. The SINTEF Institute in Europe has published a study called Dipseity that pays money through personal data. It is a direct data trading market that provides the people with the data they produce to those who need it and receives the price directly. Accordingly, Leebin aims to establish a legitimate data trading ecosystem by providing a platform for directly trading the data designated by him.

4) e-commerce market

The online e-commerce market continues to grow each year, reaching about $ 3 trillion in 2017. Typically, an e-commerce broker connects the buyer to the seller and asks for a brokerage fee. Amazon charges a 15% to 45% commission on sales, and eBay charges a 10% sales fee. In both e-commerce as well as these two companies, the commission rate is set as the sales amount, which is excessive considering the selling cost of the product. This fee problem is even worse in offline stores. In South Korea, about 40% of sales are reported as commission. Excessive brokerage fees cause commodity prices to rise unnecessarily, and this burden is incurred by consumers.

And for small businesses, retailers can't use e-commerce sites like Amazon and eBay. Because it is not possible to provide a list of products based on a specific region, it is not easy to post the product on the main page of a large portal site. Therefore, the existing e-commerce market is difficult to be applied to the small-scale production market represented by 3D printers or to the regional-based service market such as a beauty salon.

Lee Bin runs an e-commerce service called Donation Mall and Advertising Mall. Donation malls and advertising malls are e-commerce services that use bins as currency. In the donation mall, donors can exchange commodities, medical and educational items. The donation mall is run directly by the Vienna Operations Foundation and does not receive a sales fee for any commodity exchange. In the case of the advertising mall, the target audience selected by the advertiser or the seller of the product naturally connects the stakeholders directly to purchase the advertisement product. In the case of consumers who purchase goods or services, brokerage fees (advertising costs) are minimized, enabling them to purchase goods at a low price, and producers can select effective buyers based on the contextual data of Leebin users. You can enjoy it. By setting buyers and linking advertisements based on the user's location data, not only is it possible to sell products effectively associated with local advertisements, but it is also possible to sell products or services to consumers at a lower price through advertisement cost compensation.

Hereinafter, according to an embodiment of the present invention, this chapter proposes and describes the overall architecture of the bean and the rebind service for improving the consumption ecosystem.

7 is an architecture of a blockchain-based social network service (levin service) system according to an embodiment of the present invention.

Vin is implemented as Altcoin on Ethereum's smart contract platform. Therefore, the Bean Coin and the Bean Wallet are implemented as smart contracts, which are called by the Liveen Social Network Service or the Liveen Platform to process the transaction details of the bean. There is also a Liveen Private Blockchain for context data management of the LIVEEN service. It is a high-performance blockchain that can handle big data and is mainly used to secure user-produced content or evaluate the value of user-produced data through the Levin social network. The blockchain follows the consensus method of data value agreement, which evaluates the value of user-generated data and distributes the beans through it. This will be described later. The Liveen Query module is provided as a smart contract of the Levin Private Blockchain, which is used for the application of statistical processing and machine learning, such as analyzing and determining the user's context data and extracting the desired user information from the platform. Used. Finally, the LIVEEN platform consists of the Liveen Common Platform, the Liveen Charity Platform, the Liveen Advertising Platform, and the Liveen Commerce Platform. Smart contract platforms like Ethereum can be replaced with their own public blockchain platform provided by the Bean Operations Foundation in the future as the ongoing operating costs are incurred.

A bean is a coin issued by Lee Bin and available for donation, advertising, and commerce. The 1 / 1,000 bean is called Fino. That is, 1,000 pino is 1 bin.

1 Veen = 1,000 Fino

Beans are issued based on the value of data produced by Leebin. This requires a method other than electricity mining, such as proof of work or proof of stake, as proposed by Bitcoin and Ethereum. The electricity-based mining method, which is represented by proof of work, uses a lot of power, causing environmental problems. The Chinese government made such a case and took steps to ban mining in China. This problem is a side effect of providing competitive mining incentives by recording monetary transactions on distributed ledgers and by applying game rules to gain credibility. This is pointed out as one disadvantage of the cryptocurrency ecosystem, and is being attacked by cryptocurrency skeptics. Therefore, blockchain researchers are making great efforts to solve this problem. As part of this effort, Bean and Leebin provide a way of agreeing the rules of distribution, rather than the rules of competition. That way, given that blockchain is a reliable data store, it is a consensus that measures value by the quantity and quality of data stored in the blockchain and distributes rewards through value. Livin can do this because he stores user-generated content in the ledger, not his transaction records.

In this specification, a new method of consensus of value (CoV) is used to determine and negotiate the value of a transaction. Lee Bin offers a consensus model of value consensus, which can be transformed and used in various blockchains that measure value based on the quantity and quality of data recorded in the ledger.

The following describes one rule for measuring data value in a ribin.

Smart contracts provided by Ethereum issue the total amount of beans and then distribute the beans according to specific rules. It is expected that it will take some time for the Levin social network service to be published and enough users will be gathered. For example, when the total issuance amount is 15 billion, the token issuance model that follows the normal distribution curve is adopted to prevent the drastic drop in service by reducing the issuance amount until the mining completion point. The total amount of beans is 15 billion, and the amount of beans issued varies by year. In addition, for the continuous supply of beans, the Foundation purchases a certain amount of beans on the market every month to maintain the price of the beans. Percentage of purchases is determined monthly by the board of directors.

8 is a graph showing the daily issue amount of bins issued by year.

The amount of beans issued may be changed by the Bean Operations Foundation, depending on the operating status of the LIVEEN services.

D + 1 year: 1,180,000 Veen

D + 2 year: 1,420,000 Veen

D + 3 year: 1,770,000 Veen

D + 4 year: 2,360,000 Veen

D + 5 year: 3,540,000 Veen

D + 6 year: 3,540,000 Veen

D + 7 year: 2,360,000 Veen

D + 8 year: 1,770,000 Veen

D + 9 year: 1,420,000 Veen

D + 10 year: 1,180,000 Veen

9 is a cumulative issuance amount of bins for each year after the release (distribution) of the blockchain-based social network service (Rvern social network service) according to an embodiment of the present invention.

It can take a total of ten years, for example, to release all beans issued annually to the market. After all beans have been published, the beans are distributed because of advertisements, data transactions, and donations, and users produce personal context data for effective advertising or donations.

As mentioned earlier, the Levin social network service users will distribute coins issued per hour by combining reputation and data produced within a certain time (eg, one hour). In other words, all contextual data produced during a specific time period is calculated for each user, and the amount of issue per hour (unit time mined) is reflected as the score ratio. And 10% of the mined bins can be allocated to the operating costs of the rebinds.

Table 1: Mining Rate and Limits by Context

Contextual division	code	Data score percentage	limit
location	LD	30%	12
behavior		AD	20%	12th
Picture
PIC	20%	Chapter five
Posts		TL	20%	500 characters
Hashtag	TAG	5%	20
recommendation	LIK	5%	4 (2 Likes, 2 Hates)

Table 1 shows the types of user context data, the weight of data points, and the maximum limit. The information in this table may change after testing. The maximum limit is contextual data that can be produced by one user over an hour of unit time to prevent indiscriminate data production. Referrals allow two likes and dislikes, respectively, to prevent multiple dislikes from being recorded to increase your reputation score. Data that you set as private does not affect data scoring.

And to prevent the production of meaningless data, we apply the user's reputation to the data output. Reputation (REP) is a 10-point scale, and your reputation is determined by the volume of recommendations (likes / dislikes) of other users in the data produced. Therefore, the formula for calculating the data score (DataScore) is as follows.

[Equation 1]

For example, if you have 12 location records, 6 action records, 3 photos, 200 words, 10 hashtags, and 3 recommendations, you get 432 points if your reputation is 8 points. The data scores of all those people calculated are distributed according to the ratio of mined bins. The following formula is used to determine the reward bin of a specific user according to the mining quantity (QoM) of the unit time. As mentioned earlier, 10% (QoM / 10) of the mined amount is estimated by the operating cost of Leebin. Any remaining bins used for operating expenses will be incinerated by the Foundation. The formula for calculating DataScore and Rewards is subject to change by the Bean Operations Foundation, depending on the operating status of the Levin service.

[Equation 2]

Examples of calculating compensation are as follows. For example, if a total of five people scored 1000, 600, 500, 500, and 400 data points, the 1000 points earner would get a relative score of 0.33 points, and the amount of bins mined in unit time would be 10,000. In this case, 2,970 beans will be obtained out of 9,000 beans except 1,000 service operation costs. Beans acquired by users are distributed to content providers at specific intervals according to the policies of the Bean Operations Foundation.

FIG. 10 is a diagram illustrating a process of a blockchain-based social network service (leavin social network service) according to an embodiment of the present invention, and FIG. 11 is a relative frequency distribution graph of a flat plate.

Livin is divided into social network services and a platform for donation, advertising, and e-commerce, which are reward-based self-life records, or social network systems that share contextual data. You can receive the service. User-produced contextual data can be searched and searched by you or other users, and can be recommended as "like" or "dislike" if it is not your life record. These recommendations from others apply to the reputation of the contextual data producer. In addition, content uploaders that have been evaluated as inappropriate can be fined through penalties to systematize corporate social obligations. The Service also includes an empty wallet for sending or receiving money from others. In addition, the service allows users to receive donations or watch advertisements. The advertisements are exposed in the order in which the most advertising expenses can be obtained, and when the user watches one advertisement, the registered advertising expenses are deposited into the user's wallet. After watching the advertisement, the next higher advertising fee is replaced by the advertisement.

Levin users can query the data recorded at a specific location. Users can rate "likes" and "dislikes" specific content, with a limit of two ratings per hour. And one content can only have one recommendation per user. Recommendations are anonymous, and you can't view content that you set private. The user can search the contents recorded by the user on his main screen. There is also an 'Ineligible' item in the assessment, to remove social data such as advertisements or pornography. As the influence of the Internet platform expands, it is pointed out that corporate social responsibility is required. Regulatory moves to social media and portals are emerging in the US, Germany, the UK and France. In particular, Germany has enacted penalties of up to 50 million euros for social media operators who neglect `` clearly criminal '' posts. However, Livin can systemize corporate social obligations, rather than mandatory monitoring by law. The user may make one 'unsuitable' recommendation at an hour. If social data receives a 'non-conformity' rating above a certain criterion, the user who posted the data will be fined. The criteria and amount of fines may be determined and announced at the start of the service.

As described above, the context data can be produced to obtain a bean. In this case, the user's reputation is applied. Reputation is calculated by combining the contextual data produced by many users with likes and dislikes. First-time subscribers start with 5 points, with more 'likes' higher and lower 'likes' lower. Reputation is calculated relatively, which is called the "Like Score" after subtracting the "Like" count from the "Like" count of all the content of a particular user.

[Equation 3]

LikeScore = Number of Likes-Number of Hates

List the likes in the highest order and distribute the reputation scores according to a normal distribution with an average of 5 and a standard deviation of 2. Reputation scores were applied on a 10-point scale, and a normal distribution was adopted to induce users to know their position in the overall system. The population is all users, the average reputation is 5 points, and the standard deviation 2 is distributed. The following equation shows this as a normal distribution.

[Equation 4]

ReputationDistribution = N (5,2 ² )

Referring to Fig. 11, a graph of the relative frequency distribution of the plate is shown, and Table 2 shows the relative frequency distribution table of the plate.

Table 2: Relative Frequency Distribution Table

P (X: Reputation)	Value	Frequency distribution	Cumulative
9 <X≤10	0.017	1.7%	1.7%
8 <X≤9	0.044	4.4%	6.1%
7 <X≤8	0.092	9.2%	15.2%
6 <X≤7	0.161	16.1%	31.4%
5 <X≤6	0.192	19.2%	50.5%
4 <X≤5	0.192	19.2%	69.7%
3 <X≤4	0.161	16.1%	85.8%
2 <X≤3	0.092	9.2%	94.9%
1 <X≤2	0.044	4.4%	99.4%
0 <X≤1	0.017	1.7%	100%

For example, if you like the top 1.7%, you get 9.0 and if you like the top 15.2% you get 8.0.

Reputation can be applied by dividing into 100 percentiles, taking into account the first decimal place. This reputation may change depending on the testing or operation of the LIVEEN service.

The LIVEEN platform according to the present embodiment is a platform for donation, advertisement, and electronic commerce based on context data accumulated through the LIVEEN social network service. Hereinafter, the platform will be described in detail.

The LIVEEN platform selects subjects through queries based on contextual data. That is, the target person can be extracted from the user's registered location data, social data, and personal history data, and is composed of various conditional statements. Table 3 outlines an example of a ribin query.

Table 3: Examples of queries on the Levin platform

division	Explanation	construction	example	Example
Selection	gender	WHO	WHO IS <Women>	female
	characteristic	HAS	HAS CHILD	A person with a child
	education	EDUCATED IN	EDUCATED IN <Seoul>	Educated in Seoul
	location	LOCATED IN	LACATED IN (<Seoul>)	People in Seoul, Busan
	Interest	INTERESTED IN	INTERESTED IN <ONE PIECE>	People interested in one piece
	language	LANGUAGE IN	LANGUAGE IS <English>	A native speaker of Korean
	cellphone	PHONE IS	PHONE IS <IPHONE 6S>	Man using iphone 6s
	age	AGE BETWEEN	AGE BETWEEN 18,26	18 to 26 years old

This query will be refined with the help of marketing experts, and will be applied from simple queries to judgments using artificial intelligence. When the LIBIN query is activated, many AI developers will develop an ecosystem platform that can make a decision logic using Leebin's context data and sell it as a research project of the LIBIN business.

Like the rain described above, donations may be exchanged through the Ribin platform. Donors can select specific donors through the Ribin query. For example, "List 100 people who lived in Sierra Leone for the longest time in school in 2010-2015." You can query like this. The donor can directly check the user's context data extracted from the query or donate directly through a simple query. Contributions will be made via wire transfer through the Rivin Wallet and may or may not be disclosed to the beneficiary if desired. Livin wants to contribute to a smooth donation culture by eliminating or minimizing the costs of donation brokerage through this direct donation method. The beneficiary can exchange the donated amount through the exchange. In countries without exchanges, the donor can purchase the designated item at a low price in the non-profit donation mall.

The LIVEEN advertising platform may advertise to a desired target by using the LIVEEN query. In this case, the advertiser may directly calculate the number of advertisement targets and the advertisement cost. For example, an advertisement such as "Advertise 100 people with the most 'Pizza' hashtag among 20s and 30s living in Seoul, Korea, can be advertised as 1 bean."

At this time, the advertiser needs at least 110 bins because 10% of the total advertising costs are settled as donations and advertising platform maintenance costs. If the target person does not watch the advertisement, the non-watched advertisement fee is returned to the advertiser. Such direct advertising is not only effective for the advertisers who provide the advertisements, but also the viewers who watch the advertisements are rewarded. Ad revenues in the past have been monopolized by ad brokers, while advertising on the Livin platform returns 90% of advertising costs to ad viewers, minimizing the cost of intermediation, as well as direct-to-peer connections between advertisers and viewers. Advertisement can be said to have been realized.

The LIVEEN advertising platform will provide advertisers with a variety of data to analyze the effectiveness of advertising. It provides the advertisement and product analysis service that shows this in conjunction with the product purchase history of the advertising and advertising mall of Leebin. This is to solve the problem of inadequate analysis of advertisement effect, which is the biggest problem in the mobile advertisement market. In addition, it is possible to analyze the effects of marketing target selection. For example, it can be used as a reference for selecting marketing targets by comparing the effects of advertising with 20s and advertising with 30s. Livin will continue to provide effective advertising results to advertisers.

Leebin will evolve into a data trading brokerage platform in the future. Personal information set by the user or contextual data produced by social services can be traded directly for a reasonable amount.

Levin social service users can register their designated items (e.g. addresses, e-mail addresses, etc.) and set their own value for the personal information they have registered. This feature may present a problem of privacy at present, and therefore only the possibility is considered here. However, the problem of illegal or legal third party transaction of personal information continues to be a problem, and when the transaction of data produced by the user is activated, personal data transaction service is conducted in consultation with the foundation and the operation organization.

Livin offers an e-commerce shopping mall where you can use your beans to buy goods or services. The shopping mall is divided into a donation mall and an advertising mall. The donation mall can purchase relief goods through donations, and the advertising mall can buy advertised products at low cost. In the case of a donation mall, the beneficiary can purchase relief supplies equal to the amount of the donation, which is limited to food, medical, medicine and educational supplies suitable for relief. The donation mall has a non-profit, inexpensive operation policy that minimizes the cost of mediating donations. In the case of the advertising mall, the advertiser can freely register the advertised product and purchase it immediately after the advertisement. In the case of sellers who sell products, they can immediately link the advertising fee they consumed with sales, thereby measuring the effectiveness of advertising.

Livin's e-commerce platform aims to decentralize e-commerce in the personal production market represented by 3D printers and retail services. In other words, if a person produces a product directly to the rebind service and the consumer pays the cost, the customer can directly deliver or supply the service. In traditional commerce platforms, regional-based retail products are not easy to sell their products or services directly to various people.

However, Livin's Livin Query can select the targets for sale and sell them in conjunction with advertisements, enabling effective advertising and sales.

LIVEEN and VIEN aim to create an ecosystem that minimizes commissions from brokerage and profits participants through decentralization of donations, advertising, data transactions and e-commerce. Therefore, the user's content collected in the Levin social network service is paid according to the amount of data and the reputation of the provider to reward the data provision. The produced data may be selected for donation targets, advertisement targets, and sales targets based on the Leebin query. Donors, advertisers, and sellers make direct donations, direct advertisements, and direct sales through Vienna. In the case of an advertisement, a social service user watches an advertisement, and at this time, an advertisement fee allocated to the user can be obtained. This advertisement is naturally linked with e-commerce, and viewers who purchase the advertisement can purchase the goods or services. This creates an ecosystem that connects producers and buyers to Levin and Beans, and enables users to effectively advertise, sell and watch low-cost advertisements and purchases without excluding donation, advertising, and commercial brokering costs.

Livin according to the present embodiment is a blockchain-based social network service that provides rewards appropriate for valuable data that a user voluntarily creates. Users create and share a variety of quality content based on their interests, and are rewarded with coins according to the value of the content. The coins received in this way can be exchanged for real currency through the exchange, and can be used in connection with an advertising platform and an e-commerce platform for real trading. Rewards are determined in proportion to the amount of data produced by the user and the results evaluated by other users, and the coins issued in specific units are distributed according to the data contribution provided by the user. The contextual data accumulated by the user becomes information that can provide customized advertisements and customized donations, and advertisers and donors can use the information to provide advertisements or donations to targets that meet specific conditions. In other words, an ecosystem is created where people who produce contextual data can issue coins and spend coins on advertising, donations, and physical transactions. As you say, "You are your data," your data is happening at this moment, and you are the producer. With Levin, users will contribute to the realization of true universal human value by ensuring the right rewards for data, decentralization of advertising, data transactions, donations and e-commerce, and ensuring trust.

Referring back to FIG. 10, the SNS platform 10 (that is, REBIN platform) applied to the blockchain-based social network service system according to the present embodiment is a data platform based on location information of users. Meanwhile, Internet service providers provide rewards for unfairly and unilaterally collected user data through a cryptocurrency called bin.

Users who use the LIVEEN platform provide the platform with their current location information as well as their current behavior and various media materials on the platform (Step ①, Upload Information (GPS), My Actions / Hashtags, Information, etc.). The bin can be mined by this information uploading action.

The LIVEEN platform collects data uploaded by users and performs quantitative evaluation of the collected data. This approach can be referred to as the Consensus of Value (hereinafter referred to as CoV). By CoV, the data value of users can be converted into quantified scores and returned to users in the form of empty tokens based on the converted scores.

In addition, users can perform content evaluation (step ②) such as rating like / dislike, target advertisement viewing based on user data (step ③), and a bean is provided for each action.

The data of users accumulated on the LIVEEN platform can be consumed in various ways. Advertisers or commerce companies want targeted advertising rather than costless omnidirectional advertising. At this time, various media data as well as location data accumulated on the REBIN platform can be usefully used for these companies. Therefore, advertisers or commerce companies combine specific conditional search and send queries to the rebind platform, which then masks users who come from querying data based on the received queries and returns them to advertisers / commerce vendors. (Step ④). In order for advertisers / commerce companies to use this query system, it is necessary to pay the empty tokens to the REBIN platform.

In addition, the REBIN platform can serve as an intermediary platform that enables advertisers / commerce companies to target and advertise on a data basis (step ⑤). In this case, the advertiser / commerce company will need to pay an empty token to use this brokerage platform.

12 is a flowchart of a method for providing a blockchain-based social network service performed in a blockchain-based social network service system according to an embodiment of the present invention, and FIG. 13 is a blockchain-based social network service according to an embodiment of the present invention. It is a figure which shows the structure of a system.

The blockchain-based social network service providing method, in particular, the data value evaluation method performed in the blockchain-based social network service system (particularly, the SNS platform 10) according to an embodiment of the present invention is the aforementioned CoV, Algorithms that value data stored by users (eg, current location data, current behavior, photos, posts, hashtags, recommendations, etc.). The total weight of the six data is different, and the rewards can be different according to the reputation of the data producer.

The Levin platform is provided to a terminal used by the user in the form of a mobile application and can be used by the user. Referring to FIG. 13, the REBIN platform includes a user layer in the form of a public blockchain in which users participate in the form of a node, and a private blockchain layer in which the user's data is determined to block the block. It may be a two-tier hybrid blockchain in which layers are combined.

In FIG. 13, a sector means a variable area range. Users N4 and N5 operating in areas where S1 and S2 overlap, may be compute nodes that calculate the value of the data of users N1 through N12 generated in S1 and S2 (CAL _S1S2 ).

Similarly, users N10, N11, and N12 operating in areas where S2 and S3 _overlap may be compute nodes that calculate the value of data of users N4 to N15 operating in areas S2 and S3 (CAL _S2S3 ).

The result value calculated by the calculation node may inform the verification nodes V1 to Vn constituting the private blockchain layer. Because sectors are randomly zoned according to the user's geographic distribution, users who are located at the intersection of sectors and can be compute nodes can also change randomly every hour.

From S1 to S3, all data generated by blockchain-based social network service applications are also propagated to the private blockchain layer in the form of transactions. Therefore, not only the public blockchain that is the user layer but also the nodes V1 to Vn forming the private blockchain may independently perform inter-sector data value calculation based on the propagated data.

The nodes of the private blockchain layer are compared with the self-calculated verification result that CAL _S1S2 and CAL _{S2S3, which} are the calculation result values received from the user layer, are correct values. If the calculation result value propagated in the user layer is an incorrect calculation value, the public blockchain node that provides the calculation result value may not receive the calculation compensation.

In addition, nodes that calculate wrong values in the private blockchain layer can also be excluded from the role of validator and permanently retired.

If the result is compared and found to be equal, the verification node can block the transactions corresponding to the result and store it in the private blockchain. In addition, additional compensation may be provided to the calculation nodes belonging to the sector intersection that assisted the calculation.

CoV logic is as follows.

The SNS platform 10 zones the sector at this point (step S100). Sector zoning can be done randomly.

The user node belonging to the intersection between the sectors is selected as the calculation node (step S105).

The calculation node calculates a data score (data score, DS _Nn ) for data provided by all general user nodes Nn belonging to both sectors as shown in Equation 5 (step S110). Equation 5 is similar to Equation 1.

[Equation 5]

LD is position input number, AD is behavior input number, PIC is photo input number, TL is article input number, TAG is hashtag input number, LIK is recommended number,

,

,

,

,

,

Is the data score ratio (weighted) for each contextual data (see Table 1).

Here, the user may raise 12 or more position inputs and 12 or more action inputs. However, since the limit values according to Table 1 are set to 12 and 12, respectively, the user may not receive additional compensation for this or more actions. The same goes for photos, posts, hashtags, and recommendations. Here, the limit value for each user behavior is exemplary and may be changed as necessary.

The calculation node calculates the reputation REP _Nn for general user nodes as shown in Equation 6 (step S115).

[Equation 6]

sort is a sort function, Number of LIK is the number of likes, Number of DIS is the number of dislikes. Here, REPDist is Reputation Distribution, and may be distributed as shown in Equation 4, FIG. 11 and Table 2.

The user's reputation (REP _Nn ) can be arranged in order according to the normal distribution curve N (5, 2 ² ), and the reputation can be calculated according to the ranking. for example. The top 1.7% of users are weighted by 100% and the bottom 1.7% of users by 1.7%. When the weight of reputation management is given high, the SNS service can be managed well.

When the data score and reputation calculation for all the normal nodes in the sector are completed, the verification nodes constituting the private blockchain receive the calculation result value (sector result value) and compare and verify that it is the same as the verification result value calculated by itself ( Step S120).

If the calculation result value is the same as the verification result value, the calculation is considered to be successful, and the verification node confirms a block for the transaction corresponding to the result value and rewards the calculation node that calculated the result value ( Step S125). The reward may be to provide a certain amount of bins.

If the calculation result value is not the same as the verification result value, it is regarded that the calculation is not performed correctly, and a penalty is given to the verification node and / or the calculation node which incorrectly calculated the result value (step S130).

For example, the calculation error at the verification node can be confirmed by comparing with the verification result value calculated at another verification node belonging to the private blockchain. It is assumed that the verification result value calculated in the plurality of verification nodes is correct, and the calculation value deviating from this value may be regarded as an outlier and a calculation error may occur.

After this first verification, it is possible to check whether there is an error in the calculation node. That is, it may be determined that a calculation error occurs in a calculation node that represents a calculation result value that is not the same as a verification result value that is recognized as having no calculation error.

When the reward payment and penalty grant according to the calculation are completed, the reward is paid to the user node Nn which inputs the data (step S135). The reward to be paid may be calculated according to Equation 2.

The above-described steps S100 to S135 may be periodically performed at predetermined times (for example, one hour).

The above-described method for providing a blockchain-based social network service, particularly a method for evaluating data value, may also be implemented in the form of a recording medium including instructions executable by a computer such as an application or a program module executed by a computer. Computer readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. In addition, the computer readable medium may include a computer storage medium. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data.

The above-described method for providing a blockchain-based social network service may be executed by an application basically installed in a terminal (which may include a program included in a platform or an operating system basically mounted in the terminal), and the user may use an application store server. The application may be executed by an application (ie, a program) installed directly on the master terminal through an application providing server such as an application or a web server related to the corresponding service. In this sense, the above-described method for providing a blockchain-based social network service may be implemented as an application (that is, a program) that is basically installed in a terminal or directly installed by a user, and may be recorded in a computer-readable recording medium such as a terminal. .

Although the above has been described with reference to embodiments of the present invention, those skilled in the art may variously modify the present invention without departing from the spirit and scope of the present invention as set forth in the claims below. And can be changed.

Claims (14)

1. A social network service providing method performed in a blockchain based social network service system,

   Receiving, by the social network services platform, user context data including location information from the user node;

   Evaluating the value for the user context data; And

   Registering the user context data as a block confirmed in the blockchain, and paying a coin corresponding to the value of the user context data to the user node as a reward.
2. The method of claim 1,

   And the user context data further includes at least one of behavior information, a photo, a text, a hashtag, and a recommendation number.
3. The method of claim 1,

   And calculating a data score for the user context data in the value evaluating step and applying a reputation for the user node as a weight.
4. The method of claim 3,

   And the reputation is determined by a good score corresponding to a recommendation amount of another user for all user context data generated in the user node.
5. The method of claim 4, wherein

   The reputation is a blockchain-based social network service providing method, characterized in that the likelihood scores are arranged in order and a reputation score is relatively distributed according to a normal distribution having a predetermined mean and standard deviation.
6. The method of claim 3,

   The method of claim 1, wherein the reward reflects a ratio of the data score to the amount of mining time per unit time.
7. The method of claim 1,

   When the query based on the user context data is input from the company terminal, the social network service platform inquires and masks a user node having a relatively high relevance to the query, and transmits the query to the sender terminal. Blockchain-based social network service providing method.
8. The method of claim 7, wherein

   The blockchain-based social network service providing method characterized in that the payment using the coin is required as a prerequisite for inputting the query to the company terminal.
9. The method of claim 1,

   The valuation step,

   Zoning the plurality of sectors based on location;

   Selecting a user node belonging to an intersection between any two sectors as a computing node;

   Calculating data scores of all user nodes belonging to the two sectors at the computing node;

   Calculating a reputation of all user nodes belonging to the two sectors at the computing node;

   Transmitting a calculation result value in which the reputation is reflected in the data score, to a verification node; And

   Comparing and verifying the self-calculated verification result value and the calculation result value for all the user nodes in the verification node,

   If the verification result value and the calculation result value are the same, compensation for the calculation is paid to the calculation node, and if the verification result value and the calculation result value are not the same, at least one of the verification node and the calculation node in which the calculation is incorrect A method for providing a blockchain-based social network service, wherein a penalty is given to one.
10. The method of claim 9,

    The calculation by the calculation node is performed in a public blockchain layer, and the calculation and verification by the verification node is performed in a private blockchain layer.
11. The method of claim 10,

    The verification node is a blockchain-based social network service providing method, characterized in that for verifying the calculation error by comparing the verification result value with another verification node in the private blockchain layer.
12. The method of claim 9,

    The data score calculating step is a block chain-based social network service providing method characterized in that for calculating the data score (DS _Nn ) using the following equation.

    

    

    -LD is the number of location inputs, AD is the number of behavioral inputs, PIC is the number of photo inputs, TL is the number of text inputs, TAG is the number of hashtag inputs, LIK is the number of recommendations,

    

    ,

    

    ,

    

    ,

    

    ,

    

    ,

    

    Is the data score ratio (weighted) for each contextual data-
13. As a blockchain-based social network service system,

    A user node for generating user context data including location information; And

    Receive the user context data from the user node, evaluate the value with respect to the user context data, register the user context data as a fixed block in the blockchain, and pay the coin in accordance with the value Blockchain-based social network service system comprising an SNS platform.
14. The method of claim 13,

    Further comprising a company terminal for transmitting a query based on the user context data to the SNS platform,

    The SNS platform is a blockchain-based social network service system, characterized in that for querying and masking a user node having a relatively high correlation to the query, and transmits the query to the company terminal that sent the query.

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