The era of comprehensive digitalization is approaching, users are no longer worried about too little information, but too much information. The Internet has become a major core issue in terms of how to quickly and effectively find out the truly valuable information from the vast amount of information.
The two founders of Tencent raised this question: what can technology/products do in the face of information overload?
This problem can be partially solved with blockchain. “The problem of “making truly valuable content stand out” can actually be translated into an economic problem – pricing content.
Price is the best predictor of the quality of content, for example, an article priced at $1,000 will not be of worse quality than an article priced at $1.
So how do you price content?
If you use blockchain technology to create a content pricing market, you will be able to excavate valuable content, or it can be understood as a prediction market of content value, which is actually supported by economic principles, that is, “efficient market theory”.”
We assume that many “investors” in the market are rational and seek maximum profit, and each person’s analysis of content is relatively independent, then if the use of group wisdom to price content, the price will be a good predictor of the value of content.
How to build a prediction market for content?
The way we build this prediction market is very simple: users can vote to price content.
Simply put, if a reader believes that the current price of a piece of content is much lower than the actual value of the content, they can vote “yes” to raise the price of the content, and the increased price is the cost of the vote, and if the final price of the content is higher than the user’s expected price, the user will The user is rewarded financially if the final price of the content is higher than the user’s expected price.
new price = current price + cost of voting
Of course we have to set up incentives so that people can make predictions for their favorable outcome and get rewarded for the results. In order to win as much as possible, people will use various methods, such as information gathering, to make the predictions as accurate as possible.” The
mechanism could look like this: for a piece of content, the first person who votes yes, Mr. One, spends all of his vote on the article, and the second person who votes yes, Mr. Two, spends half of his vote on the author and half on Mr. One, who voted first. If Mr. Ûi also votes, the money spent by Mr. Ûi will be divided into three parts, one for the author of the article, one for the first voter, one for the second voter, and so on.
That means that the person who voted in front of you is participating in a prediction campaign that the article should be worth more, and the student who got it right will naturally get a portion of that prediction campaign, in fact, the top 35% of those who voted yes will get the excess.”
“That means that the person who voted in front of you is participating in a prediction campaign that the article should be worth more, and the student who got it right will naturally get a portion of that prediction campaign.
In this way, after people’s rational judgment of the value of the content, more valuable content will be unearthed by the people involved in this market, and through the mechanism of the prediction market, the problem of the discovery of quality content is solved.
This is actually the basic principle of UGC Network: the world’s first content value prediction platform.
1) How does quality content stand out?
UGC Network introduces a value prediction marketplace into the content platform, allowing the market to shape the pricing of content, rather than a centralized agency. In this way, after people’s rational judgment on the value of content, more valuable content will be unearthed by people involved in this market, and the problem of discovering quality content is solved through the mechanism of the prediction market.
2) If random likes would cost money, would bad content still run rampant like this?
The prediction of content is subject to thoughtful consideration commensurate with the price paid.
We may like something in Weibo, Zhihu, or our circle of friends, but sometimes the likes do not necessarily indicate our approval of the content. Only when the number of likes is rationally selected can we ensure that the content with high likes is of higher content value.
The first person who likes the article has all the money he spends to the author of the article, and since the person who doesn’t like the article later doesn’t get the benefit afterwards, that is, his prediction about the article is incorrect, and he pays the price accordingly.
In this way, we can ensure that the members of the content platform are making predictions about the value of the content of the article after a judgment that matches the price they will pay.
Of course, to ensure the principle of fairness, community participants can also earn points for completing community tasks, such as retweeting and spreading articles, to gain access to votes if they don’t want to spend the monetary cost.
Here, people put in the time and effort to get the right to vote and still get rewarded if they find good content.
3) How do you ensure that the more valuable the content, the higher the author’s earnings?
The platform that content creators want to gather more is definitely the one with a larger user base. UGC Network attracts a large group of users interested in content by introducing a prediction market.
Under the mechanism of UGC Network, authors produce high quality content that earns higher and higher revenues due to the predictions of more and more people, and through such a mechanism, the authors’ motivation to produce high quality content is ensured.
4) When bounty is not just a bounty, you may also get more “rights”
Bounty is upgraded?
Reward = approval of the content of the article + the platform’s expected benefits (the value of one’s own rational thinking)
This upgrade from a single function to a dual attribute of the act of reward is brought about by the mechanism of the predictive market of content value.
For example, if you agree that an article is well-written, your act of approval has two meanings: appreciation of his content + prediction that his content is a good piece of content.
“If the content you approve of is good content, your (prediction that the content is good content) will be rewarded.
In other words, the revenue you get is also the value you bring to the act of judging the content to be good after thinking rationally.”
In other words, the revenue you get is also the value you bring to the act of judging the content to be good after thinking rationally.
The four aspects of evolution driven by the UGC Network are a change in the way content producers benefit and article audiences benefit:
First, the problem of discovering quality content is solved through the act of predicting the merits of content.
Second, the audience of content, becomes the digger of quality content.
Third, the higher the value of the content, the greater the revenue the author receives.
Fourth, the act of rewarding is upgraded from a single attribute, to a double attribute.
Let Zhihu distressed cheat praise text, let Faceook worry about false content, each content platform on the article of the centralized trial right, many content platform quality content is no way through the platform’s mechanism to get reasonable income, these problems, are likely to use UGC Network to solve.
UGC Network: the world’s first content value prediction platform
1) UGC Network and U Community
UGC Network is the world’s first content value prediction platform, a fair and value-driven content incentive network. The UGC Network’s mission is to solve the core problem of “how to quickly and efficiently identify the most important content from the mass of information” on the Internet.
U Community is built on the UGC Network, a blockchain technology and digital asset content community consisting of content producers, content discoverers, community witnesses, and ordinary users, which helps blockchain enthusiasts make investment decisions by introducing a prediction market based on the value of content and enabling the U Community to continuously produce quality content that is loyal to the interests of users.
The U community will be deployed on the UGC Network public chain with high availability, high performance and low latency, and the U community is to the UGC Network what Stemmit is to Steem.
2) The original founding team of Silicon Valley Confidential
The UGC Network and U community is built by the original founding team of Silicon Valley Spies Silicon Valley.
was founded in September 2015 in San Mateo, Silicon Valley, U.S.A. Currently, there are more than 4 million subscribers on the network, which is a community and ecology linking high-quality content from China and the United States. With a comprehensive focus on blockchain technology, it covers three major segments: blockchain media matrix, San Francisco Meetup and global blockchain conference, and blockchain courses and communities in China and the United States.
Blockchain Media Matrix 》
Blockchain Media Matrix includes Silicon Valley Spy, Silicon Valley Blockchain, Silicon Valley Live and dozens of accounts across the network.
Blockchain Media Matrix includes Silicon Valley Spy, Silicon Valley Blockchain, Silicon Valley Live and dozens of account sequences across the network.
Since 2016, Silicon Valley Scout has taken advantage of the local Silicon Valley team and has exclusively interviewed Silicon Valley blockchain companies and individuals including: Vitalik, founder of Etherum; Paul Veradittakit, partner of Pantera Capital, the first bitcoin fund in the United States; Blockstram; Tezos; Blockstram; and Tezos. Blockstram; Tezos; Kyber Network….
and published several 100,000+ explosive articles, which is very rare in the field of blockchain media in China and the United States, specifically:
“Blockchain, how will redefine the world? 阅读量：198310
《Dropout programmer to change the world, the 90-year-old boy who looks like Jack Ma really wants to beat Zuckerberg…》 阅读量：107993
《Unexpectedly, blockchain has been reduced to a tool for political struggle》 阅读量：121169
San Francisco Meetup and the Global Blockchain Conference 》”
San Francisco Meetup (two 100-person offline events per month in Silicon Valley):
Bitcoin Jeff Garziky, one of the early developers of Bitcoin;
Stanford Blockchain Open House;
Blockchain technical difficulties and smart contract development;
Blockchain quantitative trading and arbitrage;
Blockchain Connect San Francisco China-US Blockchain Conference:
Silicon Valley Confidential and Silicon Valley Blockchain host three global blockchain conferences of different scales in Silicon Valley each year, the most recent one was held in San Francisco on January 26th US time on the theme of Blockchain Technology Evolution in US and China” was held in San Francisco on January 26th, US time, and became a Silicon Valley phenomenon. 1500 tickets were quickly sold out, and the guests included: Tim
, a legendary Silicon Valley investor who invested in Skype, Tesla, SpaceX, etc. Draper; Brad Garlinghouse, CEO of
Ripple; Charlie Lee, founder of
Litecoin; Riccardo Spagni, head of
” Joseph Poon, founder of the Lightning Network and originator of Plasma; Kavita Gupta, founding managing partner of Consensys Capital; Shoucheng Zhang, professor at Stanford University and founder of Danhua Capital; Shuai Chu, founder of
founder Shuai Chu;
NEO founder Da Hongfei;
Kraken CEO Jesse Powell, one of the largest exchanges in the U.S.;
OKEx CEO Li Shubing and other top Chinese and American blockchain experts.
硅谷密探和火币集团达成战略合作，由火币集团COO老师朱嘉伟主講的《《火币集团COOThe audio class “From 0 to 1, Learn Blockchain Comprehensively” is considered to be the first complete and systematic explanation of introductory blockchain knowledge content on the market, and by the end of January, more than 6,000 copies were sold across the network.
smart contract development class:
and Dr. Dong Mo of UIUC cooperated to polish the “Introduction to Full-Stack Development of Ethernet Smart Contracts” practical training camp class, and the learning completion rate reached 81.95%. The number of students enrolled in the second session was 100, and the actual number of applicants exceeded 700, with an acceptance rate of less than 15%. Participants include elites from Stanford, Princeton, Harvard, MIT, Peking University and other academic institutions, as well as engineers from Facebook, Google, Oracle, Tencent and other organizations.
This course also provides a steady stream of high-quality blockchain development talent from Silicon Valley to the UGC Network development team.
Paid user community:
By the end of January 2018, the paid user community reached 10,904; the number of users reached 101,399.” (
3) Current development process of the project
public chain is in the pre-development stage, internal test nodes have been built;
is based on the open source public chain for customization development, the development and deep customization of the public chain is in progress, it has been adapted to the UGC Network upper layer application, and the public chain related DAPP is under development. DAPP is under development.