How to govern the phenomenon of big data killing, and how to solve the problem of big data killing

To control the phenomenon of "big data killing", it is not to "kill" big data, but to be good at leveraging to form a joint force of supervision and governance. Regulatory authorities should establish and improve big data online supervision platforms, and improve the ability to investigate and deal with all kinds of hidden "big data use" illegal acts. It is necessary to include the protection of consumer evaluation rights and the use of tourists' information into the scope of key supervision and governance, keep pace with the times and upgrade regulatory means, and create a legal environment that allows consumers to "walk away" and travel safely.

The National Day is approaching, and a topic related to ** tourism - "Big data killing behavior is expressly prohibited from October 1" on the Weibo hot search list. The topic stems from the Ministry of Culture and Tourism's issuance of the "Interim Provisions on the Management of Tourism Business Services" (hereinafter referred to as the "Regulations") officially implemented on October 1 this year, Article 15 of the "Regulations" makes it clear that tour operators shall not abuse technical means such as big data analysis, based on tourists' consumption records, travel preferences, etc. to set unfair trading conditions, infringing on the legitimate rights and interests of tourists. This regulation is aimed at the "big data killing" behavior that has been criticized in recent years.

The advent of the "big data era" has brought a lot of convenience to people, but also brought some negative impacts, and "big data killing" is one of them. In the "Interim Provisions on the Administration of Tourism Business Services" (draft for comments) issued by the Ministry of Culture and Tourism in October last year, the prohibition of "big data killing" is defined as "** tour operators shall not use big data and other technical means to set up differentiated products and services for the same product or service under the same conditions for tourists with different consumption characteristics".

Based on the two provisions of the "Provisions" (draft for comments) and the "Provisions", "big data killing" can be simply understood as: ** tourism operators abuse big data analysis methods, use their own information advantages, and set higher standards for old customers than new customers, causing old customers to suffer. In March last year, the Beijing Municipal Consumer Association released a survey results showing that nearly ninety percent of the respondents believed that the phenomenon of "big data killing" was widespread, and the respondents said that they had the experience of "big data killing", among which online shopping, ** tourism, hotel accommodation, online car-hailing, takeaway, film and television and other consumption scenarios were the most likely to be "killed by big data".

In fact, this kind of thing cannot be restrained at all, because this kind of thing is actually a normal business behavior of a business, which is reasonable and legal.

First of all, big data is "ripe", the people's will, and the law should do something. To deal with all kinds of "big store bullying" behaviors such as big data "killing ripeness", relevant departments should strengthen relevant legislative work, plug regulatory loopholes, and increase the cost of violating the law.

Second, innovate the way of big data supervision. Science and technology is not a "butcher's knife", should not help abuse, the relevant regulatory departments should be from the technical level, the establishment of a corresponding big data online supervision platform, for the network information platform to carry out all-weather supervision, improve the ability to investigate and deal with all kinds of hidden big data illegal acts.

Third, establish a blacklist system for the untrustworthy. Once it is discovered that the platform has "killed ripe" behavior, it should not only be given an administrative punishment, but also included in the integrity blacklist.

Fourth, platforms should be autonomous and self-disciplined. Platforms should realize that integrity is the foundation of business, and don't look at "money" in a hurry. The use of big data to "kill ripeness" not only betrays the trust of consumers, but also harms their interests, which is a kind of practice of exhausting the fish.

Finally, consumers should have multiple "hearts". There are many big data "killing" routines, and consumers can't guard against it. Consumers may wish to compare the price difference on multiple platforms, adhere to the principle of shopping around, and disguise themselves as the most sensitive users, so as to "confuse" big data.

No matter how the rules of new technologies change and how rapid the development and iteration are, the old rules of honesty and honesty should not be broken. It is believed that with the improvement of various policies, laws and regulations, as well as the self-control and self-discipline of Internet platforms, a new form of Internet economy in which law enforcers, online platforms and consumers are co-governed will be formed, and the chaos caused by big data technology can be fundamentally curbed and consumers can consume clearly.

Strive to make yourself a non-regular customer;||Compare the ** of the same item many times, ask others about the price of this product, break the barrier between consumers, so as not to be killed by big data;Starting from the root cause, it is necessary to be cautious about the authorized user information and refuse to apply for authorization of the software, especially for positioning or communication. Why do some people get along for a few years and still haven't been able to become a couple, while some people become each other's other half after only a month together?

In fact, men and women want to go further, it is easy to say that it is simple and difficult to say, and the simplicity lies in the fact that as long as two people have a common topic with each other, talk endlessly, and have something they like to do together, it is easy to have a good feeling.

If there is no mutual understanding, no tacit understanding, and no common goal, then even if two people have a good impression of each other, they cannot become each other's other half.

Therefore, at this time, the existence of "telepathy" between two people is particularly important, and when there are the following three relationships between you, then the relationship between you will soon change.

Men and women with these three types of "telepathy" can easily have a relationship.

Tacit behavior is synchronized.

Why do many couples develop from boyfriend and girlfriend? In fact, it is because of the tacit understanding between them that they have reached synchronization.

Two people have been together for a long time, they can find each other's temperament, know what they can say and what they can't say, understand what they like to eat and taboos, even if a group of people go out to party, one of them will help each other avoid things that can't be eaten when one of them orders food, two people have been together for a long time, and their interests and hobbies will become extraordinarily consistent, he likes to play billiards, and the other party is slowly never going to be particularly proficient in playing Two people often play together.

Even if it is a gift, it will be more appropriate than other people's gifts, and it will be sent to the top of my heart. Thinking about it this way, the tacit understanding between two people is too important, and when the fit of two people is highly compatible, it is difficult for others to enter between two people. When this tacit behavior between two people reaches synchronization, they will soon become each other's partners.

During this time, a user who was cut leeks**Meituan's killing routine, the same product, members** are much more expensive than non-members**.

In fact, this is not the first time that big data killing has been exposed, as early as before, many netizens broke the news that no matter what mobile phone you use, as long as you authorize your basic information to the software, then the platform will judge your financial strength through your daily consumption, so as to give different consumption**, which is also big data killing.

To put it simply, killing ripeness is the behavior of major Internet apps using their own user databases to differentially locate loyal users. It is the same product, the old user's ** will be higher than the new user, and the higher the consumption frequency on a certain platform, it will also become the target of big data.

So why does big data pick acquaintances to commit crimes?

Internet giants have all kinds of basic information about users, and in order to expand their user channels and continue to attract new users, major Internet platforms have to increase subsidies. Anyone who has ordered takeout has encountered that the discount for new users is staggering, while old users will never enjoy such a service.

The cost of subsidizing new users is earned back from old users. And because the old users are very sticky, they basically won't switch platforms, so the platform is mature, who will you kill if you don't kill them? This is the routine of the Internet platform.

Compare the ** of the same item many times, ask others about the price of this product, break the barrier between consumers, so as not to be killed by big data;

Hello. In fact, this kind of big data killing problem has always existed. Because it's recorded when you browse the web.

So when you make a purchase or browse some data, it will be accessed to the relevant data for intelligent access. And all of this data will be effectively distributed to some merchants. So when you go shopping or something again, there will be a big data killer.

Big data kills ripeness everywhere, how to manage chaos? Didi, Alibaba, JD.com.

Learn about the phenomenon of big data "killing" in the consumer space.

Big data killing is actually a kind of discrimination, which should be expressly prohibited, and if a case is found, it must be strictly punished, because now we all pay attention to equality, and we must have integrity in doing business.

I think this kind of behavior is really excessive, in other words, isn't this kind of behavior bullying honest people? I feel that this kind of behavior should be banned, it is too unfair to the average person.

This is an unreasonable behavior, which will allow those old users to obtain these goods at a higher **, increase the user's purchase cost, and make people distrust the platform.

Big data kills ripe customers means that regular customers spend more money than raw customers, although this phenomenon is inevitable at the moment of social development, but in the context of increasingly transparent information, more and more important goodwill, and increasingly rational consumers, the best countermeasure should be to use big data to give regular customers better personalized services, including more discounts.

I think this kind of behavior is very shameful, this kind of behavior seriously infringes on the legitimate rights and interests of consumers, and I hope that there will be relevant policies to regulate it.

Big data kills ripeness means that the more times the same person places an order on the same software, the more expensive his page displays**, and this phenomenon is mainly the result of some operators taking advantage of customer dependence psychology to collect money in disguise.

Big data killing is to use the user's access data to recommend products to users, and these products will be relatively high in the user. This phenomenon occurs because the permissions of the app cannot be restricted by the user.

It is these officials who will integrate data, such as the mobile phones used by these people, or the number of orders, and then improve the delivery of **, because the staff of these apps do not comply with the rules and regulations.

In fact, this is a reflection of the social phenomenon analyzed after big data analysis, and with the development of science and technology, many social phenomena can be analyzed according to digitalization, so he can easily discover the future development direction through cloud computing.

"Killing ripeness" is not a unique phenomenon of big data, but essentially a human nature.

A large part of the reason is the realization of a monopoly in the market, the formation of a monopoly on user data.

Big data killing is a technology that uses big data analysis technology to mine user behavior and preferences, so as to achieve more accurate targeted marketing. The key to cracking big data is data collection and data analysis.

First of all, in order to crack the big data killing, a large amount of data collection is required. These data can be used in the user's behavior data, social data, search engine data, etc., including the user's browsing history, search history, purchase history, geographic location, etc. This data can be used to help companies better understand their users, so as to better achieve precision marketing.

Secondly, in order to crack the big data killing, a large amount of data analysis is also required. These data analysis can be achieved by building models, such as machine learning models, deep learning models, etc., which can help enterprises better analyze user behavior and preferences, so as to achieve more accurate targeted marketing.

In general, in order to crack the big data killing, a large amount of data collection and data analysis is required to achieve more accurate targeted marketing.

Summary. As mentioned above, everyone generates data, and a large number of data taken together can be called big data.

It is said that big data is familiar because the same goods or services, old customers see **, but it is much more expensive than new customers. Big data familiarity refers to the phenomenon that the same goods or services, the old customers see that the first is much more expensive than the new customers. On December 20, 2018, Big Data Killing was selected as one of the top ten popular terms in social life in 2018.

As mentioned above, everyone generates data, and a large number of data taken together can be called big data.

There may be two reasons why "big data is so spurned": First, the Internet was originally brought with a "dimensionality reduction attack" to the traditional economy, and it also came with a transparent mission. Your current "dragon slaying boy has become an evil dragon" does not match your own net design.