Let's look at the big data in interdisciplinary dialogues

Absrtact: August 14, Tencent Network held a summer meeting in the Courtyard hall, and the theme of this time is big data. Interestingly, this sharing of big data will invite academics and experts from all fields, an interdisciplinary idea to touch

On the August 14, Tencent hosted a summer club in the Courtyard Hall, and the theme of the meeting was "big data". Interestingly, this sharing of big data will invite academics and experts from all fields, an interdisciplinary clash of ideas. At the scene I listened to the whole field of sharing, a lot of interesting views, there are some views of the current domestic attention to large numbers of people do not mention, very speculative. Here, I also share some interesting ideas from the meeting.

The application of massive data is changing our present production mode, which not only becomes an important production factor, but also improves the production efficiency to some extent. At this time, the massive data application brings the information storm not only affects our work, the life, but also may gradually influence our way of thinking. Some people say that the big data itself is a revolution, and this revolution is to push the concept of "quantification" into every aspect of our lives.

1, the opportunity to bring the big data can be said to be the academic industry unanimously agreed, and the University of Journalism and communications Professor Liu De, the big data can also be "big cheat", even there are big risks.

large data must be full data?

Even for internet giants like bat, the data they own is just an island of data. Therefore, many large data are actually broken and closed. Before the island was broken, large numbers could not be called "full". This large and incomplete data makes it impossible for us to really get the laws we want.

large data may lead to "false rules" and "pseudo correlation"

Although the introduction and analysis of large data tell us that the big data focus on the "correlation", rather than "causal relationship", but, if only focus on the relationship, the increase in data will inevitably bring pseudo-related phenomena. When the volume of data reaches hundreds of thousands of, it only leads to the conclusion that everything is connected. At this point, the selected variables are presented as statistically significant, and such data analysis will undoubtedly fail. Therefore, even though large data is now highly praised, the traditional sociological research methods such as sampling and experimentation should not be discarded, but should be used in combination.

Zhou, a translator at the big Data age, also responds to this view: Technically, we really need to find causation. On the one hand, if there is no cause and effect in the back is difficult to find, on the other hand, cause and effect can help us better interpretation and analysis of the relevant.

Big data is inseparable from the understanding of "human nature"

The process of large data mining also needs to be injected into the mind, which is embodied as "human nature". Statistical data can not replace the understanding of human nature, the real people related to the large data mining must pay attention to human nature, this time the algorithm and modeling is targeted and meaningful. How to inject human nature into the data? Observation, experiment, investigation and other traditional research methods are very good choice. Jobs, for example, often hide behind the Apple experience shop and observe the behavior of people in the experience shop, the earliest research method that has some reason to use it today. Bottom line: Things like "experience, experience, intuition, brainwave, introspection", which seem to have nothing to do with big data, may just be the core of big data.

Large Data + small application trend

The small application of large data is the application of large data to various independent fields. The large data operation itself constructs a "new abacus" with more power, and having this new abacus does not mean having everything, but having a scientific tool that can be used in every field. How to do the small application of large data? There are two aspects: first, the combination of large data and small data, this small data is based on sampling data; Secondly, expertise from various fields of independence is important, such as the combination of psychology, law, sociology, marketing, and so on, with data, will be able to explore a more scientific way of large data analysis and mining.

2. On the industrial application of large data, Wang Jian, chairman of the Huada gene, expressed his view that genetic research is a very rare industry study, but it is a real big data application.

How to predict diseases effectively and how to reduce the incidence of infectious diseases depends on genetic research. The number of cells in a person's body is 10 14 times, and the cancer of one cell can lead to the end of life. After the cancer cell is decomposed into RNA, it is 10 9 times, and the protein is 10 19 times, so large data is enough to form large data, and gene research is faced with such magnitude of data research and application.

Taking the qualitative and quantitative study of tumor cells as an example. First, you know what the tumor cells are now, and what the cells will look like when one or two genes change. Secondly, when the genetic changes of many tumor cells constitute a considerable amount of data, we can through the data to show the dynamic process of cell carcinogenesis, so as to further predict the disease. Such research would make more sense if used in the prevention and treatment of congenital diseases, and fewer babies would be born with birth defects. Watson's push for the "million-man Gene program" is a veritable big data application. Therefore, Wang Jian from the genetic research, expressed his understanding of large data: from the big goal, the implementation of large data, to achieve great science, so that the successful application of research in various fields to form a large industry.

3. On the topic of "What new technologies bring to our Lives" Wu Guosheng, a professor at Peking University's philosophy department, gives me the idea that technology itself is not value neutral, it has its own logic and attributes, and that makes it necessary to embrace the inherent logic of new technologies when using new technologies, And that will change the way we live.

In the past, we thought technology was neutral, it was a tool for human use, and how it was used depended on human beings, but that was not the case. Technology has its own autonomy, its own structure, some technology must point to something. For example, the Internet is a technology based on democratic ideology, Internet users are relatively equal distribution of information, sharing information, so the technology originated in the United States, not China. And when the internet comes into China, people, besides enjoying the convenience and efficiency of the Internet, are forced to accept the ideology of democracy, equality and openness in the Internet world, which is rooted in Internet technology. Therefore, although the domestic building of the Internet wall, but the wall is also easy, this is the internal logic of the Internet decision.

4. On the topic of large data and social change, experts from different fields share their feelings from their respective fields.

, a translator of the big Data age, Zhou that the more advanced stages of large data should be the integration and sharing of data and the integration and sharing itself as a business model.

He cited an example of a larger data to help the global energy better be configured. First, Zhou's UESTC worked with the power group to learn about energy supply and demand in various countries through a large number of remote sensing devices and local exploration data. Secondly, through the cooperation with the Meteorological Bureau to obtain weather data, including sunshine, wind direction, rainfall and so on, so that solar, wind, water and other new energy to achieve short-term forecasts, and achieve energy load balance. These data, if they are integrated and shared with the Power group's data, will enable more efficient deployment of energy resources.

The columnist, Ann, talks about a problem: Big Data has a class nature, and the big data age may be the birth of a new political revolution.

Before, Yu, director of the Social Research Center of the Institute of Agriculture, Cass, said that big data makes everyone more transparent, and that all kinds of behavior in our lives will be collected through data and analyzed, so ordinary people can say there is no secret. However, these data are not common people can see or use, the real ownership of these data is some enterprises, institutions and governments, ordinary users are only large data providers, this is the generation of class.

Therefore, in the large data age, the ownership of data is a key issue. This is similar to the original state of capital when capitalism was first born. If we say that the lack of material causes the flow of capital, the emergence of capitalism is the emergence of some enterprises and share power with the state, we can also say that the Big data era is just wet a new political revolution of the birth of the era. If people with large numbers do not allow people to share the results of big data, but use large numbers to control people (such as stability), it may cause greater internal conflicts, even international struggles.

sociology Professor Guo Hua is concerned about how ordinary people in society face and use new technologies, will new technologies narrow the information divide and the social divide?

She has done a study on how the new generation of migrant workers use information technology. Her conclusion is that new technologies will help the social integration and urban integration of migrant workers in the Cenozoic. In fact, the new technology has indeed brought about a change in their lives: first, the migrant workers are a public life of the lack of people, information technology to their mutual communication has brought a lot of convenience; Secondly, the new media gave them the channel of expression, which was never before; They can get a better understanding of the world by invoking all the information they need in the new media.

But even so, we cannot overstate the role of information technology in vulnerable groups, because it does show a stronger Matthew effect: a strong ability to make better and better use of these new technologies, while also controlling others. Therefore, it is the key problem whether the new technology can penetrate the barrier of social structure.

In fact, research like Professor Guo Hua is what entrepreneurs need. For example, "Pea pod" has been sent to the factory in Dongguan to do research, to understand the migrant workers on the intelligent terminals and mobile applications real needs. Interested people can click here to read the findings.

On the large data and new technology, in fact, remove the technical aspects of research and application, and history, society, humanities and other disciplines in the process will also cause a lot of topics, hope that these views can bring a little different thinking.