Look at yourself through Zuckerberg’s eyes and help his rivals.
Sometimes you write, write in social networks on an important topic, and the reaction is zero. The doubt involuntarily creeps in, and whether that I write. And whether I write as it should. A look from the outside on your behavior in social networks can reveal those of your qualities and behavioral characteristics that you know, but consider it secondary. In this sense, Zuckerberg has more truthful assessments of your personality. Not always to small details, but always about the essence of your character and behavior. If only he has the right algorithms to transform your actions into traits of character traits. Psychologists have such algorithms long ago. We are saved only by the fact that on the other side of the monitor we want to sell something more than to manage us.
However, knowing how you behave in the eyes of algorithms is a useful matter. If only because it sees you and one of your friends in social networks meaningful to you, and you are not aware of this. The opportunity to see your digital selfie is given by the dataselfie.it program and its extensions for the chrome browser.
Data Selfie collects information about what you click (like and links), what you type, what and how long you view. Based on the monitoring results, the program provides the following information:
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The interface of the program is so-so. Obviously not for commercial use. Developers sell their service and do not plan, are guided by good intentions and claim that they do not store monitoring data anywhere other than the user's computer.
The video shows what the interface and monitoring reports look like.
For those who have doubts about the integrity of the monitoring, the developers came up with an argument and send curious people to the source code of the program on github . Of course, the impersonal data is transmitted to the server for processing. Including third parties, on whose servers user behavior is analyzed. And here is quite interesting. The main machine learning algorithm used by the service is Apply Magic Sauce from developers at the University of Cambridge Psychometric Center. It is a network of strategic research in the field of psychological, professional, clinical and educational evaluation. Part of this network is Cambridge Analytica, which became known as the demiurge Brexit and the election of Donald Trump. In addition to belonging to a common research network, both Cambridge programs have a unified methodology of psychological stratification. The monitoring uses the so-called “ocean method” (OCEAN - this is the first letters in English). The “big five” of evaluation parameters include: openness (how much you are ready for the new), conscientiousness (how perfectionist you are), extraversion (how you feel about society), benevolence (how friendly and cooperative you are) make one mad). On the basis of these measurements, you can accurately understand what kind of person you are dealing with, what his desires and fears are, finally, how he can behave.
Facebook tests "Who are you on the psycho" are very common. The most famous and relatively ancient is the MyPersonality application, launched in 2008 by Pole Mikhail Kosinsky, a student at Cambridge University, who later became the leading employee of Cambridge Analytica, and now Stanford. Zuckerberg and K himself, of course, out of competition, and he had long since laid out our fears, hopes, and manner of communication on the necessary shelves. But the British (and Cambridge is England) do not intend to lag behind in the game “to sell correctly is to play nerves”.
In full accordance with the methods of machine learning, this technology allows you to assess the preferences of Facebook users, comparing the structure of their likes and reposts with other data depending on the purpose. We use data from tens of millions of network accounts, which allow us to identify the most relevant combinations of user characteristics (gender, interests, religion, political views, personality type, orientation, marital status, and others) in the so-called percentiles (with what probability does the user fall into one category or another ).
It is clear why you are for this company to analyze your data for free via the Data Selfie website, even if it is impersonal. Its engineers thus refine the correlations and verify the accuracy of the algorithms. To sell them as part of advertising or elective targeting is a matter of technology.
The speech of the director of Cambridge Analytica about the principles of micro-targeting in election campaigns:
The first thing the awareness of one’s openness leads to is paranoia. You will be more watch your actions, data, put the anonymizer and vpn. You complicate your life with yourself, but not to the Big Network Brother. You will get 20% of the information from him and from the scammers (which is more important than IMHO), but you can also be controlled by the remaining amount of your interests. Better use this information for correcting impressions and cutting off a blank slip in a network.
Like, for example, I am completely without malicious intent, driving AI crazy when communicating on Facebook. Since there are quite a few friends, and Zuckerberg shows their posts using an unknown algorithm, I set my own rules for viewing posts. First, I created about 20 lists (for projects, interests and activities) and distribute my friends there. In the lists, I see all the posts of all the participants in the list and there is no need to look for them in the feed. Two months in a row a participant cannot be on the same list. Secondly, for those who have not been distributed among the lists of friends, within a month, I remove the subscription function when I see it in the feed, and at the beginning of each next one I activate the general subscription again. New friends are always in priority shows at first, but also flow into lists and friends, but without showing in the tape. I do not intend to exaggerate the complexity of my method, but the simple Data Selfie mechanism described above, comparing likes and reposts with personal data and mutual friends is unlikely to establish any correlations here.
However, knowing how you behave in the eyes of algorithms is a useful matter. If only because it sees you and one of your friends in social networks meaningful to you, and you are not aware of this. The opportunity to see your digital selfie is given by the dataselfie.it program and its extensions for the chrome browser.
Data Selfie collects information about what you click (like and links), what you type, what and how long you view. Based on the monitoring results, the program provides the following information:
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- Your position on political, religious, environmental, social and resonant issues;
- Your activity in chronological order, indicating the motives and accents to which you devoted the most attention;
- 10 of your best friends;
- 10 of the most significant resources for you;
- A list of keywords summarizing your interests;
- The list of characters and organizations that you pay the most attention to;
- The relevance of your personal focus of interest as a reflection of the ease of diverting your attention to the current news agenda;
- Your psychological portrait in 5 areas: openness, integrity, sociability, flexibility and anxiety.
The interface of the program is so-so. Obviously not for commercial use. Developers sell their service and do not plan, are guided by good intentions and claim that they do not store monitoring data anywhere other than the user's computer.
The video shows what the interface and monitoring reports look like.
For those who have doubts about the integrity of the monitoring, the developers came up with an argument and send curious people to the source code of the program on github . Of course, the impersonal data is transmitted to the server for processing. Including third parties, on whose servers user behavior is analyzed. And here is quite interesting. The main machine learning algorithm used by the service is Apply Magic Sauce from developers at the University of Cambridge Psychometric Center. It is a network of strategic research in the field of psychological, professional, clinical and educational evaluation. Part of this network is Cambridge Analytica, which became known as the demiurge Brexit and the election of Donald Trump. In addition to belonging to a common research network, both Cambridge programs have a unified methodology of psychological stratification. The monitoring uses the so-called “ocean method” (OCEAN - this is the first letters in English). The “big five” of evaluation parameters include: openness (how much you are ready for the new), conscientiousness (how perfectionist you are), extraversion (how you feel about society), benevolence (how friendly and cooperative you are) make one mad). On the basis of these measurements, you can accurately understand what kind of person you are dealing with, what his desires and fears are, finally, how he can behave.
Facebook tests "Who are you on the psycho" are very common. The most famous and relatively ancient is the MyPersonality application, launched in 2008 by Pole Mikhail Kosinsky, a student at Cambridge University, who later became the leading employee of Cambridge Analytica, and now Stanford. Zuckerberg and K himself, of course, out of competition, and he had long since laid out our fears, hopes, and manner of communication on the necessary shelves. But the British (and Cambridge is England) do not intend to lag behind in the game “to sell correctly is to play nerves”.
How an impersonal analyst works
In full accordance with the methods of machine learning, this technology allows you to assess the preferences of Facebook users, comparing the structure of their likes and reposts with other data depending on the purpose. We use data from tens of millions of network accounts, which allow us to identify the most relevant combinations of user characteristics (gender, interests, religion, political views, personality type, orientation, marital status, and others) in the so-called percentiles (with what probability does the user fall into one category or another ).
It is clear why you are for this company to analyze your data for free via the Data Selfie website, even if it is impersonal. Its engineers thus refine the correlations and verify the accuracy of the algorithms. To sell them as part of advertising or elective targeting is a matter of technology.
The speech of the director of Cambridge Analytica about the principles of micro-targeting in election campaigns:
The first thing the awareness of one’s openness leads to is paranoia. You will be more watch your actions, data, put the anonymizer and vpn. You complicate your life with yourself, but not to the Big Network Brother. You will get 20% of the information from him and from the scammers (which is more important than IMHO), but you can also be controlled by the remaining amount of your interests. Better use this information for correcting impressions and cutting off a blank slip in a network.
Like, for example, I am completely without malicious intent, driving AI crazy when communicating on Facebook. Since there are quite a few friends, and Zuckerberg shows their posts using an unknown algorithm, I set my own rules for viewing posts. First, I created about 20 lists (for projects, interests and activities) and distribute my friends there. In the lists, I see all the posts of all the participants in the list and there is no need to look for them in the feed. Two months in a row a participant cannot be on the same list. Secondly, for those who have not been distributed among the lists of friends, within a month, I remove the subscription function when I see it in the feed, and at the beginning of each next one I activate the general subscription again. New friends are always in priority shows at first, but also flow into lists and friends, but without showing in the tape. I do not intend to exaggerate the complexity of my method, but the simple Data Selfie mechanism described above, comparing likes and reposts with personal data and mutual friends is unlikely to establish any correlations here.
Source: https://habr.com/ru/post/325790/
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