Can the country distribution of users be determined through Facebook friend lists?

is doing cross-border traffic, social analysis or When operating in the international private domain, we often need to know the country of a certain Facebook user. Especially when you have the user's UID but cannot directly obtain its country field, someone has proposed this idea: Can you reversely determine the country distribution of the user through the Facebook friend list? This method may seem "indirect", but in fact, in the big data and intelligent judgment mechanism, the social circle of friends is indeed one of the important reference factors for determining national affiliation. This article will analyze in detail how to use friend lists to analyze country distribution, as well as the current mainstream automated identification methods.

When doing cross-border traffic diversion, social analysis or international private domain operations, we often need to understand a certainFacebook user'snational belonging, especially when you have the userUID, but its country field cannot be obtained directly, someone came up with this idea:Can it pass?Facebook friend list, reversely determine the country distribution of users?This method looks like"Indirectly", but in fact, in big data and intelligent judgment mechanisms,The social circle of friends is indeed one of the important reference factors in determining national affiliation.. This article will analyze in detail how to use friend lists to analyze country distribution, as well as the current mainstream automated identification methods.

 

WhyIs "Country" the most important field in Facebook data analysis?

When building user personas,"Country" is one of the basic information. It not only represents the market where the user is located, but also directly determines the following key variables:

lLanguage usage habits

lCultural preferences and social content types

lTime zone and active period

lBusiness affordability and consumer behavior

Without the country field, you can't judge the batchWhether the UID is a target market user, marketing costs and accuracy will also be seriously reduced. Therefore, even if many users cannot read country information directly from public information, they still hope to use side features (such as friend lists) for reverse identification.

 

What clues does a Facebook friend list contain?

AlthoughFacebook has gradually tightened its privacy display policy, but it is still possible to obtain the following information through users’ interactive behaviors or public friend lists:

lFriend'sUID, avatar, nickname

lLanguage in friends’ public profiles/location/interactive dynamics

lInteraction time, language type, and tags between users and friends

lThe groups the user has joined, the pages they like, and the attributes of the people they follow

in other words,A user's social circle is a collection of clues about his country affiliation.. If a friend of an account95% are from Indonesia, and the interactive language is Indonesian. The system will determine that it is an Indonesian account with a high probability.

 

How to determine the user's country through the friend structure?

This technology is calledSocial relationship inverse modeling, mainly including the following judgment logic:

1. Distribution statistics of friend countries

The system will send a message to each of the user's friendsUID performs country identification (based on language, registration behavior, avatar, group, etc.), and then counts the most common countries. For example:

lAmong a user’s friends are80% are Spanish-speaking users, concentrated in Mexico and Argentina;

lRemaining20% are from English-speaking areas, distributed in the Philippines and the United States;

lResult: The system marks him as a Latin American user, and the default country is Mexico.

2. Language analysis of friends’ interactions

Even if friends do not fill in the country field, if most of the user's interactive behaviors (comments, likes, forwarding) are in a certain language, it can also become a key basis for country identification.

For example, if a user's friend comments are almost all in Vietnamese, and the usage period is concentrated in the evening local time in Vietnam, it can basically be judged that he is a Vietnamese user.

3. Group and homepage common attention analysis

If almost all of a user's friends have joined certain country-based groups (such as Filipino shopping groups, Arabic second-hand market groups) or followed local business homepages in specific countries, the user's regional attributes can also be inferred.

This method is suitable for situations where the original account information is missing but the friend information is relatively abundant.

 

Does it need to be visible to all friends to judge?

unnecessary. Actually,It is not necessary to display every friend. As long as there is a certain amount of interactive friends, common groups or like homepage information, the system can make country judgments through graph correlation and language analysis.

This is one of the advantages of big data discrimination.Even if the sample size is incomplete, relatively accurate inference conclusions can be drawn from the structural relationships.

 

Is there any ready-made system that can automatically complete this kind of judgment?

Manual operation is undoubtedly inefficient. Faced with thousands ofUID or account data, more requiredA set of standardized and automated processing methods.

On the Digital Planet platform, you can achieve country identification in your friend list through the following methods:

luploadUID list, the platform automatically extracts the structure of friends’ social circles

lThe system identifies the national attributes of each friend through a multi-dimensional model

lSummarize the country composition of the social circle and output the most likely primary country label.

lComes with eachUID’s language preference, interaction mode, friend source ratio

Not only can the country of the account itself be identified, but the country composition of its potential customer group can also be identified.——This is very practical for scenarios such as expanding multi-language markets, international community screening, and advertising placement.

 

Advantages of Digital Planet’s Country Identification Model

In order to improve the recognition accuracy, the Digital Planet platform uses a three-layer filtering structure:

1.Basic field analysis model: According to language, registrationIP, page preference identification country;

2.Relationship circle statistical model: According to friendsThe country label of the UID group reversely determines the account attributes;

3.Cross-validation mechanism: Recalibrate the country mark through behaviors such as associating groups, liking homepages, and commenting languages.

This multi-source identification method allows even if an account lacks clear information, it can still be identified throughThe "relationship inversion" method achieves accurate attribution.

 

There are benefits for current registration, and free gold coins can be used to unlock more features when recharging.

Digital Planet is now open for registration, and the basic functions are free to use. At the same time, you can get additional bonus coins with data recharge:

ltop up588 gold coins free 30 gold coins

ltop up1088 gold coins and 60 gold coins free of charge

lThe more you recharge, the more gifts you get, which can be directly deducted from your data usage limit.

Gold coins can be used to unlock country identification modules, advancedUID field extraction tool, batch upload tasks and other functions.

 

If you are collecting users from a certain country, but the progress is slow because of incomplete information,

Let’s change the angle and start fromStarting from the Facebook friend list, use social circle analysis to reversely target country attributes..

Visit Digital Planet and experience this efficient and practical user country identification system, allowing you to extract accurate data value from fragmented information.

 

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