Dating software development

Digitalization trends in the dating industry

In 2005, 57% of online dating led to dating in real life, and in 2017 the figure began to decline and reached 34%. There are reasons for this. In order for a strong couple to form, the goals and requirements of the partners for each other must coincide. The questions of the questionnaires and filters on the service help to ensure this coincidence. And if the filters work superficially, the questionnaire is not completely filled out, the user indicated incorrect or frankly false information?

The number of users has increased significantly, in this regard, a huge amount of time is spent looking through the profiles and finding a suitable pair. Fake accounts are still stealing our time, and the men in the photographs don’t really exist. In addition, dating sites are drowning in information trash and spam. Hidden subscriptions get access to bank cards. Scammers use chatbots to carry out a lot of clever scams. In this regard, services are poorly protected from cyber attacks, and confidential data is often leaked.

In addition, there is one more nuance. Often people themselves distort their real goals and interests, but not intentionally, of course. They ask for one thing and choose another. Under the pressure of stereotypes adopted in society and their vague ideas about the future soulmate, those requirements for a partner are often indicated, which in fact are not very important for them.

An innovative solution that can secure virtual communication and make it effective is the use of artificial intelligence to help users choose partners. Traditional dating sites are in no hurry to implement it, and in vain, because startups are stepping on their heels. A striking example is the Denim application, which has introduced artificial intelligence into its services. Fraudsters or attackers trying to trick the system now face an individual matchmaking manager: artificial intelligence and automated algorithms.

Another example of incorporating AI into dating is Tinder’s “Super Likeable” feature. It allows you to predict which type of men or women is most suitable for the user, and, accordingly, will offer to chat with suitable partners.

In January 2016, the HeyBlinkMe app was released, making quick dates with live video. A couple of users receive two questions for the first acquaintance and start chatting via video. AI analyzes the emotions of the communicators, and if it catches dissatisfaction or unwillingness to communicate, the video turns off and resumes only if both people agree to continue the interrupted conversation.

It is obvious that the introduction of digital technologies in the field of dating is associated with the need to ensure security.

A number of projects (for example, BigData Love, Matchpool) are working to ensure maximum security by identifying users through the blockchain and intelligent verification, that is, confirming the authenticity of data in order to solve the problem of spreading fake profiles. And these are not all the possibilities of artificial intelligence.

Artificial neural networks created from simple processors can solve complex problems based on analysis, following the example of the work of the human brain. The more people are registered in the application, the larger the database and the more accurately the artificial intelligence works. Neural networks are capable of learning and are able to perform three tasks.

• Classification. All users are easily grouped by the data they provide.
• Prediction. The next step of the user is determined based on the situation at the moment. Therefore, individual recommendations for each specific person and the preparation of a personalized selection of questionnaires are possible.
• Recognition. The facial features of the users you like are highlighted and recognized.

Search engines actively use big data processing technology and successfully deliver ads based on our requests. They use a huge amount of information about each user: favorite music, political preferences and much more. The same principle works in dating. But using only information provided by the user himself is too primitive for neural networks. They do a tremendous amount of analytical work.

The user’s preferences will be taken into account by analyzing his real behavior on the dating site: what photos he likes, whose profiles he views, to whom he writes, with whom he calls up and communicates the longest.

Also, morphological and semantic parsing of text in user dialogs will be performed using special algorithms. So you can determine the purpose of registering a person on the site, his interests and character traits, the manner of communication.

In addition to facial features, anthropometric data are also taken into account, that is, the main physical indicators: height, chest circumference, waist. Playlists and purchases from electronic stores will be examined. If these are not one-off purchases, it is quite easy to assess the taste and needs of a person. Suitable candidates will be proposed on the fly.

This is what information technology developers are planning to implement: calculating profiles with false data, converting speech to text, analyzing mood in text and audio, recognizing faces, biometric data and GPS, analyzing information from the previous generation.