Online dating

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Online dating is an internet service that attempts to match couples using a system in which individuals can choose their partners according to such preferences as age, location and race. It is one of the most popular paid services on the Internet.

Upon joining the dating service, the users answer questions from a mandatory survey and create “profiles” of themselves. Such a profile is a webpage that provides information about a user and can be viewed by the other members of the dating service. The users indicate various demographic, socioeconomic, and physical characteristics, such as their age, gender, education level, height, weight, eye and hair color, and income. The users also answer a question on why they joined the service, for example to find a partner for a long- term relationship, or, alternatively, a partner for a “casual” relationship. In addition, the users provide information that relates to their personality, life-style, or views.

With hundreds of millions of members, Internet dating earns greater revenues than any other online subscription service. One study showed that eHarmony alone accounted for 2% of US marriages in a year, that is, 120 marriages per day. We will investigate the methodologies used by these online services in finding appropriate matches, particularly their search algorithms, but also the interfacing tools commonly used and these organizations' histories through the spread of the Internet.

Matrimonials is an ancillary concept applied mostly to international sites, with significantly more determined ends. It is interesting to view how cultures with perhaps traditional views on marriage employ non-traditional technology to facilitate it. We will introduce other relevant sociological issues, such as the cultural significance of the prevalence of online dating and how culture is altered by this prevalence.

Algorithm

Online dating has turned searching for possible partners similar to other e-commerce websites, like online shopping. To enable this, many different algorithms have been created. Each online dating company boast about their superior technology to show and create better matches. All possible approaches incorporating psychological to mathematical theories have been used.

Though each company may take a different approach, matching personalities is broadly divided into three stages which all companies use:

• Collection of User Information
• Matching Users
• Communication between users .

Collection of User Information

This step starts the very moment a person joins an online dating service. Some people don’t use online dating services for this very step of sharing private information about themselves. The data collected are basically of two types: characteristics data and criteria data. Characteristic data essentially describes the user; while the criteria data is what the user expects out of a possible partner.

Services collect data via various types of questions. There are some direct fundamental ‘yes’ or ‘no’ questions. Some ranking questions, where a user must rank various choices according to his preferences. Some questions where a user is given two possible extremes and he/she may choose anywhere between one extreme to the other and indirect questions which calculate the compatibility of a person. There are also options for users to ask their own constructed questions and also define themselves.

Once all this data is collected it has to be converted using mathematics to allow various algorithms to match people.

Matching Users

The most basic matching is done by the users themselves, when they search the database manually. This gives a lot of control to the user but it is tedious. So to do this automatically, all the responses of the users are converted into compatibility scores (which is relative strength of each match) to mathematically match people. Services look for both complementing and similarity between users to be matched.

All dating services claim trade secrecy of their particular matching algorithm. However, all matching consists of these vital steps that all the services incorporate. Firstly, the data is saved into the data base and converted to numerical scores. Compatibility scores are then calculated. A range is then formed around a person’s compatibility scores to see which other users fall into his/her range. If a person is easy going then his range will generally be higher than a difficult person. If there is very less people in someone’s compatibility range, then they may be asked to change some answers to questions from the previous ‘user information collection’ stage to get a higher volume of possible matches.

During this phase mathematical correlation is used too. Various types of factor analysis are also done. All characteristic and criteria data are considered factors. All factors are given different mathematical values and then depending on how important that particular factor is for the user, it is multiplied by a weight.

Once potential matches are listed, communication between users is facilitated.