User Interests Mining

This technology identifies user interests on the basis of data from social networks, including community memberships, responses to posts, personal publications, and profile information.

About the technology

  • More than 250 different interests.
  • Degree of involvement from 1 to 100.
  • Interest dynamics.
  • Regular data updates.

Examples of a user’s interests

How do we calculate interests?

  1. Machine learning algorithms are used to determine the topic of posts and the communities the user is interested in.
  2. The degree of involvement is based on the number of the user’s comments, likes, posts, and reposts in a specific community.
  3. The resulting degree of interest is a linear combination of the degree of involvement based on the likelihood of interest in a post/community normalized for a range of 1 to 100.

In research

In products

In advertising

Other technologies

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    Determination of the social media user’s social and demographic profile

  • Social Network Search

    Search company clients on social media by telephone and/or e-mail for research and advertising purposes

  • Sentiment Analysis

    Determination of the tone of the text and identification of +30 basic emotions, including sadness, surprise, desire, etc.

  • Topic Categorization

    Text categorization by +200 topics such as sports, real estate, finance, etc.

  • Profile Matching

    Identification of a single user’s profiles on different social media and integration of their information

  • User Data Matching

    Used to match social media user profiles with user data in free form 

  • Look-alike

    Search social media users that look like business clients or a certain audience