Применение методов лексико-морфологического анализа данных социальных сетей для задачи кредитного скоринга
Аннотация
The Master thesis on the topic “Using Social Network Data For The Task Of Credit Scoring” contains 95 pages, 28 figures, 2 tables and 78 sources used.
The main factor of making a decision or solving a problem is having enough information, the more the parameters are given the easier the solution.
The problem here is to determine whether to give an applicant loan or a credit banks and lenders the y need lots of information about the applicant in order to make this decision. This information can be taking form the applicant himself or for other agencies specialized in business. But we are forgetting to largest and renewable source of information about people which is social networks so in this paper I developed a few models that is going to extract social network data and use it to predict the statues of an applicant based on similar applicant’s data.
The main factor of making a decision or solving a problem is having enough information, the more the parameters are given the easier the solution.
The problem here is to determine whether to give an applicant loan or a credit banks and lenders the y need lots of information about the applicant in order to make this decision. This information can be taking form the applicant himself or for other agencies specialized in business. But we are forgetting to largest and renewable source of information about people which is social networks so in this paper I developed a few models that is going to extract social network data and use it to predict the statues of an applicant based on similar applicant’s data.