Open AccessTwitter Data Import Models
Author(s) -
Попов Владимир Александрович,
Чеповский Александр Андреевич
Publication year - 2021
Publication title -
vestnik novosibirskogo gosudarstvennogo universiteta. seriâ: informacionnye tehnologii/vestnik novosibirskogo gosudarstvennogo universiteta. seriâ: informacionnye tehnologii v obrazovanii
Language(s) - English
Resource type - Journals
eISSN - 2410-0420
pISSN - 1818-7900
DOI - 10.25205/1818-7900-2021-19-2-76-91
Subject(s) - computer science , software , graph , theoretical computer science , data mining , basis (linear algebra) , series (stratigraphy) , social network (sociolinguistics) , algorithm , social media , world wide web , mathematics , programming language , paleontology , geometry , biology
In this paper, the authors describe an algorithm for importing data from the social network Twitter and building weighted social graphs. To import data, the given posts are taken as a basis, users who have had any of the recorded interactions with them are downloaded. Further, the algorithm focuses on the given configuration and uses it to calculate the weights on the edges of the resulting graph. The configuration takes into account the type of user interaction with each other. The authors introduce the concept of (F, L, C, R)-model of information interaction. The authors describe the developed algorithm and implemented software for constructing weighted graphs. The paper shows the application of the algorithm and three models on the example of both a single post and a series of posts.