Модели импорта данных из мессенджера Telegram

Вестник Новосибирского государственного университета. Серия: Информационные технологии. 2022. Т. 20. № 2. С. 60–71.

Popov V., Chepovskiy A.

In this paper, an algorithm to import data from the messenger Telegram and to build weighted graphs of interacting objects is described. To import data, the given Telegram-channels are taken as a basis. Then, iteractively channels that had any of the recorded three interactions with previous ones are revealed: common external links, mentions of each other, reposts. 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 channel interaction with each other. The authors introduce the concept of (U, M, R)-model of information interaction.

The authors describe the developed algorithm and implemented software for constructing weighted graphs. The paper shows the example of weighted graph of interacting objects, that was built by the described algorithm according to the (U, M, R)-model.

Keywords: анализ социальных сетей, social network analysis, выделение сообществ, community detection, information interaction models, модели информационного взаимодействия, social networks data import, импорт данных из социальных сетей