no code implementations • 25 Jul 2022 • Qi Yang, Sergey Nikolenko, Alfred Huang, Aleksandr Farseev
In order to run organic and paid social media marketing efficiently, it is necessary to understand the audience, tailoring the content to fit their interests and online behaviours, which is impossible to do manually at a large scale.
no code implementations • 20 Jun 2021 • Qi Yang, Aleksandr Farseev, Andrey Filchenkov
We have also found that the selection of a machine learning approach is of crucial importance when choosing social network data sources and that people tend to reveal multiple facets of their personality in different social media avenues.
no code implementations • 30 Nov 2020 • Aleksandr Farseev, Qi Yang, Andrey Filchenkov, Kirill Lepikhin, Yu-Yi Chu-Farseeva, Daron-Benjamin Loo
Guided by the MBTI personality type, automatically derived from a user social network content, SoMin. ai generates new social media content based on the preferences of other users with a similar personality type aiming at enhancing the user experience on social networking venues as well diversifying the efforts of marketers when crafting new content for digital marketing campaigns.
no code implementations • 5 Feb 2020 • Qi Yang, Aleksandr Farseev, Andrey Filchenkov
Specifically, in this work, we will study the performance of different machine learning models when being learned on multi-modal data from different social networks.