Human personality traits are the key drivers behind our decision-making, influencing our life path on a daily basis. Inference of personality traits, such as Myers-Briggs Personality Type, as well as an understanding of dependencies between personality traits and users' behavior on various social media platforms is of crucial importance to modern research and industry applications. The emergence of diverse and cross-purpose social media avenues makes it possible to perform user personality profiling automatically and efficiently based on data represented across multiple data modalities. However, the research efforts on personality profiling from multi-source multi-modal social media data are relatively sparse, and the level of impact of different social network data on machine learning performance has yet to be comprehensively evaluated.
In this technical demonstration, we showcase the World's first personality-driven marketing content generation platform, called SoMin. ai. The platform combines deep multi-view personality profiling framework and style generative adversarial networks facilitating the automatic creation of content that appeals to different human personality types. The platform can be used for enhancement of the social networking user experience as well as for content marketing routines. 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.
Ads are everywhere. From expensive billboards to car door stickers, ads occupy every visible surface wherever we go. At the turn of the century, advertisers began to shift their focus online.
In the span of twenty years, we established a thriving ecosystem where brands can reach their targeted consumers in increasingly creative ways across the web.
Whether it is Facebook ads, Spotify banners, or pop-up notifications, consumers today are bombarded by ads nearly every second of every day.
Whilst receiving relevant ads may value-add to our busy lives, it does get a little annoying when you see that same pair of sneakers you searched for just once start appearing across all the web applications that you use.
In the end, cheap advertising that simply shoves products and services in consumers’ faces stand a higher chance of backfiring on their advertisers instead.
Employees of the Machine Learning Laboratory at ITMO University are engaged not only in theory, but also in applied projects. Some of them manage to inspire members of the scientific and professional community around the world, transform business and the digital space. Such work is carried out by the Media Research Group under the guidance of Professor Alexander Farseev . Today he talks about the research and projects of his team.
The digital media platforms of today, such as Facebook and Google, allow businesses countless options to reach their intended audiences. Through their AI-driven technologies, they promise the capability of influencing customers' lives at any given time or place. Yet, within this limitless potential, there lies a problem.
"With hundreds of thousands of targeting options and millions of data outputs, it becomes humanly impossible to fully utilize these platforms. While media platforms are truly powerful, a bottleneck occurs in the interaction between the platforms and the businesses that utilize them, " says Hendrik Schwartz, Co-founder and CRO of SoMin.ai.