Science / Press

Understanding economic and health factors impacting the spread of COVID-19 disease 15 February 2022

Background

The rapid spread of the Coronavirus 2019 disease (COVID-19) had drastically impacted life all over the world. While some economies are actively recovering from this pestilence, others are experiencing fast and consistent disease spread, compelling governments to impose social distancing measures that have put a halt on routines, especially in densely populated areas.

Objective


Aiming at bringing more light on key economic and population health factors affecting the disease spread, this initial study utilizes a quantitative statistical analysis based on the most recent publicly available COVID-19 datasets.

Methods

We have applied Pearson Correlation Analysis and Clustering Analysis (X-Means Clustering) techniques on the data obtained by combining multiple datasets related to country economics, medical system & health, and COVID-19 - related statistics. The resulting dataset consisted of COVID-19 Case and Mortality Rates, Economic Statistics, and Population Public Health Statistics for 165 countries reported between 22 January 2020 and 28 March 2020. The correlation analysis was conducted with the significance level α of 0.05. The clustering analysis was guided by the value of Bayesian Information Criterion (BIC) with the bin value b = 1.0 and the cutoff factor c = 0.5, and have provided a stable split into four country-level clusters.
Two-Faced Humans on Twitter and Facebook: Harvesting Social Multimedia for Human Personality Profiling 10 February 2022

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.
SoMin.ai: Personality-Driven Content Generation Platform 10 February 2022

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.

Press About Us

Maya: The New AI-Driven Frontier of Influencer Marketing 02 December 2020

Artificial intelligence has completely redefined the world we live in today. Now, our mornings start with personal assistants waking us up and laying our favorite playlists. Bots help customers with their questions and issues about the services and products they have purchased. And now, artificial intelligence is capable of redefining influencer marketing with the power of creating a persona.

Meet Maya — the next-generation virtual influencer set to transform the concept of brand marketing.

Advertising Smart and Big Date: a Singaporean Startup Entered the St. Petersburg Market 02 December 2020

The Somin.ai startup, which improves its ad targeting using artificial intelligence, has entered the St. Petersburg market. A Singapore-based startup uses big data and artificial intelligence to boost conversions.

In targeted advertising from Citibank, AI increased conversion by 53% and reduced the cost of customer contacts by 43%, Somin.ai founder Alex Farseev told DP. The Lenta network noted a 2.5-fold improvement in the effectiveness of an advertising campaign. Somin.ai is currently working with MTS.
Artificial intelligence helped Lenta to increase the effectiveness of advertising campaigns 2.5 times 02 December 2020

Lenta has completed piloting a Singapore startup to set up targeted advertising, the company's press service reports.

Lenta's digital marketing service, with the support of the company's Innovation Center, tested the project on an Instagram advertising platform for a month. The artificial intelligence platform processed data from social networks and determined user preferences.

As a result, the effectiveness of targeted advertising has increased 2.5 times compared to using classic tools for launching advertising campaigns. It was originally planned that this figure will grow by 20%.

“During testing, we paid attention not only to the cost per click, but also to the bounce rate. Quality traffic is important to us. The startup really identified users for whom our advertising was relevant, ”said Boris Evdokimov, head of Lenta's digital marketing department.

Thanks to the use of artificial intelligence, the company will be able to halve the costs of launching advertising campaigns on Instagram and increase the number of conversions in stores by 37%.

Earlier it was reported that "Lenta" opened a large distribution center in the Leningrad region. Online sales of Lenta grew 6.5 times in Q3 2020.