Understanding economic and health factors impacting the spread of COVID-19 disease
15 February 2022
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.
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
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.
Hack with tech: How Innovative Ideas Help Your Business Grow
02 December 2020
Getting leads for credit card and personal loan applications in the banking industry has always been an ordeal. So when we applied our technology to Citibank’s products and saw a 40% uplift in sales we got really excited. There’s no greater satisfaction than seeing your products solve persistent industry problems.
Even better when the clients and their partners talk about you because of the proven result.
Will virtual humans replace ‘real’ influencers, models, and more?
06 October 2020
Miquela Sousa is a 19-year-old social media star with 2.7 million followers on Instagram.
Decked out in high fashion brands like Puma and Chanel, she wears her personality- and endorsements- on her sleeve. Except, she isn’t real.