This is the concluding part of my article devoted to a statistical analysis of police shootings and criminality among the white and the black population of the United States. In the first part, we talked about the research background, goals, assumptions, and source data; in the second part, we investigated the national use-of-force and crime data and tracked their connection with race.
Full HP Ltd is an international mobile game development company with 40+ employees and offices in Rostov-on-Don and Cyprus. Their portfolio includes 8 games, among them Mad GunZ (a Google Play Editors' choice) and Blocky Cars (a Catappult Editors' choice). Mad GunZ has over 12 million downloads on all platforms, and Blocky Cars has over 32 million.
The company is actively involved in the life of the IT community and is a sponsor of the Sunflower game devs festival.
The Full HP Ltd team translates texts for Blocky Cars and Mad GunZ using Nitro professional translation service, and agreed to share some of their lifehacks with us:
how to maximize ASO optimization results
how to get on the home page of Google Play
how to monetize children’s games
and the benefits of releasing a game on alternative platforms.
Currently, social network sites tend to be one of the major communication platforms in both offline and online space. Freedom of expression of various points of view, including toxic, aggressive, and abusive comments, might have a long-term negative impact on people’s opinions and social cohesion. As a consequence, the ability to automatically identify and moderate toxic content on the Internet to eliminate the negative consequences is one of the necessary tasks for modern society. This paper aims at the automatic detection of toxic comments in the Russian language. As a source of data, we utilized anonymously published Kaggle dataset and additionally validated its annotation quality. To build a classification model, we performed fine-tuning of two versions of Multilingual Universal Sentence Encoder, Bidirectional Encoder Representations from Transformers, and ruBERT. Finetuned ruBERT achieved F1 = 92.20%, demonstrating the best classification score. We made trained models and code samples publicly available to the research community.
Looking for an app development company? I’ve searched for information about it and made this list. It might help to find an app development company to hire. The list contains basic information about each company included in it like company size, hourly rate, min. project size, etc. And I recently decided to upgrade the list to 100 app development companies.
