Machine learning - completed projects
QTM (IMPROVING THE METHODOLOGY OF AUTOMATIC TEXT ANALYSIS), 2018-2023
Project leader: Sergey Koltsov
Topic modeling is a promising instrument for computational social science and digital humanities as it allows to automatically reveal thematic structure of large text collections – an immensely important task in the era of big Internet data. However, topic modeling, notably LDA as its main algorithm, has a number of problems that prevent its efficient use by social scientists, including social media analysts.
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EthnoHate (Ethnic Hate Speech Prediction in Social Media Texts), 2018-2020
Project leader: Olessia Koltsova
The project aims to identify ethnic hate speech in social media texts. In the course of the project, experiments were conducted with traditional classification models and with neural networks and their applicability for this task was investigated.
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EthnoMonitor (Development of Concept and Methodology for Multi-Level Monitoring of the State of Interethnic Relations with the Data from Social Media), 2015-2017
Project leader: Olessia Koltsova
The major result of this project is a conceptual approach to and a methodology of system devised to monitor ethnic relations on the Post-Soviet space. Its main goal was to trace, in a semi-automatic way, distribution of discussions about ethnicity in the Russian-language social media over time and space. The primary task of this tracing was an early prevention of emerging inter-ethnic conflicts.
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PolSentilex (Open database and a crowdsourcing website for development of sentiment analysis instruments), 2014-2016
Project leader: Sergey Koltsov
The project is aimed at the development of a software, a database and a sentiment lexicon that can further help create a methodology of detecting the emotional polarity of user-generated Russian language content.
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Network Classification and Packet Switching, 2015
Project leader: Sergey Nikolenko
The modern network edge must perform a wide spectrum of tasks: deep packet inspection, firewalling, VPN services, intrusion detection and many others. These tasks may have radically different computational requirements but traditional architectures of network processors are not suitable for processing packets with heterogeneous processing requirements. We obtained new results in this field.
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Recommender Systems, 2014
Project leader: Sergey Nikolenko
Recommender systems analyze user interests and try to predict which items will be most interesting for a specific user at a specific moment of time. Modern recommender systems are based on collaborative filtering (Bell, Koren, 2007a; 2007b; Koren, 2008; 2009; 2010; Koren, Bell, 2011; Agarwal, Chen, Elango, 2009); they have experienced a surge of interest over the latest years based on the Netflix Prize contest devoted to developing a new movie recommendation system.
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The Development of a Methodology for the Network and Semantic Analysis of Blogs for Sociological Purposes, 2012
Project leader: Olessia Koltsova
This project, which researched the discussion of socially important topics in the Russian blogosphere, was carried out with the support of the HSE Scientific Foundation as part of the contest ‘Teachers and Students 2011–2012’. The researchers collected and analyzed an array of Internet data. The long-term goal of this project was focused on developing a new method that raised the quality of social Internet research to the next level.
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Project leader: Sergey Koltsov
Topic modeling is a promising instrument for computational social science and digital humanities as it allows to automatically reveal thematic structure of large text collections – an immensely important task in the era of big Internet data. However, topic modeling, notably LDA as its main algorithm, has a number of problems that prevent its efficient use by social scientists, including social media analysts.
More...
EthnoHate (Ethnic Hate Speech Prediction in Social Media Texts), 2018-2020
Project leader: Olessia Koltsova
The project aims to identify ethnic hate speech in social media texts. In the course of the project, experiments were conducted with traditional classification models and with neural networks and their applicability for this task was investigated.
More...
EthnoMonitor (Development of Concept and Methodology for Multi-Level Monitoring of the State of Interethnic Relations with the Data from Social Media), 2015-2017
Project leader: Olessia Koltsova
The major result of this project is a conceptual approach to and a methodology of system devised to monitor ethnic relations on the Post-Soviet space. Its main goal was to trace, in a semi-automatic way, distribution of discussions about ethnicity in the Russian-language social media over time and space. The primary task of this tracing was an early prevention of emerging inter-ethnic conflicts.
More...
PolSentilex (Open database and a crowdsourcing website for development of sentiment analysis instruments), 2014-2016
Project leader: Sergey Koltsov
The project is aimed at the development of a software, a database and a sentiment lexicon that can further help create a methodology of detecting the emotional polarity of user-generated Russian language content.
More...
Network Classification and Packet Switching, 2015
Project leader: Sergey Nikolenko
The modern network edge must perform a wide spectrum of tasks: deep packet inspection, firewalling, VPN services, intrusion detection and many others. These tasks may have radically different computational requirements but traditional architectures of network processors are not suitable for processing packets with heterogeneous processing requirements. We obtained new results in this field.
More...
Recommender Systems, 2014
Project leader: Sergey Nikolenko
Recommender systems analyze user interests and try to predict which items will be most interesting for a specific user at a specific moment of time. Modern recommender systems are based on collaborative filtering (Bell, Koren, 2007a; 2007b; Koren, 2008; 2009; 2010; Koren, Bell, 2011; Agarwal, Chen, Elango, 2009); they have experienced a surge of interest over the latest years based on the Netflix Prize contest devoted to developing a new movie recommendation system.
More...
The Development of a Methodology for the Network and Semantic Analysis of Blogs for Sociological Purposes, 2012
Project leader: Olessia Koltsova
This project, which researched the discussion of socially important topics in the Russian blogosphere, was carried out with the support of the HSE Scientific Foundation as part of the contest ‘Teachers and Students 2011–2012’. The researchers collected and analyzed an array of Internet data. The long-term goal of this project was focused on developing a new method that raised the quality of social Internet research to the next level.
More...
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