The International Symposium ‘Application of Big Data Analysis for Trend Spotting Related to the Development and Use of Human Capital’ will be held in Moscow, Russia on April 12, 2021. The Symposium is organised by the Institute for Statistical Studies and Economics of Knowledge (ISSEK) of the Higher School of Economics as a part of the XXII April International Academic Conference Economic and Social Development.

The symposium is organised in the framework of a research grant funded by the Ministry of Science and Higher Education of the Russian Federation (grant ID: 075-15-2020-928).

The event is held with the aim of discussing issues and presenting research results related to the development of technologies for processing big data and natural language analysis in application to the current tasks of predictive analytics, forecasting, identifying global trends and challenges related to human capital management.

Nowadays, the growing gap between the increasingly complex needs and instrumental capabilities in the field of strategic analytics is becoming evident. In strategic management systems at the state and corporate levels, the demand for timely and objective information (evidence-based policy) for making management decisions (actionable intelligence) is growing. At the same time, against the background of the increasing information flow, it is more and more difficult to solve this problem without using automated data analysis and data mining tools, relying only on the opinion of experts. One of the key sources of information is textual materials: news, media reports, legal and sci-tech information. To process it, various analytical tools are being created to provide information to experts based on the processing of billions of text documents and related metadata. The development of these tools is associated with the technological revolution in the field of technologies for analyzing large databases of texts (Natural Language Proсessing, NLP): thanks to the development of embedding models and transformer-type neural network architectures used to solve practical problems. We are talking about the models and approaches of BERT, ULMfit, GPT-2 and GPT-3, ELMo, and others, which allow to represent the ‘meaning’ of words and add new ones to the traditional capabilities of ‘classic’ embedding models (such as word2vec, GloVe, fastText), generative capabilities (filling in gaps in the text, writing an extended text based on the initial fragment, answering questions with justification for the choice etc.). However, progress has not yet reached such a level that there is no need for expert verification of the analysis results.

Therefore, in modern conditions, it is important to understand the existing limitations of the toolkit and to highlight promising areas of research in the field of analysis of large arrays of full-text data to support the expert activities. This becomes especially important in the context of monitoring global trends and challenges related to the formation and use of human potential. These are the issues that will be considered within the framework of the Symposium.

Russian and foreign researchers interested in this area are invited to participate in the Symposium. The program of the event is currently being formed. Many presentations of the symposium will be devoted to the challenges and opportunities associated with the emergence of new technologies and methods of analysis based on big data & NLP.

Date: April 12, 2021

Format: online (on Microsoft Teams and Verspeak platforms). The symposium sessions will be also broadcasted live on HSE ISSEK's YouTube channel.

Working language: English and Russian with simultaneous translation.

Terms of participation and registration: participation is free of charge; there is no registration fee. To take part in the event, please register at the link below until 18:00 April 11, 2021.

Contact person from Symposium Organising Committee: Ilya Sochenkov, Deputy Director of the HSE ISSEK Centre for Strategic Analytics and Big Data (isochenkov@hse.ru)

Media contacts: Elena Gutaruk (egutaruk@hse.ru)