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Text analytics and natural language processing become increasingly important in many business companies and the financial services world is no exception. The banking sector is struggling to find new ways of communicating with customers in order to answer to their needs in various innovative ways. The aim to ease customer communication through modern technologies has a central place in the digitalization roadmap of many banks and here comes the important role of text analytics. The goal of this paper is to derive new and useful insights on customer behavior, study the usefulness of a well-known topic modeling technique and propose a methodology for its application in the banking domain. The current empirical study is carried out on real chat data generated between operators in a call center and clients of a large bank. We capture the main topics of client interest, analyze their characteristics and trace their development over time. Several challenges are faced during the empirical study mainly stemming from the domain and noisiness of data - it is predominantly in Bulgarian but there are chats in other languages too; transliteration is extensively used; there are some specific structural characteristics inherent to chat data. Nevertheless, results are promising - the extracted topics are interpretable and meaningful which is confirmed by the application of different techniques for evaluation of results. As a major contribution of the current empirical study, we consider the valuable insights into customer behavior obtained from the analysis of real-world chat data in the banking domain. Furthermore, results can be used not only for tracking trends in customer behavior, but they can serve as guidance for the effective development of chatbot systems. Considering the challenges imposed by chat data in the banking domain, another contribution of the current paper is the development of a methodology for topic extraction from chats in this domain. The current research also suggests what text processing techniques should be applied on customer support chats in order to obtain more meaningful results. The last is applicable to data not only in the banking domain, but in any other text data domain too. Finally, results from the experiment are also evaluated through the lens of the COVID-19 crisis and the analysis of its impact on customer behavior. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate weighted time-varying causal graphs based on daily log-return and realized volatility time series of the S&P500 stocks. In order to construct causal graphs for each quarter between Q1 2005 and Q2 2020, we compute cross-correlations between series and conduct pairwise Granger Causality tests for lead-lag relationships. We take individual stocks as nodes and significant causal relationships as weighted edges. Our analysis is based on a comparison of network topology and properties for different periods, including the 2007-2010 subprime crisis, the European sovereign debt crisis, and the coronavirus pandemic, as well as tranquil periods. In addition to edge weights, our study also takes into account the estimated lag of the causal interactions and uses network level measures to identify meaningful patterns over time. We also conduct an analysis of the industrial sectors interconnectedness via smaller graphs derived from the stock-level causality graphs. The results of the work reveal that network topology changes during periods of market stress and crisis and this can be captured by using convenient network construction methods and measures. Our results also show that the patterns of network topology transformation and magnitude of spillovers transmission during the coronavirus crisis and accompanying events differs from previous crisis periods. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has become an accelerator for the shift of many everyday human activities from all sectors of social and economic life from traditional face-to-face to online mode. Education, despite of its conservative nature, was most strongly influenced by this trend. This paper discusses a pedagogical experiment of integrating a system for ongoing assessment of students in a university course, which was transformed from face-to-face to online as a result of the forced transition to distance learning during the pandemic. The goal of this experiment was to motivate the permanent involvement in the learning process of students who have no experience as online learners. The study is aimed at seeking the effectiveness of the applied approach of integrated continuous assessment as a 'soft" transition from face-to-face to distance learning. [ABSTRACT FROM AUTHOR]

The ubiquity of technology in the last decades has transformed education, accelerated the development of e-learning and has placed a lot of challenges to the higher education institutions in terms of students' assessment. These potential challenges of e-assessment slowed down the process of its proliferation to some extent but the COVID-19 pandemic forced the introduction of e-assessment in all educational stages, and in most cases institutions had to "switch, almost overnight, to online teaching and virtual education" [1]. This study aims to identify the impact of students' experience from one of the leading Bulgarian universities – Sofia University (SU) in forced introduction of e-assessment on their views and perspectives about it. The research method is an online survey, conducted at the end of the semester in academic year 2019/2020 and students from all 16 SU faculties were invited to take part. The paper focuses on three main aspects – 1) students experience in e-assessment during pandemic; 2) students' views on e-assessment; and 3) the impact of their experience in e-assessment on their views. Findings from data analysis reveal that students were mostly summative assessed through course works (artefacts) submissions and tests, and the use of different types of formative assessment was very limited. The technologies utilised for the assessments by academic staff were also very deficient. These results demonstrate that most of the teachers transferred their experience and approaches to students' assessment from face-to- face to the online environment without adaptation and modification to specifics of the latter. This decreased to a certain extent the trust of students in e-assessment and reinforced their preference to face-to-face assessment. Conclusions impose the need for advanced training of academic staff in the field of e-learning and e-assessment design. [ABSTRACT FROM AUTHOR]

The article gives models of the spread of infectious diseases, including Covid-19. Models and simula- tions of an epidemic in the presence of quarantine and the moment of its termination have been made. It is particu- larly important to pinpoint the timing of the lifting of measures or their granting. Also, the proposed simulation model shows the impact of group gatherings such as: the beginning of the school year, holidays and more. mass events on the epidemic picture. These studies are also relevant in the event of a mutation in the virus that will change the rate of spread. [ABSTRACT FROM AUTHOR]

Several static models for description of the Covid-19 pandemic are considered, analyzed and compared. The best models relative to this pandemic (generalized fractional-power model and generalized inverse tangent model) are new. These and other non-symmetric models are user friendly and show a good agreement with the official data for the pandemic in Europe. The best models give less than 1% error for a 20-day prediction period and less than 1.5% error for a 40-day prediction period. Recommendations for the use of the models are made. The results obtained may be used in the analysis of possible new waves of Covid-19 in different countries, in Europe and worldwide. Such waves seem more and more likely. [ABSTRACT FROM AUTHOR]

Due to the unprecedented COVID-19 pandemic, and the resultant recommendations of the public health officials and local governments, the Organizing committee decided to use remote technologies to hold the AMEE'20 conference as a virtual meeting in place of the usual in-person conference. The present volume of proceedings consists of the papers presented during the 46 th International Conference "Applications of Mathematics in Engineering and Economics" (AMEE'20), 7- 13 June 2020. The Conference is organized every year by the Faculty of Applied Mathematics and Informatics at the Technical University of Sofia and the Faculty of Mathematics and Informatics at Sofia University "St. Kliment Ohridski". [Extracted from the article]