Research and Design Seminar "Modern Digital Technologies of Text Analytics"

2024/2025

Academic Year

ENG

Instruction in English

6

ECTS credits

Delivered at:

School of Fundamental and Applied Linguistics

Course type:

Compulsory course

When:

2 year, 2, 3 module

Course Syllabus

Abstract

In the Project Seminar Modern Digital Technologies of Text Analytics (2nd year) various modern methods and techniques are studied. Multiple text types (including multimodal, different genres) are tackled with the use of software. Programming using R and Python is applied to work with Big Data. The aim of the seminar is to revise and evaluate and put into practice familiar as well as brand-new approaches.

Learning Objectives

• the development of skills based on qualitative and quantitative methods and techniques that allow to evaluate the characteristics of various communicative situations of discourse; the development of skills concerning corpus and other computer methods and techniques that allow to evaluate the characteritics of various communicative situations of discourse; the development of skills using qualitative and quantitative methods and techniques that allow to evaluate individual style features (idiostyle features) of communicants in discourse; training of masters , to do independent research design and organizational work.

Expected Learning Outcomes

• * Get value out of Big Data by using a 5-step process to structure your analysis.
• Knowledge about how to design, develop and evaluate NLP programs using programming language Python
• Knowledge about ongoing developments in NLP
• A student compares research design
• Affective mechanisms of decision-making
• Able to think critically and interpret the experience (personal and of other persons), relate to professional and social activities
• Able to solve professional problems based on synthesis and analysis
• Known basic NLP tasks

Course Contents

• NLP
• Data Visualization
• Academic project (Master’s thesis)

Assessment Elements

• home assignment
• project

Interim Assessment

• 2024/2025 3rd module
  0.4 * home assignment + 0.6 * project

Bibliography

Recommended Core Bibliography

• Academic English: Theoretical and Practical Issues : учеб. пособие / сост. Т.Ю. Мкртчян, М.Г. Науменко ; Южный федеральный университет. - Ростов-на-Дону ; Таганрог : Издательство Южного федерального университета, 2018. - 165 с. - ISBN 978-5-9275-2853-0. - Режим доступа: https://new.znanium.com/catalog/product/1039713
• Alblawi, A. S. (2018). Big Data and Learning Analytics in Higher Education: Demystifying Variety, Acquisition, Storage, NLP and Analytics.
• Aman Kedia, & Mayank Rasu. (2020). Hands-On Python Natural Language Processing : Explore Tools and Techniques to Analyze and Process Text with a View to Building Real-world NLP Applications. Packt Publishing.
• Rukmini, S. (2017). Academic Research Writing: An Overview and Process. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.7CED46CD

Recommended Additional Bibliography

• Hellmann, S. (2015). Integrating Natural Language Processing (NLP) and Language Resources Using Linked Data.
• I. Korotkina B., & И. Короткина Б. (2017). Academic Literacy and Methods of Global Scientific Communication ; Академическая грамотность и методы глобальной научной коммуникации. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.8C60FBE4

Authors

• BANNIKOV KONSTANTIN VALEREVICH
• Balakina Iuliia Vladimirovna
• Патракова Ева Павловна