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

2023/2024

Учебный год

ENG

Обучение ведется на английском языке

9

Кредиты

Кто читает:

Департамент фундаментальной и прикладной лингвистики

Статус:

Курс обязательный

Когда читается:

2-й курс, 2, 3 модуль

Преподаватели

Меркулова Эдита Николаевна

Сохраби Маджид

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
• Academic project (Master’s thesis)

Assessment Elements

• Homework
• Homework

Interim Assessment

• 2023/2024 3rd module
  0.8 * Homework + 0.2 * Homework

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