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About Study Course

Credit points / ECTS:2 / 3
Course supervisor:Anda Rožukalne
Study type:Part time, Full time
Course level:Bachelor
Target audience:Marketing and Advertising; Information and Communication Science; Communication Science
Language:Latvian
Branch of science:Communication Sciences; Communication Theory

Objective

The content and structure of the course was created with the aim of promoting understanding of the use of artificial intelligence-based language technologies in media audience research.
The aim of the course is to introduce students to the interaction processes of media, public relations messages and advertising audience communication, promoting the necessary competences in modern media audience research related to the selection and structuring of media audience data, the use of AI-based applications, language technology solutions in media audience research and research results use within professional activity.
The course is based on a critical evaluation of the theoretical approaches of media audiences and media effects, using the theory of media use and gratification among various approaches in depth, which explains the regularities of media use and audience behavior.
During the course, the understanding of audience formation and transformation in the digital environment, its behavior under the influence of social networking platforms, the concept of mass audience will be studied, the course examines audience research methods and approaches, with the help of which journalistic, public relations and advertising communications (including digital communications) can be clarified. efficiency and impact factors, with a special focus on the use of AI-based tools and the development of language technologies for understanding media audiences.
The course offers a broad analysis of the processes of the modern communication environment, evaluating traditional media, social media, the influence of algorithms, commercial and socially relevant information from the audience's point of view.

Prerequisites

The course “Introduction to studies and speciality” has been mastered.

Learning outcomes

Knowledge

As a result of successful completion of the study course, students:
• Will describe the nature of media and social media audience, typology, theoretical approaches of analysis.
• Will tell and describe the historical factors of media audience formation and modern development processes.
• Will understand the interaction between media functions, media content and audience.
• Will present the goals and methods of media audience research in various fields of communication.
• Will present the use of language technologies in audience research, explaining the possibilities of AI-based tools (Internet aggressiveness index; Saeima discussion corpus; Audiense, BrandMentions, Determ, MeltWater, SIMILARWEB, Hootsuite, Talkwalker, Keyhole, Digimind, Mention, Exolyt, Youscan, etc.).
• Will understand the concepts of media audience activity and passivity, interactivity, its goals, functions and effects.

Skills

As a result of successful completion of the study course, students:
• Using data search, selection and structuring and analysis capabilities, will assess and analyze media audience types.
• Distinguish and apply media audience research methods, tools, AI-based tools (Internet aggressiveness index; Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan, etc.).
• Will distinguish and evaluate the behavior of multimedia audiences.
• Differentiate levels of interactivity and functions in multimedia communication.
• Will analyze media audience studies and research approaches, use of AI tools (Internet Aggressiveness Index; Audiense, BrandMentions, Determ, MeltWater, SIMILARWEB, Hootsuite, Talkwalker, Keyhole, Digimind, Mention, Exolyt, Youscan, etc.) and language technologies.
• Will analyze and process the data set with the aim of preparing it for the training of the artificial intelligence solution.
• Will interpret media usage habits and their causes using various AI tools (Internet Aggressiveness Index; Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan, etc.) options.
• Skills will integrate modern audience understanding in the multimedia communication process.
• Will collect and analyze the possibilities of using audience research methods and AI-based applications (Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan, etc.) for solving extraordinary media audience and media interaction problems (testing of new media formats and content products, evaluation of effectiveness , offering creative solutions, etc.).
• Will apply language technology and AI-based media audience analysis tools (Internet aggressiveness index; Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan, etc.) and methods to solve problems related to the interaction of various factors (content creation and management, its frequency, audience perception, predictable and unpredictable impact factors of use, short-term and long-term effects, etc.)
• Will create and be able to offer research formats, methods and AI-based tools for complex (fragmented, individually oriented, hard to reach, specific niche users) media audience groups (Internet aggressiveness index; Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan etc.) using the capabilities of language technologies.
• Will search, identify, select and analyze structured and unstructured audience data in order to offer a solution to media audience-related problems and an AI-based tool (Internet Aggressiveness Index; Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan) within the framework of professional goals etc.) use and development (explaining the audience's media use functions, evaluating the audience's attention, identifying new factors of activity and passivity, etc.).
• Using language technology solutions, will be able to create audience data analysis application performance tasks when developing a bachelor's or master's thesis.

Competence

As a result of successful completion of the study course, students will have obtained:
• Competence to search, select, collect and analyze primary and secondary audience data, applying the information to media audience assessment and generating new audience analysis ideas to achieve various communication goals.
• Competence to generate ideas for media audience monitoring and analysis solutions using AI-based tools (Internet Aggressiveness Index; Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan, etc.) opportunities, including preparing and testing language technology tools training material (Internet aggressiveness index, emotion detection model, etc.).
• Using the acquired knowledge and skills, will be able to develop competence in various sectors of professional activity, educating and managing the media audience of data acquisition, selection, structuring, analysis and AI-based tools Internet Aggressiveness Index; Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan, etc.) usage processes.
• Responsibility for the quality of the information collected and provided for media audience assessment, the value and relevance of information sources, as well as its potential effects, using various audience assessment data and methods, including commercial and non-commercial AI-based tools Internet Aggressiveness Index; Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan, etc.).
• Critical and creative attitude towards media audience research methods, content and form, including AI-based media audience research tools (Internet aggressiveness index; Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan, etc.).
• Self-critical attitude towards media audience data and the value of information analyzed with AI tools (Internet aggressiveness index; Audiense, BrandMentions, MeltWater, SIMILARWEB, Digimind, Mention, Exolyt, Youscan, etc.) and its relevance to communication goals.
• Responsible application of knowledge-based technologies in the process of evaluating and reaching media audiences.

Study course planning

Planning period:Year 2024, Autumn semester
Study programmeStudy semesterProgram levelStudy course categoryLecturersSchedule
Multimedia Communication, MKN1Bachelor’sRequiredAnda Rožukalne, Gunta Līdaka, Dite Liepa, Lāsma Šķestere
Multimedia Communication, MK1Bachelor’sRequiredAnda Rožukalne, Dite Liepa, Gunta Līdaka
Public Relations, SA1Bachelor’sRequiredAnda Rožukalne, Dite Liepa, Gunta Līdaka
Journalism, ZR1Bachelor’sRequiredAnda Rožukalne, Dite Liepa, Gunta Līdaka