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Название: Revealing Media Bias in News Articles: NLP Techniques for Automated Frame Analysis
Автор: Felix Hamborg
Издательство: Springer
Год: 2023
Страниц: 245
Язык: английский
Формат: pdf (true), epub
Размер: 30.5 MB
This book presents an interdisciplinary approach to reveal biases in English news articles reporting on a given political event. The approach named person-oriented framing analysis identifies the coverage’s different perspectives on the event by assessing how articles portray the persons involved in the event. In contrast to prior automated approaches, the identified frames are more meaningful and substantially present in person-oriented news coverage. The book is structured in seven chapters: Chapter 1 presents a few of the severe problems caused by slanted news coverage and identifies the research gap that motivated the research described in this thesis. Chapter 2 discusses manual analysis concepts and exemplary studies from the social sciences and automated approaches, mostly from computer science and computational linguistics, to analyze and reveal media bias. This way, it identifies the strengths and weaknesses of current approaches for identifying and revealing media bias. Chapter 3 discusses the solution design space to address the identified research gap and introduces person-oriented framing analysis (PFA). Crawling news websites can be achieved using many web crawling frameworks, such as scrapy for Python. Such frameworks traverse the links of websites, hence need to be tailored to the specific use case. Extracting information from news articles is required to convert the raw data that the crawler retrieves into a format that is suitable for further analysis tasks, such as Natural Language Processing.
Автор: Felix Hamborg
Издательство: Springer
Год: 2023
Страниц: 245
Язык: английский
Формат: pdf (true), epub
Размер: 30.5 MB
This book presents an interdisciplinary approach to reveal biases in English news articles reporting on a given political event. The approach named person-oriented framing analysis identifies the coverage’s different perspectives on the event by assessing how articles portray the persons involved in the event. In contrast to prior automated approaches, the identified frames are more meaningful and substantially present in person-oriented news coverage. The book is structured in seven chapters: Chapter 1 presents a few of the severe problems caused by slanted news coverage and identifies the research gap that motivated the research described in this thesis. Chapter 2 discusses manual analysis concepts and exemplary studies from the social sciences and automated approaches, mostly from computer science and computational linguistics, to analyze and reveal media bias. This way, it identifies the strengths and weaknesses of current approaches for identifying and revealing media bias. Chapter 3 discusses the solution design space to address the identified research gap and introduces person-oriented framing analysis (PFA). Crawling news websites can be achieved using many web crawling frameworks, such as scrapy for Python. Such frameworks traverse the links of websites, hence need to be tailored to the specific use case. Extracting information from news articles is required to convert the raw data that the crawler retrieves into a format that is suitable for further analysis tasks, such as Natural Language Processing.