{"product_id":"revealing-media-bias-in-news-articles-nlp-techniques-for-automated-frame-analysis-9783031176951","title":"Revealing Media Bias in News Articles: NLP Techniques for Automated Frame Analysis","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eThis open-access book employs an interdisciplinary approach, person-oriented framing analysis, to identify biases in English news articles reporting on a political event. It identifies different perspectives on the event by assessing how articles portray the persons involved. The book discusses manual analysis concepts and automated approaches from social sciences and computer science, highlighting their strengths and weaknesses. It introduces person-oriented framing analysis (PFA), a new approach to identify substantial frames and reveal slanted news coverage. The thesis includes a large-scale dataset and a novel model for target-dependent sentiment classification. Newsalyze, a prototype system, aims to reveal biases to non-expert news consumers. The book primarily targets researchers and graduate students interested in understanding and tackling media bias from an interdisciplinary perspective. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 238 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 26 February 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer International Publishing AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThis open-access 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 coverages 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.\u003cbr\u003e\u003cbr\u003eThe 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), a new approach to identify substantial frames and to reveal slanted news coverage. Chapters 4 and 5 detail target concept analysis and frame identification, the first and second component of PFA. Chapter 5 also introduces the first large-scale dataset and a novel model for target-dependent sentiment classification (TSC) in the news domain. Eventually, Chapter 6 introduces Newsalyze, a prototype system to reveal biases to non-expert news consumers by using the PFA approach. In the end, Chapter 7 summarizes the thesis and discusses the strengths and weaknesses of the thesis to derive ideas for future research on media bias.\u003cbr\u003e\u003cbr\u003eThis book mainly targets non-experts in the news industry who want to understand how media bias affects their understanding of political events. It also provides insights for journalists and media professionals who want to improve their reporting and avoid biased coverage. The book is written in a clear and accessible style, with examples and illustrations to help explain complex concepts.\u003cbr\u003e\u003cbr\u003eOverall, this book is a valuable resource for anyone interested in understanding the impact of media bias on political discourse and the importance of unbiased reporting.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 391g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031176951\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2023\u003c\/p\u003e","brand":"Felix Hamborg","offers":[{"title":"Paperback \/ softback","offer_id":44270936752378,"sku":"9783031176951","price":29.88,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_178f6f5b-d65f-40bf-a8ee-49072e9c2452.jpg?v=1686154278","url":"https:\/\/shulphink.com\/products\/revealing-media-bias-in-news-articles-nlp-techniques-for-automated-frame-analysis-9783031176951","provider":"Shulph Ink","version":"1.0","type":"link"}