Climate change is one of the key societal challenges of our times, and its debate takes place across scientific disciplines and into the public realm, traversing platforms, sources, and fields of study. The analysis of such mediated debates has a strong tradition, which started in communication science and has since then been applied across a wide range of academic disciplines.So-called ‘content analysis’ provides a means to study (mass) media content in many media shapes and formats to retrieve signs of the zeitgeist, such as cultural phenomena, representation of certain groups, and the resonance of political viewpoints. In the era of big data and digital culture, in which websites and social media platforms produce massive amounts of content and network this through hyperlinks and social media buttons, content analysis needs to become adaptive to the many ways in which digital platforms and engines handle content.This book introduces Networked Content Analysis as a digital research approach, which offers ways forward for students and researchers who want to work with digital methods and tools to study online content. Besides providing a thorough theoretical framework, the book demonstrates new tools and methods for research through case studies that study the climate change debate with search engines, Twitter, and the encyclopedia project of Wikipedia.
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Growing research in sign language recognition, generation, and translation AI has been accompanied by calls for ethical development of such technologies. While these works are crucial to helping individual researchers do better, there is a notable lack of discussion of systemic biases or analysis of rhetoric that shape the research questions and methods in the field, especially as it remains dominated by hearing non-signing researchers. Therefore, we conduct a systematic review of 101 recent papers in sign language AI. Our analysis identifies significant biases in the current state of sign language AI research, including an overfocus on addressing perceived communication barriers, a lack of use of representative datasets, use of annotations lacking linguistic foundations, and development of methods that build on flawed models. We take the position that the field lacks meaningful input from Deaf stakeholders, and is instead driven by what decisions are the most convenient or perceived as important to hearing researchers. We end with a call to action: the field must make space for Deaf researchers to lead the conversation in sign language AI.
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In this paper I describe the ways in which the communication discipline can make a hidden crisis transparent. For this purpose I examine the concept of crisis entrepreneurship from a communication point of view. Using discourse analysis, I analyse the discursive practices of crisis entrepreneurs in the domain of education in the Netherlands. This paper is part of my Ph.D. project in which I examine the dilemmas encountered by crisis entrepreneurs and the interactional solutions they choose in addressing a crisis. In my Ph.D. project I have analysed how crisis entrepreneurs use discursive practices: (1) to show the factuality of the problem. For example, the way the problem is presented is too theoretical and is not a problem in reality; (2) to present the credibility of the messenger as an authentic, legitimate spokesman. Crisis entrepreneurs may be accused of wanting to attract attention to their own cause; (3) to create the accountability for the problem and the solution. For example, crisis entrepreneurs can be accused of nursing personal grievances or of drawing attention to the issue without actively attempting to solve it. The conclusion is that a communication professional is able to recognize a problem raised by crisis entrepreneurs. Knowledge of interactional dilemmas helps communication professionals understand the potential of crisis entrepreneurs.
