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The increasing importance and proliferation of text data provide a unique opportunity and novel lens to study human communication across a myriad of business and marketing applications. For example, consumers compare and review products online, individuals interact with their voice assistants to search, shop, and express their needs, investors seek to extract signals from firms' press releases to improve their investment decisions, and firms analyze sales call transcripts to increase customer satisfaction and conversions. However, extracting meaningful information from unstructured text data is a nontrivial task. In this chapter, we review established natural language processing (NLP) methods for traditional tasks (e.g., LDA for topic modeling and lexicons for sentiment analysis and writing style extraction) and provide an outlook into the future of NLP in marketing, covering recent embedding-based approaches, pretrained language models, and transfer learning for novel tasks such as automated text generation and multi-modal representation learning. These emerging approaches allow the field to improve its ability to perform certain tasks that we have been using for more than a decade (e.g., text classification). But more importantly, they unlock entirely new types of tasks that bring about novel research opportunities (e.g., text summarization, and generative question answering). We conclude with a roadmap and research agenda for promising NLP applications in marketing and provide supplementary code examples to help interested scholars to explore opportunities related to NLP in marketing.

To demonstrate how teacher candidate narratives in response to videos depicting science and literacy instruction can be used to both teach and evaluate beginning teachers’ emerging conceptions of disciplinary literacy.

Teacher candidates viewed and responded to videos depicting exemplary practice in science education and then videos of their own practice. Qualitative discourse analysis was used to investigate the science teacher candidates’ interpretations of problems of practice, their views of scientific literacy and understandings of their students.

The teacher candidates displayed distaste for textbooks, reinforced by negative experiences with textbooks in school settings, and yet they viewed textbooks as essential for effectively teaching knowledge about science. At the same time, each viewed the natural world as the ideal “text” for teaching knowledge about science, at times compensating for the weaknesses of textbooks and at other times entirely replacing textbooks as the source of knowledge about science. We consider what this means for preparing teachers for effective subject matter and literacy practice.

Video reflections like these demonstrate that what teacher candidates understand about video representations of others’ and their own teaching are far from literal and are interpreted through the educational and background lenses of the teacher candidates’ themselves. We suggest that a great deal more work needs to be done to better understand how to use video reflection to best develop teacher candidates’ conceptions of subject matter and literacy practice.

In this chapter, recent research applications in secondary content-area instruction for students with learning or behavioral disabilities are reviewed. Included are research studies in the areas of English, SAT vocabulary, world history, algebra, social studies, and chemistry. Generally, instructional strategies that have included strategy instruction, peer mediation, as well as mnemonics and other verbal elaborations, have been effective in substantially improving learning performance. Implications for practice and future research are discussed.

Drawing from the work of sociologist Niklas Luhmann, this paper analyzes and critiques the ways sociology presents itself as a vehicle for sociological “enlightenment.” It begins with a brief historical account of how sociology has come to describe itself as a science in the name of promoting social justice rooted back to the European Enlightenment of the eighteenth century. Next, the relevant elements of Luhmann's theory of society are explained ground the analysis. Luhmann's critiques of sociology and science are then presented to explain how a Luhmannian understanding of social systems exposes what is missing in sociology's current self-description of itself and its “enlightenment” mission. Building upon Luhmann's observations, a preliminary observational analysis of the communication techniques and technologies of sociology, such as classes, conferences, and publications, is assessed to evaluate the tools sociology uses to engage in communication and “irritate” other social systems. The central question here is, are these tools effective in communicating sociological knowledge in a way that aligns with the aspirational humanistic goals sociology seeks to achieve? The argument then concludes with some remarks about how sociology might potentially overcome its communicative efficacy problem if it takes seriously the insights from a Luhmannian approach to communication and considers alternative forms of communication to reach new audiences. In this way, sociology could perhaps overcome the gap between the facts of its communicational efficacy and its enlightenment norms.

Having considered various types of pedagogy as well as technology affordances and multimedia learning principles, this chapter focuses on issues surrounding the representation and sharing of content using technology. Anderson & Krathwohl’s (2001) Taxonomy of Learning, Teaching and Assessing is examined as a means of conceptualizing different types of thinking processes in a way that can be applied across discipline areas. The representational requirements of different subject areas (English, mathematics, science, history, geography, and computing) are explored by means of examples, with reference to the role of technology and the range of possible tasks that may be utilized. Assessment issues as they relate to the representation of content are also considered. The broader contextual shift toward open education and sharing is discussed, including key drivers such as learning object repositories, open educational resources, Creative Commons licensing, and massive open online courses.

In this paper, we aim to provide a comprehensive overview of customer feedback literature, highlighting the burgeoning role of artificial intelligence (AI). Customer feedback has long been a valuable source of customer insights for businesses and market researchers. While previously survey focused, customer feedback in the digital age has evolved to be rich, interactive, multimodal, and virtually real time. Such explosion in feedback content has also been accompanied by a rapid development of AI and machine learning technologies that enable firms to understand and take advantage of these high-velocity data sources. Yet, some of the challenges with traditional surveys remain, such as self-selection concerns of who chooses to participate and what attributes they give feedback on. In addition, these new feedback channels face other unique challenges like review manipulation and herding effects due to their public and democratic nature. Thus, while the AI toolkit has revolutionized the area of customer feedback, extracting meaningful insights requires complementing it with the appropriate social science toolkit. We begin by touching upon conventional customer feedback research and chart its evolution through the years as the nature of available data and analysis tools develop. We conclude by providing recommendations for future questions that remain to be explored in this field.

As the Web 2.0 induces changes in human relationships, several implications across issues and domains of socio-economic life follow; politics is one of them. In the context of Web 2.0, social media have established themselves as a part of citizen’s daily routine. Hence, social media have a direct impact on politics today. This chapter examines this phenomenon and its implications for politics by tracing and examining the recent initiative launched by Rede Globo aimed at collecting citizens’ views and visions on Brazil’s future. “The Brazil I Want” project sought to encourage citizens to publish videos featuring their visions and views of Brazil’s future. Thousands of citizens used this opportunity to express their concerns and hopes related to the future of their cities and their country. This chapter seeks to make sense of it in two ways. First, it explores to what extent and how social media can serve as source of information. Here the concepts and tools of big data and data mining are employed. Second, it inquiries into what people currently think about their country. By bringing these two research perspectives together, this chapter argues that effective ways of resolving issues and concerns the citizens thus voiced exist to the benefit of the efficiency of the policymaking process and the society’s wellbeing.

Reading comprehension is a critical area of instruction for all students, but particularly for students with learning disabilities (LD) that impede their ability to understand what they read. This synthesis includes 30 intervention studies on reading comprehension for students with LD conducted in several countries and all regions of the United States. Specifically, the current review focuses on the efficacy of these strategies across grade levels, with various types of reading materials, and in conjunction with other instructional components that have potential to enhance instructional benefits to students. Results suggest that reading comprehension instruction is effective for improving the skills of this population.