Chris J. Vargo

Dr. Chris J. Vargo is an assistant professor specializing in data analytics and digital advertising. Chris employs the use of computer science methods to investigate social media data using theories from communication, psychology and political science. Research methods of specialization include: data mining, machine learning, computer-assisted content analysis, data scraping, APIs, investigative statistics, prescriptive and predictive analytics, data forecasting, network analysis, Python, information retrieval and computer automation. In the classroom, Chris currently teaches advertising analytics at two levels: to undergraduates (APRD4300) and in the Leeds School of Business Master's in Business Analytics marketing specialization (APRD 6342 & APRD 6343). He also directs the CMCI/Leeds Marketing and Business Analytics partnership for CMCI. His goal is to improve the quantitative analytical skills of CU graduates and to equip them with skill sets that are in industry demand. Notable journals Chris has published in include Journal of Communication, the Journal of Interactive Advertising, New Media & Society, Journalism & Mass Communication Quarterly, Mass Communication & Society and Social Science Computer Review. Chris has two research specializations: agenda-setting theory in new media landscapes and eWOM on social media. He currently serves as the Editor of The Agenda Setting Journal. Chris has three degrees in Advertising & Public Relations: a PhD from The University of North Carolina at Chapel Hill, an MA from The University of Alabama and a BA from The Pennsylvania State University. His background includes real-world public relations and digital marketing experience at Sony BMG Music, Porter Novelli and Fox/DreamWorks. In addition, Chris worked in the IT field for several years.

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Unsupervised Text Classification for Marketing Analytics (Coursera)

Marketing data is often so big that humans cannot read or analyze a representative sample of it to understand what insights might lie within. In this course, learners use unsupervised deep learning to train algorithms to extract topics and insights from text data. Learners walk through a conceptual overview [...]

Network Analysis for Marketing Analytics (Coursera)

Network analysis is a long-standing methodology used to understand the relationships between words and actors in the broader networks in which they exist. This course covers network analysis as it pertains to marketing data, specifically text datasets and social networks. Learners walk through a conceptual overview of network analysis [...]

Supervised Text Classification for Marketing Analytics (Coursera)

Marketing data often requires categorization or labeling. In today’s age, marketing data can also be very big, or larger than what humans can reasonably tackle. In this course, students learn how to use supervised deep learning to train algorithms to tackle text classification tasks. Students walk through a conceptual [...]

Native Advertising (Coursera)

Native advertising is a niche form of advertising that leverages the design and format of news and entertainment content. Native advertising is less about selling products and more about producing useful content for consumers who are in the ‘consideration’ phase of the advertising purchase funnel. Often in the form [...]

Search Advertising (Coursera)

Consumers search for virtually everything. This includes the things that small businesses do, from restaurants to bespoke products. When consumers search they get organic results along with paid results. Paid search ads are systematically designed to be relevant. As a result, they’re often useful at getting consumers where they [...]

Introduction to the Digital Advertising Landscape (Coursera)

The digital advertising landscape is complex. There are many different types of ads, including: display, video, audio, sponsored, native, social media and search. Consumer data and the ad tech that action on that data are both ubiquitous and complicated. As a result the sheer number of options available to [...]

Social Media Advertising (Coursera)

Social media platforms are driven by digital advertising. As a result, social media advertising is affordable and can be purchased at almost any budget. Targeting options in social media advertising are also sophisticated. It is possible to tailor ads around a user’s behaviors (e.g., likes, posts and clicks). This [...]