The online Master of Arts in Mass Communication with a specialization in Audience Analytics includes 39 credit hours: 36 hours of coursework plus three final credits in the capstone course. Program curriculum is guided by an Advisory Council of top industry experts, with courses taught by industry professionals and University of Florida faculty.
Students take two to three courses at a time, preparing for an exciting career in consumer and audience analytics; media, marketing, audience research; or consulting among the many in-demand areas that tap this skill set.
Unique Learning Experience
Statistics RequirementsStudents entering the Audience Analytics program should have successfully completed an introductory statistics course within the past five years. For those who have not met this requirement, students may still be admitted to the program but will need to complete an introductory statistics course by the beginning of the second semester in order to continue with the program. This course may be taken online at UF or another institution of higher learning, including community colleges. Online options to meet this requirement include the “Mass Communication Statistics” course (MMC 6936) offered most semesters within the College of Journalism and Communications.
A multivariate statistics course is also required during this program. The course may cover several multivariate methods, or one in depth, such as Analysis of Variance (ANOVA) or Multiple Regression. Students who can demonstrate successful completion of such a course may opt out with program director approval. Otherwise, students should complete a multivariate statistics course during the course of the program, but prior to the beginning of the fourth semester. As with the introductory statistics course, options to meet this requirement include most any multivariate statistics course offered by an institution of higher learning, including a community college. At this time, there are no known online versions of the course at UF. In this case, it is permissible to complete an online Coursera course currently offered by Duke University titled Linear Regression with Modeling (Course 3): https://www.coursera.org/specializations/statistics If using this option, you must select the “pay” option in order to receive (and present to UF) a certificate of completion.
Data Management and Ethics (1)
An overview of the nature of data and how to assess data quality. Course develops data literacy and addresses the ethical implications of data gathering and analysis, including identification of elements and processes that can compromise data quality. This course provides students with the tools to enable them to critically assess data integrity.
Data Mining and Analysis (3)
This course provides a survey of advanced business decision making using data analysis to garner business insights. This course will introduce students to basic data analysis and machine learning techniques used in many industries today to make intelligent data-driven decisions. Students will learn how to collect data, mine it for meaning, and utilize statistical methods and machine learning to gather useful information to determine what is significant and how to incorporate the learnings into next steps.
Data Storytelling and Visualization (4)
This course will cover the fundamentals of effective data-driven storytelling. Students will learn how to detect and articulate the stories behind data sets and communicate data findings in visual, oral, and written contexts for various audiences and publics. Students will become familiar with associated tools.
Research Methods in Digital Communications (3)
This course is designed to make you think strategically and theoretically about how, why and with whom you interact via digital media. By the end of the course you should have a fundamental understanding of research tools that will help you both plan for and evaluate the effectiveness of online communications methods including a multitude of social media and web tools. Specifically, you will develop a better understanding of the consequences – costs and benefits — of local and global messaging and interactivity.
Introduction to Programming with Data (3)
This course provides a hands-on overview of how to program for data analysis. With the help of Python, students will learn how to write code for easy collection, analysis and sharing of data. The course offers an introduction to programming best practices, while quickly getting started with practical data evaluation tasks like tabular reporting and data visualization techniques.
This course is the culmination of the Audience Analytics specialization and serves as the capstone course. Students will draw from all of their previous course work to analyze a consumer or audience problem or challenge for an assigned client, design a study proposal, execute the study utilizing appropriate methods, tools, and analyses, and produce a final report and presentation for the client. They will work one-on-one with their instructor to receive guidance at critical steps along the way. *Prereq: All core and methods courses.
MMC 6730: Social Media Management (3)
This course teaches students to use social media strategically to create value for their business, non-profit, or organization. An emphasis is placed on strategic collaboration, tactical execution and measurement of social media efforts. Students will learn by doing in assignments focused on The course will cover blog writing, Facebook, Twitter, LinkedIn, and an array of niche social media platforms.
MMC 6727: Social Media Metrics & Evaluation (3)
The success or failure of social media strategies are determined by the real-world impact of campaigns. Just as social media managers must tap their creative side to create engaging campaigns, they must also draw on their analytical side in considering meaningful, tangible data. Metrics are not merely important for judging campaign success and failure, they are also crucial for demonstrating to management the ROI of social media efforts. Students will learn by doing through collection and analysis of real social media campaign data. After completing the course students will be able to (1) describe the proper measurement mechanisms to employ, (2) identify the data points that help clarify campaign effectiveness (3) the proper approach for analyzing data, and (4) determine how the outcomes from data analysis should modify overall strategy. *Prereq: Intro to Statistics.
MMC 6936: Creative Storytelling (3)
Storytelling is an essential part of strategic communication, and digital technology and social media have expanded the power of “the story” in helping organizations persuade and influence key audiences. This course will instruct you how to harness the power of effective storytelling and apply storytelling techniques across multiple channels. It will review and examine the oral tradition, historical and cultural significance, and evolution of storytelling as well as the importance and relevance of storytelling in communication. You will learn and apply strategies and tools for creating effective print, digital and visual stories. We will explore best practical applications for implementing and disseminating stories across a variety of media to tap into and leverage the current and exciting communication landscape.
MMC 6936: Public Affairs Communication (3)
This course will provide an understanding of successful public affairs communication and campaign strategies on behalf of public affairs/policy organizations, nonprofits, corporations, governmental entities, trade associations, political candidates, and elected officials.
MMC 6726: Emerging Technology and Social Media (3)
This course studies the multiple uses for gamification, virtual reality, and virtual worlds. Cases related to successes, failures, and uses of these tools are analyzed with a special focus on cases pertaining to engagement, branding, and business. Students will research ethical and sociological issues associated with gamification, explore virtual worlds and mobile apps, and analyze the uses of gamification in a variety of contexts. Throughout the course, students will apply what they are learning so they may confidently leverage gamification in their professional lives.
Predictive Analytics (3)
Description forthcoming. *Prereq: Data Mining and Analysis.