Digital Media and Data Science: An Analysis of User Behavior and Social Network in the Era of Information Technology

Course 20: Digital Media and Data Science: An Analysis of User Behavior and Social Network in the Era of Information Technology

I. Course Description

In recent years, with the continuous emergence of massive data gathered by platforms such as the Internet, mobile Internet and the Internet of Things, it has brought unprecedented opportunities for scientific research. For researchers and large enterprise managers, it is more urgent to understand how to make full use of massive information in the context of big data and extract valuable information from it. This increased demand has also spawned interdisciplinary disciplines in new media and computing.

This course focuses on social media data analysis, covering communication strategies, market research, and technology applications. Students will learn to reveal the patterns and trends by analyzing the raw data from platforms such as Facebook, Instagram, Twitter, TikTok, and YouTube. The course is divided into three parts: methods and challenges, data collection and analysis skills training, and actual case study. Students will master the R tool for data mining and social media analysis, and will critically think about the ethical application of social media data.

II. Professor Introduction

Manuel González Canché – Tenured professor at the University of Pennsylvania

Professor Manuel Gonzalez Canche works in the Higher Education Department of the University of Pennsylvania. He is also a joint mentor at the School of Human Development and Quantitative Methods and the International Education Development Program; a Senior Fellow in Higher Education.

Manuel Research has focused on pathways to underrepresented minority groups, education and immigration issues, social inequality, social psychology and cultural research, social networking and social capital and data visualization, particularly in understanding the structural factors influencing the likelihood of career success among minority and risk students. Manuel He won the University of Arizona Visiting Scholar Award for How Community Colleges Use Social Media to Improve Student Success, and is the author of Social Media in Higher Education: Literature Review and Research Direcentation.

III. Syllabus

1. What is social media data mining?
2. How does the data-mining technology work out?
3. Is social media data mining ethical?
4. How to judge the moral standards of the media?
5. How to use statistical technology to extract data from social media platforms?
6. Questions of collecting data from social media platforms
7. Explore the relevant research questions and hypotheses
8. 8 analyzed and plan study reports / case studies
9. Explore the application and challenges of data mining
10. Social Network Analysis in Social Media Data Mining (SNA)