MIS-661: Marketing Online

Time: Wednesday 6:15 pm
Location: Babbio 122

Jie Ren, PhD Candidate
Howe School of Technology Management
Office: Babbio 625
Office hours: By appointment
Email: jren1@stevens.edu

Course Description

Nowadays, online marketing has become an influential vehicle of brand awareness and product purchases. In the electronically mediated social network, customers can take the role of word-of-mouth and do the marketing for companies. The key to make this happen is to understand this network and understand customer behavior in this network. Rooted in sociology, psychology and computer science, social network theories can help us make sense of the complicated phenomenon and make better online marketing strategies. This course will provide a basic understanding of social network theories and the way they are applied in online marketing.

In this course, students will develop this understanding from three aspects: (1) social network theories and marketing theories, (2) the techniques and best practices of online marketing, and (3) social network analysis. By the end of this course, students will be capable of analyzing networks and conducting their own online marketing campaigns. That is, students will be asked to actively work in teams and attempt to create an information cascade.

NodeXL: a free Excel template that works on PCs. For Mac users, you will need to acquire PC emulator software on the Mac to get the software to work.

R: a free software that works for both PCs and Macs. It is mainly for statistical analysis. Since there are many specialized network packages, students can use R as part of their projects.

Required and Suggested Texts
Main Texts:

  • Watts, D. J. (2004). Six degrees: The Science of A Connected Age.
  • Papers that are related to social networks (see the reading in the table)
  • Supporting Texts:

  • Van Den Bulte, C., and Wuyts, S. (2007). Social Networks and Marketing. Marketing Science Institute.
  • Hansen, D. L., Shneiderman, B., and Smith, M. A., (2009). Analyzing Social Media Networks with NodeXL, Morgan Kaufman.
  • Li, C., Benoff., J. (2011). Goundswell. Harvard Business Review Press.
  • Rogers, E. M., (2003). Diffusion of Innovations, Fifth Edition, Free Press.
  • Wikipedia entry reading: Viral Marketing, Graph Theory, Information Cascade, Social Network, Preferential Attachment, Reciprocity (Social Psychology), Homophily, Crowdsourcing, Social Media, Social Capital.
  • Grading
    Here is the breakdown for the grading purposes:

  • Attendance: 10%
  • Assignments: 20%
  • Midterm paper: 20%
  • Final paper: 50%
  • Ethical Conduct
    The following statement is printed in the Stevens Graduate Catalog and applies to all students taking Stevens courses, on and off campus.
    "Cheating during in-class tests or take-home examinations or homework is, of course, illegal and immoral. A Graduate Academic Evaluation Board exists to investigate academic improprieties, conduct hearings, and determine any necessary actions. The term 'academic impropriety' is meant to include, but is not limited to, cheating on homework, during in-class or take home examinations and plagiarism."

    Reference: The Graduate Student Handbook, Academic Year 2003-2004 Stevens Institute of Technology, page 10.

    Consequences of academic impropriety are severe, ranging from receiving an "F" in a course, to a warning from the Dean of the Graduate School, which becomes a part of the permanent student record, to expulsion.

    Consistent with the above statements, all homework exercises, tests and exams that are designated as individual assignments MUST contain the following signed statement before they can be accepted for grading:

    I pledge on my honor that I have not given or received any unauthorized assistance on this assignment/examination. I further pledge that I have not copied any material from a book, article, the Internet or any other source except where I have expressly cited the source. Signature __________ Date __________
    Please note that assignments in this class may be submitted to www.turnitin.com, a web-based anti-plagiarism system, for an evaluation of their originality.
    Course Schedule and Announcements
    Course schedule will be posted online (http://personal.stevens.edu/~jren1/MIS661/). Make sure to regularly consult the web page for an updated schedule.

    Week Topic Reading Assignment
    1 (August 28) Course Overview   Install R & NodeXL
    2 (September 4) The representation of networks
    Technique 1: Email Marketing
    Watts, Chapter 1: The Connected Age
    Wikipedia: Social Networks
    Wikipedia: Graph Theory
    Adjacency Matrix
    3 (September 11) Ties, Brokerage and Social Capital
    Technique 2: Online Advertising
    Watts, Chapter 2: The Origins of A "New" Science
    Granovetter, M. S. (1973). “The Strength of Weak Ties”. The American Journal of Sociology 78(6): 1360. Burt, R. S. (2001). “Structural holes versus network closure as social capital.” Social capital: Theory and research, 31-56.
    Degree Centrality
    Betweenness Centrality
    4 (September 18) Preferential Attachment
    Technique 3: Pay per Click Advertising
    Watts, Chapter 3: Small Worlds
    Travers, J., and Milgram, S. “An Experimental Study of the Small World Problem”, Sociometry 32(4, Dec. 1969): 425:443.
    Wikipedia: Preferential Attachment
    Small World Network
    Clustering Coefficient
    5 (September 25) Small-world Networks
    Technique 4: Affiliate Marketing
    Watts, Chapter 4: Beyond The Small World.
    Barabási, A.L., Albert, R. (1999). “Emergence of scaling in random networks”. Science, 286, 509-512.
    Wikipedia: Small World Networks
    Distance Matrix and MDS
    6 (October 2) Search in Networks
    Technique 5: Search Engine Marketing/Optimization
    Watts, Chapter 5: Search in Networks. Cluster Analysis
    7 (October 9) Diffusion, Reciprocity and Homophily
    Technique 6: Social Media
    Watts, Chapter 6: Epidemics and Failures
    Wikipedia: Reciprocity
    Wikipedia: Homophily
    Sentiment Analysis (Twitter, Amazon, etc)
    8 (October 16) Crowdsourcing
    Technique 7: Crowdsourcing
    Watts, Chapter 7: Decisions, Delusions, and The Madness of Crowds
    Ren, J. (2011) “Who's More Creative, Experts or The Crowd?” AMCIS.
    Wikipedia: Crowdsourcing
    Mechanical Turk
    9 (October 23) Social Influence
    Technique 8: Viral Marketing
    Watts, Chapter 8: Thresholds, Cascades and Predictability
    Watts, D. J., and Dodds, P. S. (2007). “Influentials, networks, and public opinion formation”. Journal of Consumer Research, 34, 441-458.
    Watts, D. J., Peretti J., and Frumin, M (2007). “Viral marketing for the real world”. Harvard Business Review. 85 (5).
    Aral, S., Walker, D. (2012). “Identifying influential and susceptible members of social networks”. Science, 337(6092), 337-341.
    Bitly & QR code
    10 (October 30) Incentives and Motives
    Technique 10: Web Design & Web Analytics
    Watts, Chapter 9: Innovation, Adaption and Recovery Web Scraping
    11 (November 6) Diffusion Networks
    Technique 11: Mobile Marketing
    Watts, Chapter 10: The End of the Beginning
    Watts, Chapter 11: The World Gets Smaller
    12 (November 13) Consumer Behavior Online
    Technique 12: Customer Relationship Management
    Trust Online
    Why You Shouldn't Trust Internet Comments. Science Blog
    13 (November 20) No class    
    14 (November 27) Review    
    15 (December 4) Final Project Presentations
    Final paper due in one week