Download Syllabus - Stevens Institute of Technology

Stevens Institute of Technology
Howe School of Technology Management
Syllabus
MGT 644/MIS 661
Online Marketing
Semester: 2014 Spring
Instructor Name & Contact Information:
Jie Ren
Office phone: 201-665-9633
Email: [email protected]
Day of Week/Time: Wednesday, 6:15pm to
8:45pm
Office Hours:
By Appointment
Class Website:
Moodle
Course Description
This course provides a basic understanding of social network theories and the way they are
applied in online marketing. 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. The specific topics include the representation of
networks and basic concepts of network theories, such as strength of weak ties, centrality,
clustering coefficient, small world network. These topics also include online marketing
techniques: such as email marketing, search engine optimization, social media marketing, etc.
Also students will be expected to conduct quantitative analysis of marketing data, such as MDS,
cluster analysis and opinion mining.
Course Objectives
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-ofmouth 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 develop better online marketing strategies.
Additional learning objectives include the development of:
Written and Oral Communications Skills: multiple individual homework assignments will be
used to assess writing skills and the final presentations will be used to assess presentation skills.
Teaming Skills: 60% of the deliverables for the course are team deliverables which require
students to work effectively in teams to accomplish the overall course objectives. A survey is
used to measure individual contributions to team performance.
Analytic problem solving skills: Students will use different methods of social network analysis to
analyze online data and they will interpret the results pertinent to how they solve a business
problem.
Ethical Understanding: Students will make a presentation about the ethical issues involved
with privacy and data collection on social media.
Course Outcomes
In general, after completing the course, students will be able to
1.
2.
3.
4.
Apply social network theories to enhance understanding of customer need.
Apply marketing theories to create online marketing strategies.
Analyze networks and online data using NodeXL and R
Conduct online marketing campaigns.
Pedagogy
The course will employ lectures, individual assignments, team presentation and project. Students
will engage in the following activities:
 Attend and participate in the weekly classes.
 Actively participate in the in-class discussions Read assigned material prior to the
indicated class lectures (if required).
 Prepare homework assignments in accordance with predefined guidelines.
 Work in teams and attempt to create an information cascade.
Moodle will be used as the primary course management tool. You will be automatically enrolled
in Moodle once you register for the course. All relevant class materials and class announcements
will be also posted on Moodle. Additionally, this course will use two free softwares for analysis
(see below).
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 Textbook
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)
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Additional & Optional Readings
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.
Course Components
The course will emphasize the various aspects of Online Marketing listed in the syllabus.
Class Participation - To enhance the learning experience, all students are expected to participate
in class discussions. You are expected to review the assigned readings and materials and be
prepared to explain your answers to the assigned materials.
Homework – Graded homework will be submitted via Moodle. Late homework submissions
will be subject to a 10% deduction.
Midterm paper - There will be a midterm group work that aims to analyze twitter data for
opinion mining. Students will be expected to give presentations and generate reports
Final project: - Students will work in teams to conduct online campaigns and present their
results and generate reports.
The scale for grades is: A >92; A- 92~90; B+ 89~85; B 84~80; B- 79~75; C+ 74~70; C 69~65;
C- 64~60; F<60
The components and their weights are as shown below:
Assignment
Class Participation
Assignments
Mid-Term Paper
Final paper
Total Grade
Grade Percent
10%
20%
20%
50%
100%
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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.“
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.
Reference:
The Graduate Student Handbook, Academic Year 2003-2004 Stevens
Institute of Technology, page 10.
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.
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Course Schedule
Week
1
Subjects
Course Overview
Reading Material / Homework Assignments / Exams
Install R & NodeXL
Watts, Chapter 1: The Connected Age
The representation of networks
2
Technique 1: Email Marketing
Wikipedia: Social Networks
Wikipedia: Graph Theory
Assignment: Adjacency Matrix
Watts, Chapter 2: The Origins of A "New" Science
3
Ties, Brokerage and Social
Capital
Technique 2: Online Advertising
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.
Watts, Chapter 3: Small Worlds
Preferential Attachment
4
Technique 3: Pay per Click
Advertising
Travers, J., and Milgram, S. “An Experimental Study of the Small World
Problem”, Sociometry 32(4, Dec. 1969): 425:443.
Wikipedia: Preferential Attachment
Watts, Chapter 4: Beyond The Small World.
Small-world Networks
5
Technique 4: Affiliate Marketing
Barabási, A.L., Albert, R. (1999). “Emergence of scaling in random
networks”. Science, 286, 509-512.
Wikipedia: Small World Networks
Assignment: Distance Matrix and MDS
Search in Networks
Watts, Chapter 5: Search in Networks.
6
Technique 5: Search Engine
Marketing/Optimization
Assignment: Cluster Analysis
Watts, Chapter 6: Epidemics and Failures
7
Diffusion, Reciprocity and
Homophily
Technique 6: Social Media
Wikipedia: Reciprocity
Wikipedia: Homophily
Watts, Chapter 7: Decisions, Delusions, and The Madness of Crowds
Crowdsourcing
8
Technique 7: Crowdsourcing
Ren, J. (2011) “Who's More Creative, Experts or The Crowd?” AMCIS.
Wikipedia: Crowdsourcing
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Week
Subjects
Reading Material / Homework Assignments / Exams
Mid-report due: Sentiment Analysis (Twitter, Amazon, etc)
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.
Social Influence
9
Technique 8: Viral Marketing
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.
Incentives and Motives
10
Technique 10: Web Design & Web
Analytics
Diffusion Networks
11
Technique 11: Mobile Marketing
Watts, Chapter 9: Innovation, Adaption and Recovery
Watts, Chapter 10: The End of the Beginning
Watts, Chapter 11: The World Gets Smaller
Consumer Behavior Online
Trust Online
Technique 12: Customer
Relationship Management
Why You Shouldn't Trust Internet Comments. Science Blog
13
Online Marketing Case Study
Cases in the book of Groundswell
14
Review
12
Final Project Presentations
15
Final paper due in one week
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