COMM 670 / MLIS 502 SOCIAL NETWORKS
Rutgers, The State University
of New Jersey
Fall 2012
Mon 6:20-9:00pm (CI 337)
Prof. Keith Hampton
Course website: http://ecollege.rutgers.edu
DESCRIPTION
Social
networks is the description of a diverse body of theory and empirical study based
upon the premise that relationships,
in contrast to individual attributes,
are useful for understanding social structure and social behavior. Network
analysts study the structure of these relations, how the patterns of social
interactions allocate resources, constrain behavior, and channel information
and social change. Their methods can be quantitative or qualitative.
This course is a
non-mathematical introduction to social network analysis. It is an introduction
to the fundamental concepts related to the theory and measurement of social
structure, including: network size, diversity, centrality, homophily, multiplexity,
frequency of contact, tie duration, and tie strength. We
will consider how using a network perspective can help to conceptualize and
clarify many different types of important sociological questions and offer new
ways of answering those questions. The course will show how attending to the
organization of social relationships can increase our understanding of various
aspects of individual, community, and organizational life, such as health,
social support, job attainment, and the spread of information. Particular
attention is given to the role of communications media and the role of new
technologies in the maintenance and formation of social networks. The topic of
“social capital” – the resources that people may access through their social
contacts – will also be a central focus of the course. What are the costs and
benefits of different kinds of network structure for people and for groups? We will constantly
ask how and why various forms of personal social capital are unequally distributed,
and how this contributes to social mobility, the reproduction of inequality,
and democratic participation.
PREREQUISITS
PhD
students: no prerequisites.
MCIS
students: no prerequisites.
LEARNING OBJECTIVES
At
the end of the course students will be able to critically review the theory,
methodology, and findings of a research study that uses social network
analysis; describe the history of studies on social networks; and determine and
apply appropriate network theory and methodologies to a research question in
their area of study.
ASSIGNMENTS, ATTENDANCE
AND ASSESSMENT
A major component of the
course will involve the development and use of a personal blog. Students will
receive access to the necessary blogging software and will be provided with
basic instruction on how to maintain a blog. Students are not expected to have
prior experience with blogs.
Final grades will be based on
an evaluation of 10 blog postings on the subject of the weekly course readings
(20%), 20 comments on other students’ blog postings (10%), a presentation
outlining the final project (10%), class participation (10%), and a final
project (50%). Students are urged to pay close attention to due dates, late
assignments will not be graded.
Final grades will be assigned
according to the following scale:
A: 90-100%
B+ 85-89%
B 80-84%
C+ 75-79%
C 70-74%
D 60-69%
F below 60%
Course readings,
attendance, and participation:
Students are expected to have read the week’s readings in advance of the course
meeting. Class meetings will be in a seminar format and students should be
prepared to participate in a discussion based on the topic and readings of the
week. Use of mobile phones and computing devices in class, for purposes
unrelated to note taking and direct class participation, will adversely affect
your grade. Students are expected to attend all classes; if you expect to miss
one or two classes, please use the University absence reporting website – https://sims.rutgers.edu/ssra/ – to
indicate the date and reason for your absence. An email will automatically be
sent to the instructor from this system. Note that if you miss classes for
longer than one week, you should contact a dean of students to help verify your
circumstances.
Blog Postings: Students are responsible for submitting short
commentaries on 10 of the weeks’ readings (600-750 words). Commentaries should focus
on a minimum of 4 of the readings from each week and should consist of
limited summary; focusing on an evaluation of the readings and
identifying 2-3 questions for discussion during the class meeting (focus
on the papers’ key issues, strengths and limitations, and a comparison to
previous weeks’ readings). Each commentary must be submitted as a post to
the student’s personal class blog by 5:00pm on the Friday before the class
meeting.
Blog Comments: Each student is responsible for contributing
comments to fellow students’ blogs. Comments should be a minimum of 200 words
and offer a critique of that week’s posting, seek clarification, compare or
contrast postings, or provide additional evidence or new information (such as a
link to a related article, website, etc.). Each student must contribute a
minimum of 20 comments, credit will be given for a maximum of two comments each
week, students cannot comment on the same blog more than three times over
the duration of the course. Comments must be posted by 10:00am on the
day of class for posts related to that week’s readings.
Participation: To encourage active participation all seminar
members will take turns introducing the day's readings and facilitating the
discussion at different times during the semester. At the beginning of each
week’s session discussion leaders will briefly evaluate the readings and
suggest possible questions for discussion.
Presentation:
The in-class presentation is as an opportunity for students to explore
individual interests and to make a preliminary presentation of their final
project. Student’s presentations should be 10 minutes long, use PowerPoint, and
follow the format of a formal conference presentation. Presentations of papers
or proposals should include the following elements:
-Identification of the key problem.
-Research
question(s).
-Three citations of key research in the area.
-Research
methods and procedure.
-Main strengths and weaknesses of your methods.
Final Project: The final project can take on one of a number of
different forms to be negotiated individually with the instructor. Projects
should deal with course themes focusing on a topic of interest to the student.
Possibilities for the final paper/project include a full research proposal,
software or a website, or a paper of near publishable quality based on the
analysis of existing data or data collected as part of an original research
project (20-25 double spaced pages).
The consequences of
scholastic dishonesty are very serious. Evidence of plagiarism, cheating,
fabrication, facilitation of dishonesty, academic sabotage, criminal activity,
or other violations of research or professional ethics will be dealt with
severely – at a minimum the student will receive an F in the course. Rutgers
academic integrity policy is at http://academicintegrity.rutgers.edu.
COURSE MATERIALS
All
readings, files, and grades will be available from the course website: http://ecollege.rutgers.edu.
Optional
Klinenberg, Eric (2012). Going Solo: The Extraordinary Rise and Surprising Appeal of Living
Alone. New York: Penguin.
Rainie, Lee and Barry Wellman (2012). Networked: The New Social Operating System. Cambridge, MA: MIT Press
Wasserman, Stanley, and
Katherine Faust. (1994). Social
Network Analysis: Methods and Applications. New York: Cambridge University
Press.
UCINET: Social Network
Analysis Software.
Available from Software Anywhere
(Citrix).
NodeXL: Social Network Visualization Software
Free download, requires Excel: http://www.codeplex.com/NodeXL (available
in SC&I labs).
Subscribe to Socnet, the e-mail
list of the International Network for Social Network Analysis (INSNA). Send
email to listserv@lists.ufl.edu with the following information in
the body of the message (leave the
Subject line blank): subscribe SOCNET <yourfirstname>
<yourlastname>
OTHER INFORMATION
Students seeking help with
the content of this course should contact the instructor either during office
hours, or make a separate appointment. When seeking advisement and support,
email is no substitute for an in person meeting with the instructor. Students
should plan ahead and consult with the instructor in advance of any due dates.
Do not expect a detailed response by email to requests for advice or review of
materials – contact the instructor for a scheduled in person meeting, or if you
feel comfortable bring up your issue at the start of the class meeting.
COURSE OUTLINE
Week 1 (September 10) - Introduction and Organization
Week 2 (September 17) – What is Social Network
Analysis?
Borgatti, S. P., Mehra, A., Brass, D. J., & Labianca,
G. (2009). Network Analysis in the Social Sciences. Science, 323(5916), 892-895
Marin,
Alexandra, and Barry Wellman (2010). Social Network Analysis: An
Introduction. Pp. 11-25 in Handbook of
Social Network Analysis, edited by Peter Carrington and John Scott: Sage.
Monge, Peter and Noshir Contractor. (2003). Theories of Communication Networks.
Wellman, Barry. (1999). The Network Community: An Introduction. Pp.
1-48 in Networks in the Global Village,
edited by Barry Wellman.
Freeman, L. C. (2000).
See you in the Funny Papers: Cartoons and Social Networks. Connections, 23(1),
32-42.
Week 3 (September 24) – Strong Ties
Bott, Elizabeth. (1955). Urban Families: Conjugal Roles and Social
Networks. Human Relations 8:345-83.
Fischer, Claude. (1982). To Dwell Among Friends.
Wellman, Barry, and Scot Wortley.
(1990). Different Strokes from Different Folks: Community Ties and Social
Support. American Journal of Sociology 96(3):558-88.
McPherson, M., Smith-Lovin, L.,
& Brashears, M. E. (2006).
Social Isolation in America: Changes in Core Discussion Networks over Two Decades.
American Sociological Review, 71, 353-375.
Kalmijn,
M. (2003). Shared
Friendship Networks and the Life Course. Social Networks, 25,
231-249.
Klofstad, C., Sokhey, A,. & McClurg
S. (in press). Disagreeing About Disagreement: How
Conflict in Social Networks Affects Political Behavior. American Journal of Political
Science.
Week 4 (October
1) – Weak Ties / Social Capital
Granovetter, Mark. (1973). The Strength of Weak Ties. American Journal of Sociology 78(6): 1360-1380.
Burt, Ronald. (1993). The
Social Structure of Competition. Pp. 65-103 in Explorations in Economic Sociology,
edited by Richard Swedberg.
Lin, Nan. 2001. Building a Network Theory of Social
Capital. Pp. 3-29 in Social Capital:
Theory and Research, edited by Nan Lin, Karen Cook, and Ronald Burt.
Burt, Ronald. 2001. Structural Holes versus Network
Closure as Social Capital. Pp. 31-56 in Social
Capital: Theory and Research, edited by Nan Lin, Karen Cook, and Ronald
Burt.
Cote, Rochelle and Bonnie Erickson
(2009). Untangling
the Roots of Tolerance. American
Behavioral Scientist 52(12): 1664-1689.
Week 5 (October 8) – Network Size and Homophily.
McPherson, Miller, Lynn Smith-Lovin
and James Cook. (2001). Birds of a
Feather: Homophily in Social Networks. Annual
Review of Sociology 27: 415-444.
Kossinets, Gueorgi, and Duncan Watts. (2009).
Origins of Homophily in an Evolving Social Network. American Journal of Sociology 115(2): 405-450.
Goel, S., Mason, W., & Watts, D. J. (2010). Real and Perceived Attitude Agreement in Social Networks. Journal of Personality and Social Psychology
99(4), 611-621.
Hill,
R. A., & Dunbar, R. I. M. (2003).
Social Network Size in Humans. Human Nature, 14(1),
53-72.
Killworth, Peter, Eugene Johnsen, H
Russell Bernard, Gene Ann Shelley, and Christopher McCarthy. 1990. Estimating the Size of Personal Networks. Social Networks 12: 289-312.
McCarty, C., Killworth, P. D., Bernard, H. R., Johnsen,
E. C., & Shelley, G. A. (2001). Comparing Two Methods for
Estimating Network Size. Human Organization
60(1), 28-39.
McCormick,
T. H., Salganik, M. J., & Zheng, T. (2010). How Many People do You Know?:
Efficiently Estimating Personal Network Size. Journal of the American
Statistical Association, 105(489), 59-70.
Week 6 (October 15) – Small World and Scale Free
Networks
Milgram, Stanley. (1967). The
Small-World Problem. Psychology Today 1:62-67
Gladwell,
M. (1999). Six Degrees of Lois Weisberg. The New Yorker 74(41): 52-64.
Kilworth, Peter, Christopher McCarthy,
Russell Bernard and Mark House. (2006).
The Accuracy of Small World Chains in Social Networks.
Social Networks 28(1): 85-96.
Watts,
Barabasi, Albert-Laszlo and Eric Bonabeau. (2003). Scale-Free Networks. Scientific American 288(5).
Bonacich, Phillip. (2004). The
Invasion of the Physicists. Social
Networks 26(3): 285-288.
Uzzi, B., & Spiro, J. (2005). Collaboration and Creativity: The Small World Problem. American Journal of Sociology, 111(2),
447-504
Week 7 (October 22) – Measurement
Zwijze-Koning, K., & Jong, M. D. T. D. (2005). Auditing Information Structures in
Organizations. Organizational Research Methods, 8(4), 429-453.
Marin, Alexandra & Keith Hampton
(2007). Simplifying the Personal
Network Name Generator: Alternatives to Traditional Multiple and Single Name
Generators. Field Methods 19(2),
163-193.
Bearman, P., & Parigi,
P. (2004). Cloning
Headless Frogs and Other Important Matters. Social Forces, 83(2), 535-557
van der Gaag, Martin, Tom .A.B.
Snijders, and Henk Flap
(2008). Position Generator Measures and Their Relationship to
Other Capital Measures. Pp 27-48 in Social
Capital: An International Research Program, edited by Nan Lin and Bonnie
Erickson: Oxford, UK: Oxford.
Fu, Yang-chih (2008). Position
Generator and Actual Networks in Everyday Life: An Evaluation with Contact
Diary. Pp 49-64 in Social Capital: An
International Research Program, edited by Nan Lin and Bonnie Erickson:
Oxford, UK: Oxford.
McCarty, Christopher, Molina, Jose
Luis, Aguilar, Claudia, & Rota, Laura (2007). A Comparison of Social Network
Mapping and Personal Network Visualization. Field Methods 19(2): 145-162.
Week 8 (October 29) – Centrality
Freeman, Linton. (1979). Centrality in Social
Networks: Conceptual Clarification. Social
Networks 1: 215-39.
Gould, R. V. (1989). Power and
Social Structure in Community Elites. Social Forces, 68(2), 531-552.
Faris, R., & Felmlee,
D. (2011). Status Struggles. American Sociological Review, 76(1),
48-73.
Borgatti, Stephen. (2005). Centrality and Network Flow. Social Networks 27(1): 55-71.
Park, Han Woo, and Loet Leydesdorff (2009).
Knowledge Linking Structures in Communication Studies Using Citation Analysis Among Communication Journals. Scientometrics 81(1): 157-175.
Week 9 (November 5) – Social Ecology / Network Effects
Sampson, Robert. (2006). Collective Efficacy Theory:
Lessons Learned and Directions for Future Inquiry. Pp
149-168 in Taking Stock: The Status of
Criminological Theory, edited by Francis T. Cullen, John Paul Wright, and
Kristie R. Blevins.
Bearman, P. S. (1991). Desertion as Localism: Army Unit
Solidarity and Group Norms in the U.S. Civil War. Social Forces 70(2), 321-342
McFarland,
D., & Pals, H. (2005). Motives
and Contexts of Identity Change: A Case for Network Effects. Social Psychology Quarterly, 68(4),
289-315
Smilde, David (2005). A Qualitative Comparative Analysis of
Conversion to Venezuelan Evangelicalism: How Networks Matter. American Journal of Sociology 111(3),
757-796.
Feld,
S. & Carter, W. (1998). When Desegregation Reduces Interracial Contact: A Class Size
Paradox for Weak Ties. American
Journal of Sociology 103(5), 1165-1186
Bahns, A. J., Pickett, K. M., & Crandall, C. S. (2012). Social Ecology of Similarity.
Group Processes & Intergroup
Relations, 15(1), 119-131
Makse, Todd, Scott Minkoff and
Edward Sokhey (2012). Spatial Processes, Network Dynamics
and the Use of Spatial Sampling Frames. Working Paper.
Week
10 (November 12) – Presentations.
Week 11 (November
19) – Presentations / Computer Networks as Social Networks I
Rainie, Lee and Barry Wellman
(2012). Networked: The New Social Operating System.
Cambridge, MA: MIT Press [Chapters 1 & 2].
Haythornthwaite, C. (2005). Social
Networks and Internet Connectivity Effects. Information, Communication & Society, 8(2), 125 – 147
Markus, Lynne (1987). Toward a
‘Critical Mass’ Theory of Interactive Media: Universal Access, Interdependences
and Diffusion. Communication
Research 14(5): 491-511.
Steinfield, Charles, Nicole B Ellison, and
Cliff Lampe. (2008).
Social Capital, Self-esteem, and use of Online Social Network Sites. Journal of Applied Developmental Psychology
29:434-445.
Backstrom, Lars, Jonathan Chang, Cameron
Marlow, and Itamar Rosenn
(2009). “How Diverse is Facebook?”
Palo Alto: Facebook.
Ugander, J., Karrer, B., Backstrom, L., & Marlow, C. (2011). The Anatomy of the Facebook Social
Graph. Arxiv preprint arXiv:1111.4503.
Week 12 (November 26) – Computer Networks as Social Networks II
Hampton, K. N., Sessions, L., & Ja
Her, E. (2011). Core Networks, Social Isolation, and New Media: Internet and
Mobile Phone Use, Network Size, and Diversity. Information, Communication & Society, 14(1), 130-155.
Hampton, K. N., & Ling, R. (forthcoming).
Explaining Large Scale Social Change in Core Networks: Why Bigger is not Better and Less Can Mean More. Working
paper. Department of Communication. Rutgers University. New Brunswick.
Hampton, K. N. (2011). Comparing Bonding and Bridging
Ties for Democratic Engagement: Everyday Use of Communication Technologies
within Social Networks for Civic and Civil Behaviors. Information, Communication & Society, 14(4), 510-528
Hampton, K. N., Lee, C. J., &
Her, E. J. (2011). How New Media
Afford Network Diversity: Direct and Mediated Access to Social Capital Through
Participation in Local Social Settings. New
Media & Society, 13(7), 1031-1049
Hampton, K. N., Goulet,
L. S., Rainie, L., & Purcell, K. (2011). Social Networking Sites and Our Lives: How People's
Trust, Personal Relationships, and Civic and Political Involvement are Connected to Their Use of Social Networking Sites and Other
Technologies. Washington, D.C.: Pew Research.
Week 13 (December 3) – Diffusion and Influence
Rogers,
Coleman, James S., Elihu Katz, and
H. Menzel.
(1957). The Diffusion of an Innovation Among
Physicians. Sociometry 20: 253-270.
Weimann, Gabriel. (1982). On the Importance of Marginality:
One More Step into the Two-Step Flow of Communication. American Sociological Review 47(6): 764-773.
Erickson, Bonnie. (1997). The
Relational Basis of Attitudes. Pp. 99-122 in Social Structures: A Network Approach edited by Barry Wellman and
S. D. Berkowitz.
Aral,
S., & Walker, D. (2012). Identifying Influential and Susceptible Members of Social Networks.
Science, 337(6092), 337-341
Watts, D. J., & Dodds, P. S. (2007). Influentials, networks, and public opinion formation. Journal of Consumer Research, 34(4),
441-458
Burris,
V. (2004). The academic caste system:
Prestige hierarchies in PhD exchange networks. American Sociological Review, 69(2), 239-264
Week 14 (December 10) – Health
Cohen, S., Brissette,
Dickens, C.M., L. McGowen,
C. Percival, J. Douglas, B. Tomensen, L. Cotter, A Heagerty, and F.H. Creed. (2004). Lack of Close Confidant,
but not Depression, Predicts Further Cardiac Events After
Myocardial Infraction. Heart 90(5):
518-522.
Bearman, P. S., Moody, J., & Stovel,
K. (2004). Chains of Affection:
The Structure of Adolescent Romantic and Sexual Networks. American Journal
of Sociology, 110(1), 44-91.
Christakis, Nicholas, and James Fowler. (2007). The Spread of Obesity
in a Large Social Network over 32 Years. The
Kolata, G. (2011, August 8). Catching Obesity From Friends
May Not Be So Easy. New
York Times.
Suitor,
Jill, Karl Pillemer, and Shirley Keeton. (1995). When Experience
Counts: The Effects of Experiential and Structural Similarity on Patterns of
Support and Interpersonal Stress. Social
Forces 73(4): 1573-1588.
Week 15 (December
17) – Final Papers Due