COMM 670 / MLIS 502 SOCIAL NETWORKS
Rutgers, The State University of New Jersey
Mon 6:20-9:00pm (CI 337)
Prof. Keith Hampton
Course website: http://ecollege.rutgers.edu
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.
PhD students: no prerequisites.
MCIS students: no prerequisites.
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:
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.
-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.
All readings, files, and grades will be available from the course website: http://ecollege.rutgers.edu.
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 email@example.com with the following information in the body of the message (leave the Subject line blank): subscribe SOCNET <yourfirstname> <yourlastname>
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.
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
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.
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
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