Seminar in Library Management
Topic: Social Network Management and Social Analytics
Spring 2017 Syllabus
Canvas Login and Tutorials
Canvas Information: Courses will be available beginning January 26th, 6 am PT unless you are taking an intensive or a one unit or two unit class that starts on a different day. In that case the class will open on the first day that the class meets.
You will be enrolled into the Canvas site automatically.
As the importance of social media in engaging our communities increases, understanding how social networks affect engagement efforts as well as knowing how to gauge effectiveness of those efforts is a critical skill. Through discussion, labs, and use of real-world tools, students in this course will learn how social networks form and function and how to evaluate the effectiveness of efforts to engage with those networks.
This course will require the use of various software packages to perform social network analysis as well as analyses of social media data. In order to complete the activities, you will need to
- To have access to a computer which has a locally installed version of Microsoft Excel (any version after 2007 will work). Please note that Office 365 Online does not support the functionality required for purposes of this class and it will not work; and
- Be comfortable (and have the permissions necessary) to install open source software on your machine.
Because of the incredible variety in possible system configurations, the amount of technical support I can provide to you is limited, so please take this into account. You are responsible for ensuring you have an adequate technical environment that will allow you to perform the lab exercises.
There are three assignment types in this course:
You will develop a presentation to the leadership of your selected organization related to the findings of your social network and media analysis. In no more than 10 slides and 10 minutes, the presentation should demonstrate the following
- The ability to discuss important social media measures succinctly and in language a non-expert will understand,
- An overview of the major findings, and
- A list of recommended next steps that are clearly based on evidence from the analysis
(Relates to CLO1, CLO2, and CLO3 and Core Competencies D and H)
There will nine discussions worth 10 points each. Each discussion will have a set of issues to be addressed and credit will be awarded proportionately based on how complete and cogent each issue is addressed in the overall discussion.
There are eight labs worth 10 points each. Each lab will have a set of outcomes to be met. Each outcome will be assigned a specific value and credit will be awarded for successfully meeting the outcome. It is important to note that several labs are cumulative. That is, the outcome of a prior lab is critical to the success of a subsequent lab.
The following is the basic outline of the course activities and assignments.
This course runs on a Monday through Sunday schedule, meaning that all assignments and activities for the week must be submitted or completed by 11:59 PT on the Sunday at the end of the week.
Note: In the following table, ASMN refers to the course textbook (Analyzing Social Media Networks with NodeXL.).
|1||Introduction to Social Network Analysis||
||ASMN – Chapter 1, 2, and 3
Wilson, C., Boe, B., Sala, A., Puttaswamy, K. P. N., Zhao, B. Y. (2009). User interactions in social networks and their implications
|2||Getting started with social media analysis||
||ASMN – Chapters 4 and 5|
|3||Preparing and filtering data||
||ASMN – Chapter 6|
|4||Analyzing clusters and groups||
||ASMN – Chapter 7
Welser, Gleave, Fisher, and Smith, (2007). Visualizing the Signatures of Social Roles in Online Discussion Groups
||ASMN – Chapter 8|
||ASMN – Chapter 10
Mislove, Lehman, Ahn, Onnela, and Rosenquist (2011). Understanding the demographics of Twitter Users.
||ASMN – Chapter 11
Kosinski, M., Stillwell, D., and Graepel,T. (2013). Private traits and attributes are predictable from digital records of human behavior,
|8||Putting it all together||
There are 300 possible points total in the course:
There are seven discussions worth 10 points each. Each discussion will have a set of issues to be addressed and credit will be awarded proportionately based on how complete and cogently each issue is addressed in the overall discussion.
There are seven labs worth 10 points each. Each lab will have a set of outcomes to be met. Each outcome will be assigned a specific value and credit will be awarded for successfully meeting the outcome.
The culminating project will be worth 160 points and will be assessed based on the following criteria:
- The ability to discuss important social media measures succinctly and in language a non-expert will understand (up to 30 points)
- A summary of the method of analysis used to perform the evaluation (up to 40 points)
- An overview of the major findings (up to 40 points)
- A list of recommended next steps that are clearly based on evidence from the analysis (up to 40 points), and
- Overall professionalism of the presentation (up to 10 points)
Late assignments will incur a penalty of a 10% grade reduction for each day they are late.
Course Workload Expectations
Success in this course is based on the expectation that students will spend, for each unit of credit, a minimum of forty-five hours over the length of the course (normally 3 hours per unit per week with 1 of the hours used for lecture) for instruction or preparation/studying or course related activities including but not limited to internships, labs, clinical practica. Other course structures will have equivalent workload expectations as described in the syllabus.
Instructional time may include but is not limited to:
Working on posted modules or lessons prepared by the instructor; discussion forum interactions with the instructor and/or other students; making presentations and getting feedback from the instructor; attending office hours or other synchronous sessions with the instructor.
Student time outside of class:
In any seven-day period, a student is expected to be academically engaged through submitting an academic assignment; taking an exam or an interactive tutorial, or computer-assisted instruction; building websites, blogs, databases, social media presentations; attending a study group;contributing to an academic online discussion; writing papers; reading articles; conducting research; engaging in small group work.
INFO 200, INFO 204.
Course Learning Outcomes
Upon successful completion of the course, students will be able to:
- Identify and demonstrate understanding of the fundamental social network analysis concepts such as centrality, betweenness, boundary spanning, ego networks, etc.
- Analyze and discuss the effectiveness of the social media efforts of a library or information organization in terms of the organization as well as its constituencies.
- Compare competing theories and modes of analysis to justify a proposed course of analysis to organizational leaders and the community at large.
Core Competencies (Program Learning Outcomes)
INFO 282 supports the following core competencies:
- D Apply the fundamental principles of planning, management, marketing, and advocacy.
- H Demonstrate proficiency in identifying, using, and evaluating current and emerging information and communication technologies.
- Hansen, D. L., Schneiderman, B., & Smith, M. A. (2010). Analyzing social media networks with NodeXL: Insights from a connected world. Burlington, MA: Morgan Kaufmann. Available through Amazon: 0123822297
The standard SJSU School of Information Grading Scale is utilized for all iSchool courses:
|97 to 100||A|
|94 to 96||A minus|
|91 to 93||B plus|
|88 to 90||B|
|85 to 87||B minus|
|82 to 84||C plus|
|79 to 81||C|
|76 to 78||C minus|
|73 to 75||D plus|
|70 to 72||D|
|67 to 69||D minus|
In order to provide consistent guidelines for assessment for graduate level work in the School, these terms are applied to letter grades:
- C represents Adequate work; a grade of "C" counts for credit for the course;
- B represents Good work; a grade of "B" clearly meets the standards for graduate level work;
For core courses in the MLIS program (not MARA or Informatics) — INFO 200, INFO 202, INFO 204 — the iSchool requires that students earn a B in the course. If the grade is less than B (B- or lower) after the first attempt you will be placed on administrative probation. You must repeat the class if you wish to stay in the program. If - on the second attempt - you do not pass the class with a grade of B or better (not B- but B) you will be disqualified.
- A represents Exceptional work; a grade of "A" will be assigned for outstanding work only.
Students are advised that it is their responsibility to maintain a 3.0 Grade Point Average (GPA).
Per University Policy S16-9, university-wide policy information relevant to all courses, such as academic integrity, accommodations, etc. will be available on Office of Graduate and Undergraduate Programs' Syllabus Information web page at: http://www.sjsu.edu/gup/syllabusinfo/. Make sure to visit this page, review and be familiar with these university policies and resources.
In order to request an accommodation in a class please contact the Accessible Education Center and register via the MyAEC portal.
Download Adobe Acrobat Reader to access PDF files.
More accessibility resources.