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{{Old Class}}
= Course Information =
= Course Information =
:'''COM 304: Quantitative Methods for Communication Research'''
:'''COM 304: Quantitative Methods for Communication Research'''


''Lecture''
''Lecture''
:'''Location:''' LWSN 1142
:'''Location:''' LWSN 2273
:'''Class Hours:''' Tuesdays and Thursdays; 9:30-10:20 AM
:'''Class Hours:''' Tuesdays and Thursdays; 9:30-10:20 AM


Line 19: Line 17:
:'''Email:''' jdfoote@purdue.edu
:'''Email:''' jdfoote@purdue.edu
:'''[[User:Jdfoote/OH|Office Hours]]:''' Thursdays; 2:00–4:00pm and by appointment
:'''[[User:Jdfoote/OH|Office Hours]]:''' Thursdays; 2:00–4:00pm and by appointment


:'''Graduate TA:''' Grace Lee
:'''Graduate TA:''' Grace Lee
:'''Email:''' lee3416@purdue.edu
:'''Email:''' lee3416@purdue.edu
:'''Office Hours:''' Thursdays; 10:30–11:45am and by appointment


:'''Graduate TA:''' Yihan Jia
:'''Graduate TA:''' Yihan Jia
:'''Email:''' jia110@purdue.edu
:'''Email:''' jia110@purdue.edu
:'''Office Hours:''' Tuesdays and Thursdays; 11:00am–12:00pm and by appointment


<div style="float:right;">{{toclimit|limit=3}}</div>
<div style="float:right;">__TOC__</div>


= Course Overview and Learning Objectives =
= Course Overview and Learning Objectives =


Welcome to COM 304: Quantitative Methods for Communication! We are excited to have you in the class. Nearly all communication jobs involve quantitative research in some way; in this course, we will provide you a foundation for doing quantitative communication research.
Communication is inherently a social process. This class focuses on understanding how the structure of relationships between people influence communication patterns and behavior. This perspective can help us to understand a broad set of phenomena, from online communities to friendships to businesses. The course will also introduce students to using network visualizations to gain and share insights about network phenomena.


I know that for many Communication majors even thinking of math and statistics is traumatic, but we will work hard to provide the resources that you need to succeed and we will take things one step at a time. You can do this!
Students who complete this course will be able to:
# Understand the foundations of social network theory and analysis.
# Critically read and comprehend concepts, results, and implications presented in studies of social networks.
# Learn how networks are related to social phenomena in their personal and professional worlds.
# Gain a basic understanding of gathering network data and analyzing them using the programming language R.


= Required resources and texts =


This course introduces students to a range of social-scientific research methods used to investigate human communication. By the end of this course, you will be able to: 
== Laptop ==
# Explain the types of research questions, methods, and analyses used by scholars who conduct social-scientific studies of communication, as well as by practitioners in fields such as marketing and consumer research, political polling, etc.;
# Critically evaluate quantitative research reports, including those you may read in other courses at Purdue as well as those described in the popular media, appearing in business reports, grant applications, and so forth;
# Design and conduct basic research studies about communication-related topics.
The course is organized into three components which are addressed simultaneously throughout the semester: (1) Research Design, (2) Statistics, and (3) Statistical Software.


The Research Design component focuses on the process of planning research, considering the range of choices researchers must make in order to conduct useful studies.  This component will not only help you conduct research, it will make you a more critical research consumer.
One of the goals of this class is a basic understanding of analyzing and visualizing network data in R. The labs on campus have R on them, and we are meeting in a computer lab so that those who need to can use the lab computers, but I recommend that you put R on your computer and do the assignments on your computer. In order to do this, you will need a machine with at least 2GB of memory. Windows, Mac OS, and Linux are all fine but an iPad or Android tablet won't work.
 
The Statistics component is concerned with analyses by which numerical data can be synthesized, described, and interpreted. This component provides a strong conceptual introduction to statistics—with a limited amount of math—and will help you to be confident in analyzing basic numerical data for almost any purpose.  
 
The Software component is closely allied with the Statistics component. This component focuses on basic applications of the Statistics Package for the Social Sciences (SPSS)—a powerful, but user-friendly computer program—and will give you an immediately marketable skill (something to put on the resume). This course should be of use to students with a number of goals, including those: (a) who are contemplating graduate study in communication or related fields; (b) whose current or future career may require them to answer questions by collecting and analyzing data (e.g., advertising, human relations, marketing, public relations); and (c) who want to develop their skills at critically evaluating research and knowledge claims made by “experts” on communication issues.
 
= Required resources and texts =


Talk to me ASAP if you don't have a laptop that will work or if your laptop dies. There are a few options that can work out - either through on-campus lab computers or using a virtual machine.


== Readings ==
== Readings ==


Required texts:  
* Required texts:  
* Salkind, N. J. (2017). Statistics for people who (think they) hate statistics (6th ed.). Los Angeles, CA: Sage.
* Easley, D., & Kleinberg, J. (2010). Networks, crowds, and markets. Cambridge University Press. [[https://www.cs.cornell.edu/home/kleinber/networks-book/ web edition (free)]] [[https://www.cs.cornell.edu/home/kleinber/networks-book/networks-book.pdf pre-print pdf (free)]] [[https://smile.amazon.com/Networks-Crowds-Markets-Reasoning-Connected/dp/0521195330/ (print edition (Amazon))]]
** ''Note'': I believe that you should be fine with one edition newer or older than this one, too. Just make sure that the topic matches up with what the syllabus says.
* Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. Riverside, CA: University of California, Riverside [http://faculty.ucr.edu/~hanneman/nettext/ [web edition(free)]]


You also will be assigned readings from online resources; these readings are listed on the course schedule of this syllabus (below) and links are provided in each lecture’s folder on the course Brightspace site.  Readings from the text and online resources will be covered in the midterm and final exams.
* Other readings: Other readings will be made available on Brightspace.


== Technology ==  
=== Reading Academic Articles ===


Smart phone or laptop to complete in-class Hotseat participation questions.
Many of the readings will be academic articles. I do not expect you to read every word of these articles. Rather, you should practice intentional directed skimming. [https://writingcenter.gmu.edu/guides/strategies-for-reading-academic-articles This article] gives a nice overview. The TL;DR is that you should carefully read the abstract, introduction, and conclusion. For the rest of the article, focus on section headings and topic sentences to extract the main ideas.


== Other suggested books ==


We will be using the statistical software SPSS for most of the labs. SPSS is loaded on all Purdue lab computers. In a pinch, you may be able to access it via goremote (https://goremote.itap.purdue.edu) but in general using the lab computers will be simpler and faster.
* Barabasi, A-L. (2002). Linked: The new science of networks. Cambridge, MA: Perseus.
* Scott, J. (2000). Social network analysis: A handbook (2nd edition). London: Sage Publications.
* Watts, D. J. (2004). Six degrees: The science of a connected age. WW Norton & Company.
* Christakis, N. and Fowler, J. (2009). [https://archive.org/details/connectedsurpris00chri/ Connected : the surprising power of our social networks and how they shape our lives]


= Course logistics =
= Course logistics =
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== Note About This Syllabus ==
== Note About This Syllabus ==


Although the core expectations for this class are fixed, this is my first time teaching the course and I may make some adjustments to the details of readings and assignments. As a result, there are three important things to keep in mind:
Although the core expectations for this class are fixed, the details of readings and assignments may shift based on how the class goes. As a result, there are three important things to keep in mind:


# Although details on this syllabus will change, I will not change readings or assignments less than one week before they are due. If you plan to read more than one week ahead, contact me first.
# Although details on this syllabus will change, I will not change readings or assignments less than one week before they are due. If I don't fill in a "''To Be Determined''" one week before it's due, it is dropped. If you plan to read more than one week ahead, contact me first.
# Because this a wiki, you will be able to track every change by clicking the ''history'' button on this page. I will also summarize these changes in an announcement on Brightspace that should be emailed to everybody in the class if you have notifications turned on.
# Closely monitor the class [[/Discord Signup|Discord]]. Because this a wiki, you will be able to track every change by clicking the ''history'' button on this page. I will also summarize these changes in an announcement on Discord that should be emailed to everybody in the class if you have notifications turned on.
# I will ask the class for voluntary anonymous feedback. Please let me know what is working and what can be improved.
# I will ask the class for voluntary anonymous feedback frequently. Please let me know what is working and what can be improved.


== Class Sessions ==
== Class Sessions ==


There are two types of class sessions: lecture sessions and lab sessions.
This course will follow "flipped" classroom model. I expect you to learn most of the content of the course asynchronously. The goal of our time together is not to tell you new things, but to consolidate knowledge and to clear up misconceptions.


The lectures sections will be led by Dr. Foote and will be Tuesdays and Thursdays in Lawson 1142. The lab sessions will be on Fridays and will be led by Grace and Yihan, the TAs of the course.
The Tuesday meeting will be a collaborative, discussion-centric session. Typically, about half of each session will be devoted to going over assignments and the other half will be a discussion of the readings and videos from that week.


I expect you to come to the lecture sessions prepared, having read the material. It is fine to have questions---indeed, one of the goals of these sessions is to identify things that are confusing and to clear up misconceptions---but you should be ready to talk about your attempts to understand and why something is confusing.
The Thursday meetings will be more like a lab. Some of these sessions will include synchronous activities; often they will be a time for me to introduce and help with R assignments. Sometimes they will be more of a co-working time, where you can work on assignments and I can be available to answer questions.
 
I will do my best to post lecture slides to Brightspace before class.


== Getting Help ==
== Getting Help ==
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Your first place to look for help should be each other. By asking and answering questions on Discord, you will not only help to build a repository of shared information, but to reinforce our learning community.
Your first place to look for help should be each other. By asking and answering questions on Discord, you will not only help to build a repository of shared information, but to reinforce our learning community.


I will also hold office hours on Thursdays, from 2-4 ([[User:Jdfoote/OH|sign up here]]).
I will also hold office hours after our class on Thursdays, from 2-4 ([[User:Jdfoote/OH|sign up here]]). If you come with a programming question, I will expect that you have already tried to solve it yourself in multiple ways and that you have discussed it with a classmate. This policy lets me have time to help more students, but it's also a useful strategy. Often [https://en.wikipedia.org/wiki/Rubber_duck_debugging just trying to explain your code] can help you to recognize where you've gone wrong.


I will also check Discord at least once a day. I encourage you to post questions there, and to use it as a space where we can help and instruct each other. In general, you should contact me there. I am also available by email. You can reach me at [mailto:jdfoote@purdue.edu jdfoote@purdue.edu]. I try hard to maintain a boundary between work and home and I typically respond only on weekdays during business hours.
I will also check Discord at least once a day. I encourage you to post questions there, and to use it as a space where we can help and instruct each other. In general, you should contact me there. I am also available by email. You can reach me at [mailto:jdfoote@purdue.edu jdfoote@purdue.edu]. I try hard to maintain a boundary between work and home and I typically respond only on weekdays during business hours.


=== Online Resources ===
Programming can be difficult and frustrating and confusing, but you will get it! I have put together a few resources to help you with the programming portion of the course.
* Finding and fixing bugs in your code [[https://purdue.brightspace.com/d2l/le/content/208700/viewContent/5698552/View Video]] [[https://jeremydfoote.com/TDIS/week_8/debugging.Rmd R Markdown file]] [[https://jeremydfoote.com/TDIS/week_8/debugging.html HTML file]]
* Intro to ggraph and tidygraph [[https://jeremydfoote.com/Communication-and-Social-Networks/week_6/ggraph_walkthrough.Rmd R Markdown file]] [[https://jeremydfoote.com/Communication-and-Social-Networks/week_6/ggraph_walkthrough.html HTML file]]


= Assignments =
= Assignments =


Your success in this class depends most on you being engaged in the learning process. It is essential that you: (a) study the readings in advance of class; (b) attend class and stay focused on the day’s material; (c) complete all of the lecture and SPSS homework assignments, and talk to me or your TA if you have questions about these assignments, and (d) plan in advance for the completion of projects and studying for exams. In short, it is essential that you take significant responsibility for your own learning.  If you do so, you may find that Quantitative Methods is not only challenging but rewarding.


In order to encourage your learning, the course includes several types of assignments.
There will be multiple types of assignments, designed to encourage learning in different ways.
 
== Participation ==
 
I expect you to be an active member of our class. This includes paying attention in class, participating in activities, and being actively engaged in learning, thinking about, and trying to understand the material.
 
To make sure that everyone has an opportunity to participate and to encourage you to do the assignments, I will randomly select students to discuss readings or to explain portions of homework assignments and labs.
 


== Midterm and Final Exams ==
== Discussion Questions ==


Students will complete a midterm and a final exam.  Each exam will cover material from lectures, discussion, and readings. They will assess your knowledge of research methods and statistics, but not your use of SPSS. Review sheets will be distributed before each exam. The midterm and final exam each are worth 100 points. Please do not make travel arrangements that interfere with the scheduled exams.
In order to make sure that we are prepared to have a productive discussion, you are required to submit one or two discussion questions that you think would be interesting to discuss on Monday by noon. Post your questions on the shared Google Doc at https://docs.google.com/document/d/1AK4MhWLVwDuxqvTwLomN7hu4aLpo59n5qXgEap8SBNc/edit?usp=sharing; try to group similar questions together.
 
Questions should engage with the readings and either connect to other concepts or to the "real world". Here are some good example questions:
 
* The readings this week talked a lot about how network ties get created. I made a list of my closest friends and I realized that most of them only became friends after we happened to be in the same groups over and over again. What role does repetition have in forming ties?
* I was confused by the reading on social capital. What's the difference between social capital and power? And if they are the same, then why not just call it "network power"?
* Imagine you were asked to analyze the network of a big company to help them to identify people who deserve a raise. What measures would you use to identify them? What would you not use?
 
Some weeks will also include more practical homework (mostly data manipulation and visualization in R). On those weeks, portions of our discussions will center around going over homework questions and identifying places where folks are still confused.


== Homework/Labs ==
== Homework/Labs ==


Students will complete 10 SPSS homework assignments over the course of the class. They will be assigned in Friday labs and are due in the next lab, when lab begins. Each SPSS homework assignment is worth 5 points, for a total of 50 points.
There will be a number of homework assignments. At the beginning of the class, these will be designed to help you to grasp foundational network concepts. As the class progresses, more and more of them will be analyzing and visualizing networks in R.


== SPSS Quizzes ==
== Exams ==


There will be two quizzes pertinent to the SPSS component of the course. These quizzes will assess your ability to use SPSS and interpret the program output. They will be given during Friday lab sessions at the middle and end of the semester. Each SPSS quiz is worth 50 points. Please do not make travel arrangements that interfere with the scheduled quizzes.
There will be one take home exam. It will assess your understanding of core communication and social networks concepts.


== Survey Design Project ==
== Final Project ==


To build your knowledge of survey design, you will work in a group on a survey development project. The project involves developing research and survey questions; the project and your contribution to the group together are worth 50 points.
Students will work on a [[/Final project|Final Project]] that explains how network analysis and a network approach can benefit an organization.


== Survey Analysis Project ==
A number of intermediate assignments through the semester will help you to gain the skills and data necessary to be successful.


To encourage synthesis of knowledge and skills across all of the course components, you will work in a group on the collection and analysis of data from the Survey Design Project. The project involves the collection, analysis, and “write-up” of data. Detailed descriptions of this project will be provided as the semester progresses. This project is worth 80 points.
= Grades =


== Participation ==
This course will follow a "self-assessment" philosophy. I am more interested in helping you to learn things that will be useful to you than in assigning grades. In general, I think that my time is much better spent in providing better feedback and in being available to work through problems together.


I expect you to be an active member of our class. This includes reading the material before class, paying attention in class, participating in activities, and being actively engaged in learning, thinking about, and trying to understand the material.
The university still requires grades, so you will be leading the evaluation of your work. This will be completed with me in three stages, at the end of weeks 5, 10, and 16. In each stage, you will use [[Self Assessment Reflection|this form]] to reflect on what you have accomplished thus far, how it has met, not met, or exceeded expectations, based both on rubrics and personal goals and objectives. At each of these stages you will receive feedback on your assessments. By the end of the semester, you should have a clear vision of your accomplishments and growth, which you will turn into a grade. As the instructor-of-record, I maintain the right to disagree with your assessment and alter grades as I see fit, but any time that I do this it will be accompanied by an explanation and discussion. These personal assessments, reflecting both honest and meaningful reflection of your work will be the most important factor in final grades.


To make sure that everyone has an opportunity to participate and to encourage you to do the assignments, I will randomly select students to answer questions about the concepts from readings or to explain portions of homework assignments and labs.
We will use the following rubric in our assessment:


Lecture classes will also typically include questions on Hotseat, which will also be used to take attendance.
* 20%: class participation, including attendance and participation in discussions and group work
* 20%: Labs and homework assignments
* 25%: Exam
* 35%: Final Project


Please do not come to class if you have COVID symptoms (or symptoms of other airborne diseases!). In order to align the incentives so that people don't show up sick, we will track attendance but lecture and lab participation will be self-graded out of a total of 20 points.
The exam will be graded like a normal exam and the score will make up 25% of your grade. For the rest of the assignments (and the other 75% of your grade), I will provide feedback which will inform an ongoing conversation about your work.


= Grades =
My interpretation of grade levels (A, B, C, D/F) is the following:


I really believe that students and instructors should be on the same team, with the goal of learning. I see grades as a tool to motivate learning. Our goal will be to provide feedback that helps you to learn.


There are 500 points in the class, distributed across assignments as follows:
A: Reflects work the exceeds expectations on multiple fronts and to a great degree. Students reaching this level of achievement will:
* Do what it takes to learn the principles and techniques of social networks, including looking to outside sources if necessary.
* Engage thoughtfully with an ambitious final project.
* Take intellectual risks, offering interpretations based on synthesizing material and asking for feedback from peers.
* Share work early allowing extra time for engagement with others.
* Write reflections that grapple meaningfully with lessons learned as well as challenges.
* Complete all or nearly all homework assignments at a high level.


{| class="wikitable"
B: Reflects strong work. Work at this level will be of consistently high quality. Students reaching this level of achievement will:
|+ Assignment points
* Be more safe or consistent than the work described above.
|-
* Ask meaningful questions of peers and engage them in fruitful discussion.
|Midterm Exam
* Exceed requirements, but in fairly straightforward ways - e.g., an additional post in discussion every week.
| 100 points
* Compose complete and sufficiently detailed reflections.
|-
* Complete many of the homework assignments.
|Final Exam
| 100 points
|-
| Survey Design Project
| 50 points
|-
|Survey Analysis Project
| 80 points
|-
| SPSS Quiz 1
| 50 points
|-
| SPSS Quiz 2
| 50 points
|-
| Lab Homework
| 50 points
|-
| Participation
| 20 points
|-
|}


Your final course grade will be calculated using the following scale:
C: This reflects meeting the minimum expectations of the course. Students reaching this level of achievement
will:
* Turn in and complete the final project on time.
* Be collegial and continue discussion, through asking simple or limited questions.
* Compose reflections with straightforward and easily manageable goals and/or avoid discussions of challenges.
* Not complete homework assignments or turn some in in a hasty or incomplete manner.


<div style=display:inline-table>
D/F: These are reserved for cases in which students do not complete work or participate. Students may also be
{| class="wikitable"
impeding the ability of others to learn.
|-
| 484-500 points
| A+
|-
|464-483 points
| A
|-
|449-463 points
| A-
|-
|434-448 points
| B+
|-
|414-433 points
| B
|-
|400-413 points
| B-
|}
</div>
<div style=display:inline-table>
{| class='wikitable'
|-
|384-399 points
| C+
|-
|364-383 points
| C
|-
|349-363 points
| C-
|-
|334-348 points
| D+
|-
|314-333 points
| D
|-
|300-313 points
| D-
| < 300 points
| F
|-
|}
</div>


== Extra Credit for Participating in Research Studies ==
== Extra Credit for Participating in Research Studies ==


he course is signed up for extra credit through the Brian Lamb School of Communication Research Participation System.
If you feel like you need to earn extra credit in order to earn the grade that you would like, the course is signed up for extra credit through the Brian Lamb School of Communication Research Participation System.


* You earn a ½ percent credit for every half-hour that you participate in a study. The maximum percent that you can earn for this course is 2% (or 10 total points), which will be added to your total course points (500).
* Please review the instructions before you sign up for studies; to view the instructions go to https://www.cla.purdue.edu/communication/research/participation/students.html
* Please review the instructions before you sign up for studies; to view the instructions go to https://www.cla.purdue.edu/communication/research/participation/students.html
* You can sign up to participate in studies by logging into http://purdue-comm.sona-systems.com/.
* You can sign up to participate in studies by logging into http://purdue-comm.sona-systems.com/.
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== Week 1: Variables, Research Questions, and Hypotheses ==
== Week 1: Introductions and the network perspective ==


==== January 11 ====
August 24


'''Assignment Due:'''  
'''Assignment Due:'''  
* [[/Discord Signup|Sign up for Discord]] and introduce yourself
* [[/Discord Signup|Sign up for Discord]] and introduce yourself
* Take [https://forms.gle/Ak9GYuFGer89k6G47 this very brief survey]
* Take [https://forms.gle/ANqbnAXxivexukgB7 this very brief survey]


'''Required Readings:'''  
'''Required Readings:'''  
* Five Big Words (on Brightspace)
* None


'''Concepts:'''
'''Concepts:'''
* Class overview and expectations — We'll walk through this syllabus.
* Class overview and expectations — We'll walk through this syllabus.
* Goals of Quantitative Research
* What are social networks?
* Why study networks?




==== January 13 ====
August 26


'''Assignment Due:'''  
'''Assignment Due:'''  
* Read the entire syllabus (this document)
* Read the entire syllabus (this document)


'''Readings (on Brightspace):'''  
'''Readings:'''  
* Variables in non-experimental studies
 
* Conceptualizing
* Writing RQs


'''Concepts:'''
'''Class Schedule:'''
* Constructs
* Network simulation activity (bring a computer)
* Hypotheses
* Start work on [[/Homework 1|Homework 1]]
* Research Questions
* Independent/Dependent Variables


==== January 14 ====
== Week 2: Network representations  ==


'''Lab 1: Intro to SPSS'''
August 31


== Week 2: Surveys ==
'''Assignment Due (on Monday):'''
* Install R and RStudio on your computer. [https://techvidvan.com/tutorials/install-r/ This tutorial] should help you to succeed.
* [[Communication and Social Networks (Fall 2021)/Homework 1|Homework 1]]
* [[#Discussion Questions|Discussion questions]] (Due Monday at noon!)


==== January 18 ====
'''Lecture Video (before class):'''
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/6819548/View Network Data and Network Types Lecture] [19:18]


'''Readings (before class):'''  
'''Readings (before class):'''  
* Scales of Measurement
* James M. Cook, [http://www.umasocialmedia.com/socialnetworks/wp-content/uploads/2016/08/WhatIsASocialNetwork.pdf What is a Social Network?]
 
* James M. Cook, [http://www.umasocialmedia.com/socialnetworks/wp-content/uploads/2016/09/IndividualsVersusNetworks.pdf Individuals versus Networks]
'''Concepts:'''
* (Optional/skim) Freeman, L. C. (2000). [https://www.cmu.edu/joss/content/articles/volume1/Freeman.html Visualizing social networks]. Journal of social structure, 1(1), 4.
* Scales
 
 
====January 20====


'''Readings (before class):'''
* How to improve online survey response rates;
* Survey questions 101: do you make any of these 7 question-writing mistakes?


'''Concepts:'''
'''Concepts:'''
* Selection effects
* Complex systems and networks
* Individual and collective behavior




* Survey Project Assigned
September 2


====January 21====
'''Class Schedule:'''
* Go through [https://ncase.me/polygons/ Parable of the Polygons] by Nicky Case
* Start work on [[/R Lab 1|R Lab 1]]


'''Lab 2: Entering and Modifying Data in SPSS'''
== Week 3: How are communication networks formed? ==


'''Assignment Due:'''
* Lab 1: Intro to SPSS
* Completed Homework Survey


== Week 3: Descriptive Statistics ==
September 7


'''Assignment Due (on Monday):'''
* [[/R Lab 1|R Lab 1]]
** [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/7337413/View Video explanation]
* [[#Discussion_Questions|Discussion Questions]]


====January 25====
'''Lecture Video:'''
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/6819550/View Edge Creation] [12:43] [[https://jeremydfoote.com/Communication-and-Social-Networks/week_3/lecture/tie_formation.html Slides]]


'''Readings (before class):'''  
'''Readings:'''  
* Salkind Chapter 2
* Monge, P. R., & Contractor, N. S. (2003). [https://purdue.brightspace.com/d2l/le/content/208700/viewContent/5245859/View Theories of communication networks]. Oxford, UK: Oxford University Press. (pp. 298--314) - On Brightspace under Content > Readings
* Salkind Chapter 4
* Feld, S. L. (1981). [https://www.jstor.org/stable/2778746 The focused organization of social ties]. American Journal of Sociology, 86(5), 1015–1035.
* McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). [https://www-jstor-org.ezproxy.lib.purdue.edu/stable/2678628 Birds of a Feather: Homophily in Social Networks]. Annual Review of Sociology, 27, 415–444.


'''Concepts:'''
''Note:'' This week involves reading two academic articles. [[#Reading_Academic_Articles|Read this]] to understand my expectations and some tips for reading and understanding these articles.
* Distributions
* Mean
* Median
* Mode
 
====January 27====
 
 
'''Readings (before class):'''
* Salkind Chapter 3
* Interquartile Range
* SD and normal curve


'''Concepts:'''
'''Concepts:'''
* Exposure, formation, maintenance, decay
* Homophily
* Reciprocity
* Triadic closure


====January 28====
* [https://jeremydfoote.com/Communication-and-Social-Networks/week_3/lecture/week_3.html Class Slides]
 
'''Lab 3: Modifying data in SPSS'''
 
'''Assignment Due:'''
* Lab 2
* SPSS Homework Survey Data File
 
== Week 4: Z-scores and correlation ==


====February 1====


'''Assignment Due:'''
September 9
* SURVEY PROJECT QUESTIONS DUE in Lecture


'''Readings (before class):'''
* Salkind Ch. 8 pp. 149-165
* Standard scores and the normal curve


'''Concepts:'''
'''Supplementary R lectures (watch before class):'''
* Standardization
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/6819552/View Why R + Programming principles lecture] [12:53]
* Z-scores
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/6819553/View ggraph explanation video] [12:14]
** [https://jeremydfoote.com/Communication-and-Social-Networks/week_6/ggraph_walkthrough.html webpage for ggraph explanation video]


====February 3====
'''Class Schedule:'''
* [https://github.com/jdfoote/Communication-and-Social-Networks/raw/fall-2021/week_4/creating_networks.Rmd R Lab 2]


'''Readings (before class):'''
== Week 4: Small group networks ==
* Salkind Chapter 5


'''Concepts:'''
September 14
* Correlation
* r
 
====February 4====
 
'''Lab 4: Descriptive Stats and z scores'''


'''Assignment Due:'''
'''Assignment Due:'''
* Lab 3
* [[#Discussion Questions|Discussion questions]]
 
* [https://github.com/jdfoote/Communication-and-Social-Networks/raw/fall-2021/week_4/creating_networks.Rmd R Lab 2] (right-click, save to your computer, and open in RStudio)
== Week 5: Reliability and Validity ==
** [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/6819549/View Homework explanation video]
 
====February 8====


'''Readings (before class):'''  
'''Lecture video:'''
* Salkind Chapter 6
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/7373077/View Networks in small groups] [14:43] [[https://jeremydfoote.com/Communication-and-Social-Networks/week_4/lecture/small_groups.html Slides]]
* Reliability and its relationship to Validity


'''Concepts:'''
* Validity
* Generalizability
* Replication


====February 10====
'''Readings:'''
* Krackhardt, D., & Hanson, J. R. (1993). [https://hbr.org/1993/07/informal-networks-the-company-behind-the-chart Informal networks: The company behind the chart]. Harvard business review, 71(4), 104-111.
* Katz, N., Lazer, D., Arrow, H., & Contractor, N. (2004). [https://libkey.io/libraries/228/articles/5387888/full-text-file?utm_source=api_559 Network theory and small groups]. Small Group Research, 35(3), 307–332.


'''Readings (before class):'''
* Sampling


'''Concepts:'''
'''Concepts:'''
* Informal networks
* Networks and group outcomes


====February 11====
== Week 5: Ego networks and network perception ==


'''Lab 5: Scatterplots and correlation'''
September 21


'''Assignment Due:'''
'''Assignment Due:'''  
* Lab 4
* [[#Discussion Questions|Discussion questions]]
* Turn in your [[Self Assessment Reflection]] on Brightspace




== Week 6: Sampling (cont'd) ==
'''Lecture:'''
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/6819551/View Ego networks and network perceptions lecture] [17:14] [[https://jeremydfoote.com/Communication-and-Social-Networks/week_5/lecture/ego_nets.html Slides]]


====February 15====
'''Readings:'''
* Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. University of California. ([https://faculty.ucr.edu/~hanneman/nettext/C9_Ego_networks.html Chapter 9])
* Marsden, P. V. (1987). [https://www-jstor-org.ezproxy.lib.purdue.edu/stable/2095397 Core Discussion Networks of Americans]. American Sociological Review, 52(1), 122–131.
* [https://hbr.org/2016/05/research-you-have-fewer-friends-than-you-think Research: You Have Fewer Friends than You Think]. (2016, May 12). Harvard Business Review.
* Smith, E. B., Menon, T., & Thompson, L. (2012). [https://pubsonline-informs-org.ezproxy.lib.purdue.edu/doi/full/10.1287/orsc.1100.0643 Status Differences in the Cognitive Activation of Social Networks]. Organization Science, 23(1), 67–82.


'''Assignment Due:'''
* Survey project


'''Readings (before class):'''
September 23
* Sampling distribution
* Sampling error


'''Concepts:'''
'''Class Schedule:'''
* [https://github.com/jdfoote/Communication-and-Social-Networks/raw/fall-2021/week_6/power_visualization.Rmd R Lab 3]


== Week 6: Power, centrality, and hierarchy ==


====February 17====
Due to Dr. Foote's illness, Sept. 28 discussion moved to Sept. 30


'''Review for Midterm'''
September 28


'''Assignment Due:'''
* [https://github.com/jdfoote/Communication-and-Social-Networks/raw/fall-2021/week_6/power_visualization.Rmd R Lab 3] (Right-click, save, open in RStudio, and knit)
** [https://jeremydfoote.com/Communication-and-Social-Networks/week_6/ggraph_walkthrough.html Introduction to tidygraph and ggraph]. Now that you've been at it for a while review this walkthrough that I wrote to help you to figure out how all of the different pieces work in tidygraph and ggraph.
* [[#Discussion Questions|Discussion questions]]


====February 18====
'''Video lecture:'''
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/7413870/View Centrality measures] [18:44] [[https://jeremydfoote.com/Communication-and-Social-Networks/week_6/lecture/centrality.html Slides]]


'''Lab 6: Reliability and Cronbach's alpha'''
'''Readings:'''  
* Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. [https://faculty.ucr.edu/~hanneman/nettext/C10_Centrality.html Chapter 10: Centrality and Power]
* Healy, K. (2013). [https://kieranhealy.org/blog/archives/2013/06/09/using-metadata-to-find-paul-revere/ Using Metadata to find Paul Revere].
* [https://www.youtube.com/watch?v=0unzqsPaPk8 Centrality measures]. Matthew Jackson. From [https://www.youtube.com/channel/UCCnG8fKY45aH73ahmGK2xcg Social and Economic Networks course]
* [https://www.youtube.com/watch?v=q8oBWwS2wAQ Centrality Eigenvector Measures]. Matthew Jackson
* (Optional) Holliday, Audrey, Campbell, & Moore, (2016). [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4898141/ Identifying well-connected opinion leaders for informal health promotion]


'''Assignment Due:'''
'''Class Schedule:'''
* Lab 5




== Week 7: Experimental Design ==
September 30


'''Class Schedule:'''


====February 22====
== Week 7: Social Capital, structural holes, and weak ties ==


'''MIDTERM EXAM'''


October 5


====February 24====
'''Assignment Due:'''
* [[#Discussion Questions|Discussion questions]]


'''Readings (before class):'''  
'''Lecture Video:'''
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/6819554/View Capital and Social Capital] [16:02] [[https://jeremydfoote.com/Communication-and-Social-Networks/week_7/lecture/social_capital.html Slides]]


'''Readings:'''
* Granovetter, M. S. (1973). [https://www-jstor-org.ezproxy.lib.purdue.edu/stable/2776392?sid=primo&seq=1#metadata_info_tab_contents The Strength of Weak Ties]. American Journal of Sociology, 78(6), 1360–1380. https://doi.org/10.1086/225469
* Kadushin, C. (2012).  [https://ebookcentral.proquest.com/lib/purdue/reader.action?docID=829477&ppg=175 Networks as Social Capital], in Kadushin, C. (2012). Understanding Social Networks. Theories, Concepts and Findings. Oxford: Oxford University Press.
* Putnam, R.D. (1995). [https://muse.jhu.edu/article/16643 Bowling Alone: America's Declining Social Capital]. Journal of Democracy 6(1), 65-78.
* (Optional) Bourdieu, P. (1986). [https://www.marxists.org/reference/subject/philosophy/works/fr/bourdieu-forms-capital.htm The forms of capital]. In J. Richardson (Ed.) Handbook of Theory and Research for the Sociology of Education (New York, Greenwood), 241-258.
* (Optional) Rainie, L. and Perrin, A. (2019). [https://www.pewresearch.org/fact-tank/2019/07/22/key-findings-about-americans-declining-trust-in-government-and-each-other/ Key findings about Americans’ declining trust in government and each other]. Pew Research Center.
* (Optional) Burt, R. S. (2000). [https://www.sciencedirect.com/science/article/pii/S0191308500220091 The network structure of social capital]. Research in Organizational Behavior, 22, 345–423.


'''Concepts:'''
'''Class Schedule:'''
* R Review
** Go through the [https://raw.githubusercontent.com/jdfoote/Communication-and-Social-Networks/fall-2021/resources/tidygraph_tutorial.Rmd Tidygraph Tutorial] in groups


====February 25====
== Week 8: Small worlds  ==


'''Lab 7: Review for SPSS Quiz 1'''
October 12


== Week 8: Causality  ==
OCTOBER BREAK - NO CLASS


==== March 1 ====
October 14


Final Project Assigned
'''Assignment Due:'''
* [[#Discussion Questions|Discussion questions]] - Just one question this week


'''Readings (before class):'''  
'''Lecture Video:'''
* Cialdini EPH Experiment (pp. 599-601)
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/6819555/View Small worlds video] [18:45] [[https://jeremydfoote.com/Communication-and-Social-Networks/week_8/lecture/small_worlds.html Slides]]
* True Experimental Designs


'''Readings:'''
* [https://www.youtube.com/watch?v=TcxZSmzPw8k The Science of Six Degrees of Separation][video][9:22]
* Travers, J. and Milgram, S. (1969). [https://www-jstor-org.ezproxy.lib.purdue.edu/stable/2786545  An experimental study of the small world problem]. ''Sociometry'', 32(4):425-443
* (Optional but short) Dodds, P. S., Muhamad, R., & Watts, D. J. (2003). [https://science-sciencemag-org.ezproxy.lib.purdue.edu/content/301/5634/827 An Experimental Study of Search in Global Social Networks]. ''Science'', 301(5634), 827.


'''Concepts:'''
* "True" experiments
*


====March 3====
'''Class Schedule:'''


'''Readings (before class):'''
== Week 9: Scale-free networks and the friendship paradox ==
* Establishing Cause and Effect
* Internal Validity
* External Validity


'''Concepts:'''
October 19


====March 4====
'''Assignment Due:'''
* [[/Social Search Assignment|Social Search Assignment]]
* [[#Discussion Questions|Discussion questions]]


'''Lab 8: SPSS Quiz 1'''
'''Lecture Video:'''
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/7524997/View Scale-free networks and the Friendship Paradox][18:21] [[https://jeremydfoote.com/Communication-and-Social-Networks/week_9/lecture/scale_free_and_friend_paradox.html Slides]]


'''Readings:'''
* Feld, Scott L. (1991), [https://www-jstor-org.ezproxy.lib.purdue.edu/stable/2781907 Why your friends have more friends than you do]. American Journal of Sociology, 96 (6): 1464–1477. https://doi.org/10.1086%2F229693
* [https://www.youtube.com/watch?v=tP2MLp7GL7Q Early Detection of an Outbreak using the Friendship Paradox]
* [https://www.youtube.com/watch?v=c867FlzxZ9Y Networks are everywhere with Albert-László Barabási]


== Week 9: Central Limit Theorem and standard errors ==
(Optional)
* Christakis, N. A., & Fowler, J. H. (2010). Social Network Sensors for Early Detection of Contagious Outbreaks. PLOS ONE, 5(9), e12948. https://doi.org/10.1371/journal.pone.0012948


====March 8====
October 21


'''Readings (before class):'''  
'''Class Schedule:'''
* Salkind Ch. 9, pp. 186-187
* [[/Six Degrees of Wikipedia Activity|Six Degrees of Wikipedia Activity]]
* Probability and Normal Curve & Standard Error of Mean (same PDF)


'''Concepts:'''


====March 10====
== Week 10: Social influence and diffusion ==


'''Readings (before class):'''
October 26
* Salkind Chapter 9 pp. 192-194
* Confidence interval for the mean


'''Concepts:'''
'''Weekly lecture:'''
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/7547996/View Social Influence and Contagion][22:12] [[https://jeremydfoote.com/Communication-and-Social-Networks/week_10/lecture/influence_and_diffusion.html Slides]]


'''Assignment Due:'''
* Turn in your [[Self Assessment Reflection]] on Brightspace
* [[Communication and Social Networks (Fall 2021)/Dutch School Data Visualization challenge|Dutch School Data Visualization
Challenge]]
* [[#Discussion Questions|Discussion questions]]


====March 11====
'''Readings:'''
* Chapter 4, "[https://web.archive.org/web/20191019100528/http://everythingisobvious.com/wp-content/themes/eio/assets/EIO_chapter4.pdf Special People]", in Watts, D. J. (2011). Everything is Obvious: Once you know the answer. New York, NY: Crown Business.
* [https://youtu.be/D9XF0QOzWM0 Duncan Watts on Common Sense]
* [Optional] Centola, D., & Macy, M. (2007). [https://www-journals-uchicago-edu.ezproxy.lib.purdue.edu/doi/full/10.1086/521848 Complex Contagions and the Weakness of Long Ties]. American Journal of Sociology, 113(3), 702–734.
* [Optional] Christakis, N. A., & Fowler, J. H. (2012). [https://onlinelibrary-wiley-com.ezproxy.lib.purdue.edu/doi/full/10.1002/sim.5408 Social contagion theory: Examining dynamic social networks and human behavior]. Statistics in Medicine, 32, 556–577.


'''Lab 9: Final Project Data Collection'''


====SPRING BREAK MARCH 14-18====
October 28
* Troubled Lands


== Week 10: Testing hypotheses ==


====March 22====
== Week 11: Communities and Core-periphery ==


'''Readings (before class):'''
November 2
* Salkind Chapter 7
* Salkind Chapter 9 pp. 188-192
* Salkind Chapter 10


'''Concepts:'''
'''Assignment Due:'''
* The null hypothesis
* [[#Discussion Questions|One discussion question]]
* Hypothesis testing
* Submit two exam questions on Brightspace
* Statistical significance
* [https://github.com/jdfoote/Communication-and-Social-Networks/raw/fall-2021/week_11/groups_in_networks.Rmd Finding and visualizing groups in networks] (Right-click, save, and open in RStudio).
* One sample z-test


'''Video Lecture:'''
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/7556414/View Communities and Core-periphery] [23:15] [[https://jeremydfoote.com/Communication-and-Social-Networks/week_11/lecture/communities_in_networks.html Slides]]


====March 24====
'''Readings:'''
* Girvan, M., & Newman, M. E. (2002). [https://www.pnas.org/content/pnas/99/12/7821.full.pdf Community structure in social and biological networks]. Proceedings of the National Academy of Sciences.
* Barberá, P., Wang, N., Bonneau, R., Jost, J. T., Nagler, J., Tucker, J., & González-Bailón, S. (2015). [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0143611 The critical periphery in the growth of social protests]. PLoS ONE.
* (Optional) Hanneman, R. A., & Riddle, M. (2005). [http://faculty.ucr.edu/~hanneman/nettext/C11_Cliques.html Cliques and sub-groups]. In Introduction to social network methods. University of California.


'''Readings (before class):'''  
'''Class Schedule:'''
* Chapter 17
* Computation of Two-way Chi-Square


'''Concepts:'''
== Week 12: Technology and networks ==
* Chi-squared tests


November 9


====March 25====
'''Lab 10: Survey Analysis Project: Data Entry'''


'''Assignment Due:'''
'''Assignment Due:'''
* Final Project data must be gathered
* [[#Discussion Questions|Discussion questions]]


== Week 11: Significance tests ==
'''Lecture Video:'''
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/7947991/View Technology and networks] [19:38]


====March 29====
'''Readings:'''
* Pariser, E. [https://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles Beware Online Filter Bubbles TED talk]
* Fletcher, R. [https://reutersinstitute.politics.ox.ac.uk/risj-review/truth-behind-filter-bubbles-bursting-some-myths The truth behind filter bubbles: Bursting some myths].
* Bail, C. [https://www.youtube.com/watch?v=nwRm_ssTarE Should we break our echo chambers?]
* Cohen, M. [https://www.psychologytoday.com/intl/blog/finding-love-the-scientific-take/202012/context-collapse Context Collapse]


'''Readings (before class):'''
(Optional)
* Cramer’s Phi
* Kleinberg, J. (2012). [https://link-springer-com.ezproxy.lib.purdue.edu/chapter/10.1007%2F978-3-642-29952-0_8 The Convergence of Social and Technological Networks]. In M. Agrawal, S. B. Cooper, & A. Li (Eds.), Theory and Applications of Models of Computation.
* Chris Bail, et al. (2018). [https://www.pnas.org/content/115/37/9216 Exposure to opposing views on social media can increase political polarization]. PNAS.


'''Concepts:'''
* Chi-Square: Effect Size


====March 31====
November 11


'''Readings (before class):'''
* How does the Internet work?
* Salkind Chapter 15


'''Concepts:'''
== Week 13: Collective behavior ==
* Testing ''r'' for statistical significance


==== April 1 ====
November 16
 
'''Lab 11: Two-way Chi-squared'''


'''Assignment Due:'''
'''Assignment Due:'''
* Lab 10
* [[#Discussion Questions|One discussion question]]
* Keep working on the [[Communication_and_Social_Networks_(Spring_2020)/Final_project | final project]]


== Week 12: t-tests ==
'''Readings:'''
* Becker, J., Brackbill, D., & Centola, D. (2017). [https://doi.org/10.1073/pnas.1615978114 Network dynamics of social influence in the wisdom of crowds]. Proceedings of the National Academy of Sciences, 201615978.
* [https://youtu.be/sdI-b5mfjH4 Video discussion with Dr. Becker] (watch after reading paper)
* Do [http://ncase.me/crowds/ The Wisdom or Madness of Crowds Simulation]


====April 5====
November 18


'''Readings (before class):'''
* Take-home exam is due
* Salkind Chapter 11


'''Concepts:'''
== Week 14: Networks and collaboration ==
* t-tests for independent groups


====April 7====
November 23


'''Readings (before class):'''
Asynchronous class - Happy Thanksgiving!
* Introduction to Effect Size


'''Concepts:'''
'''Assignment Due:'''  
* Cohen's ''d''
* 1 Discussion Question


====April 8====


'''Lab 12: t-test and Pearson's r'''
'''Lecture video:'''
* [https://purdue.brightspace.com/d2l/le/content/335123/viewContent/8035051/View Networks and Collaboration][17:19]


'''Assignment Due:'''
'''Readings:'''  
* Lab 11
* Read the [https://en.wikipedia.org/wiki/The_Wealth_of_Networks Wikipedia Article about The Wealth of Networks]
* Skim section two of Benkler, Y. (2002). [https://www-jstor-org.ezproxy.lib.purdue.edu/stable/1562247 Coase’s Penguin, or, Linux and "The Nature of the Firm."] The Yale Law Journal, 112(3), 369.


== Week 15: Networked racism ==


== Week 13: Errors and Ethics ==
November 30


====April 12====
'''Assignment Due:'''
* Rough draft of [[/Final project|Final Project]] on Brightspace and sent to your "peers"


'''Readings (before class):'''


* Salkind Chapter 9, pp. 177-186
'''Readings:'''
* Fernandez, R. M., & Fernandez-Mateo, I. (2006). [https://journals-sagepub-com.ezproxy.lib.purdue.edu/doi/pdf/10.1177/000312240607100103 Networks, Race, and Hiring]. American Sociological Review, 71(1), 42–71. '''Read the introduction (pp. 42–47) and the Summary and Conclusion (pp. 65–67)'''
* Sunstein, C. R. (1991). Why markets don’t stop discrimination. Social Philosophy and Policy, 8(02), 22–37. https://doi.org/10.1017/S0265052500001114


'''Concepts:'''
* Type I and Type II errors
* Statistical power


====April 14====
December 2


Final project review + Q&A
No class - work on Final Project


====April 15====
== Week 16: Network Visualization Principles ==


'''No Lab: Workday for Final Project'''
December 7


'''Assignment Due:'''
'''Assignment Due:'''
* Lab 12
* Peer feedback on final project
 
== Week 14 ==
 
====April 19====
 
Review for SPSS Quiz 2
 
====April 21====
 
Open Topic: Buffer Day / Out-of-class workday
 
====April 22====
 
'''SPSS Quiz 2'''


== Week 15 ==
'''Class Schedule:'''
* Review principles of good network visualizations
** Put examples at https://padlet.com/jdfoote1/networks (I will explain in class)
* Work on final projects




December 9


====April 26====
No class - work on Final Project


Out-of-class work day for final project
== Week 16.5: Finals week  ==


====April 28====
Review for Final exam


'''Assignment Due:'''
'''Assignment Due:'''
* '''Final Project'''
* [[Communication and Social Networks (Fall 2021)/Final project|Final Project]] - Due Wednesday, December 15
 
* Turn in your [[Final self reflection]] on Brightspace
====April 29====


'''No Lab'''


== Week 16: Final Exam ==
<!-- Bikerack


May 5, 1:00 pm - 3:00 pm
* Skim [https://kateto.net/network-visualization Static and dynamic network visualization with R] by Katya Ognyanova
* Show family networks
* Introduction to RStudio
** R files - Download [https://raw.githubusercontent.com/jdfoote/Communication-and-Social-Networks/master/activities/r_example.R example file here].
** R Notebook files - Download [https://raw.githubusercontent.com/jdfoote/Communication-and-Social-Networks/master/activities/r_markdown_example.Rmd example file here].
* Start [https://campus.datacamp.com/courses/network-analysis-in-r/ Network Analysis in R], chapter 1
* Use R to create an accurate network image of the family network you created for Homework #3.  Include node labels for each family member.
** If you get stuck, [https://youtu.be/isBm5RTslow this video] may help.
** Use [https://kateto.net/network-visualization Static and dynamic network visualization with R] to figure out how to make it look nice!
* Troubled Lands Activity
* Answer questions about DataCamp
* Review principles of good network visualizations
* Find and assess networks visualizations ([https://padlet.com/jdfoote1/networks padlet is here])
* Begin visualization challenge
** Right click on [https://github.com/jdfoote/Communication-and-Social-Networks/raw/fall-2021/activities/network_visualization_examples_and_assignment.Rmd THIS LINK], save it, and open it in RStudio.
* [https://github.com/jdfoote/Communication-and-Social-Networks/raw/fall-2021/week_10/lecture/ Slides]
* [https://youtu.be/5EOHaU_R94o Weekly lecture] on social influence and network diffusion
* [https://youtu.be/sdI-b5mfjH4 Interview with Josh Becker] (skim his article below first).
* [https://youtu.be/d3C2r7gPfBU Great video about homophily in networks]
* [https://youtu.be/MzA12DkQGBw Answering questions about R]
* [https://github.com/jdfoote/Communication-and-Social-Networks/raw/fall-2021/activities/school_data_example.Rmd Example with code for the Dutch School assignment]
* [https://www.youtube.com/watch?v=prCmVEUTxQE Video explaining my example]
* [https://youtu.be/mOtVC0N-ItA Networks in Organizations lecture]
-->


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