Data Into Insights (Spring 2021): Difference between revisions

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(Initializing schedule)
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# Understand the role of narrative in interpreting and producing data analyses
# Understand the role of narrative in interpreting and producing data analyses
# Competently import, process, and prepare data from analysis in the [https://www.r-project.org/ R programming language]
# Competently import, process, and prepare data from analysis in the [https://www.r-project.org/ R programming language]
# Crititcally analyze data visualizations and presentations, and recognize poor or misleading visualizations
# Critically analyze data visualizations and presentations, and recognize poor or misleading visualizations
# Produce beautiful, well-designed data visualizations in R using [https://ggplot2.tidyverse.org/ ggplot2]
# Produce beautiful, well-designed data visualizations in R using [https://ggplot2.tidyverse.org/ ggplot2]
# Craft compelling data presentations
# Craft compelling data presentations
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This is a data analysis class and you will need access to a decent computer. 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.
This is a data analysis class and you will need access to a decent computer. 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.


<!--
 
== Readings ==
== Readings ==


* Required text: '''[https://smile.amazon.com/Six-Degrees-Science-Connected-Market Six Degrees: The Science of a Connected Age]''' by Duncan Watts. I will list required chapters in the weekly notes below.
* Required texts:
**  '''Data Visualization: A Practical Introduction''' by Kieran Healy. [https://socviz.co/index.html Web version (free!)] or [https://amzn.to/2vfAixM Print version (Amazon)]
** '''R for Data Science''' by Hadley Wickham and Garrett Grolemund. [https://r4ds.had.co.nz/index.html Web version (free!)] or [http://amzn.to/2aHLAQ1 Print version (Amazon)]
** ''Effective Data Storytelling''' by Brent Dykes. [https://smile.amazon.com/dp/1119615712 Print version (Amazon)]


* Other readings: Other readings will be made available on Blackboard.
* Other readings: Other readings will be made available on Brightspace.
 
== Additional readings and resources ==
 
* Barabasi, A-­‐L. (2002). Linked: The new science of networks. Cambridge, MA: Perseus.
* Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. Riverside, CA: University of California, Riverside (available at http://faculty.ucr.edu/~hanneman/nettext/)
* Scott, J. (2000). Social network analysis: A handbook (2nd edition). London: Sage Publications.  




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# 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.
# 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.
# Closely monitor your email. 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 that will be emailed to everybody in the class.
# Closely monitor the class [https://discord.gg/qm7uU2dZyW 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.
# I will ask the class for voluntary anonymous feedback frequently. 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.


== Office hours and email ==
== Class Sessions ==


* I will hold office hours Thursday afternoons and by appointment. 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 at least two classmates. 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.
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.
* 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 (~9-5) but during the week I will generally respond within 24 hours.
 
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.
 
The Thursday meetings will be more like a lab. Some of these sessions will include synchronous activities but they will often be more of a co-working time, where you can work synchronously on assignments and I can be available to answer questions.
 
== Office Hours ==
 
I will also hold office hours Thursday afternoons on Discord. 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 (e.g., on Discord). 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 keep an eye on Discord during normal business hours. 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.


= Assignments =
= Assignments =
''Note'': Edited after the move to online classes to remove second exam and explain final project.


There will be multiple types of assignments, designed to encourage learning in different ways.
There will be multiple types of assignments, designed to encourage learning in different ways.
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== Participation ==
== 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.
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.
This also includes doing the readings and watching the videos. 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.


I will also create discussion spaces on Brightspace. I encourage you to use that space to discuss the readings and homeworks. I know that some people prefer text communication to talking in class and I expect those who are quieter in class to be more active on Brightspace.
You will also be required to submit 1-2 discussion questions on Discord before our Tuesday sessions.


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


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.
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 based on learning and developing proficiency in visualizing data in R.


== Exams ==
== Exams ==


There will be one in-class exam, approximately one-third through the semester. It will assess your understanding of core communication and social networks concepts.
There will be one in-class exam. It will assess your understanding of core concepts around storytelling and visualization.


'''NOTE''': Before the move to online classes, there were two exams. The points from the second exam will not be moved to the final project.


== Final Project ==
== Final Project ==


Students will work on a [[Communication_and_Social_Networks_(Spring_2020)/Final project|Final Project]] that explains how network analysis and a network approach can benefit an organization.
The main outcome of this course will be your final project, which will be a data presentation, either as a website or a slide deck + presentation. A detailed description of the project is [[Data_Into_Insights_(Spring_2021)/Final project|at this link]].
 
There will be a number of intermediate assignments through the semester to help you to identify a dataset, explore the data for insights, and get and give feedback on visualizations and story elements.


I made a [https://www.youtube.com/watch?v=S3eX8Jn2dJI video explaining the project].


= Grades =
= Grades =


Most of 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. The university still requires grades, so you will be leading the evaluation of your work. This will be completed with me in four stages, at the end of weeks 4, 8, 12, 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.
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.
 
The university still requires grades, so you will be leading the evaluation of your work. This will be completed with me in four stages, at the end of weeks 4, 8, 12, 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.


We will use the following rubric in our assessment:
We will use the following rubric in our assessment:
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* 20%: class participation, including attendance and participation in discussions and group work
* 20%: class participation, including attendance and participation in discussions and group work
* 20%: Labs and homework assignments
* 20%: Labs and homework assignments
* 30%: Exam
* 25%: Exam
* 30%: Final Project
* 35%: Final Project


The exam will be graded like a normal exam and the score will make up 30% of your grade. For the rest of the assignments (and the other 70% of your grade), I will provide feedback which will inform an ongoing conversation about your work.
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.


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


A: Reflects work the exceeds expectations on multiple fronts and to a great degree. Students reaching this level of achievement will:
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.
* Do what it takes to learn the principles and techniques of data storytelling, including looking to outside sources if necessary.
* Engage thoughtfully with an ambitious final project.
* Engage thoughtfully with an ambitious final project.
* Take intellectual risks, offering interpretations based on synthesizing material and asking for feedback from peers.
* 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.
* Share work early allowing extra time for engagement with others.
* Write reflections that grapple meaningfully with lessons learned as well as challenges.
* Write reflections that grapple meaningfully with lessons learned as well as challenges.
* Complete most, if not all homework assignments at a high level.
* Complete all or nearly all homework assignments at a high level.


B: Reflects strong work. Work at this level will be of consistently high quality. Students reaching this level of achievement will:
B: Reflects strong work. Work at this level will be of consistently high quality. Students reaching this level of achievement will:
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* Not complete homework assignments or turn some in in a hasty or incomplete manner.
* Not complete homework assignments or turn some in in a hasty or incomplete manner.


D/F: These are reserved for cases in which students do not complete work or participate. Students may also be
D/F: These are reserved for cases in which students do not complete work or participate. Students may also be impeding the ability of others to learn.
impeding the ability of others to learn.


== Extra Credit for Participating in Research Studies ==
== Extra Credit for Participating in Research Studies ==
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== Week 1: Introductions and the network perspective ==
== Week 1: Introduction to Stories ==


[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/intro_week1/ Slides]
January 19
 
January 14


'''Assignment Due:'''  
'''Assignment Due:'''  
* None
* None


'''Required Readings:'''  
'''Readings (before class):'''  
* None
* None


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January 16
January 21


'''Assignment Due:'''  
'''Assignment Due:'''  
* Read the entire syllabus (this document)
* Read the entire syllabus (this document)
* Introduce yourself on our Brightspace discussion board
* Sign up for Discord and introduce yourself
* Take this very brief [https://forms.gle/xz7N8KQWo2T2L2f19 survey]
* Take this very brief [https://forms.gle/xz7N8KQWo2T2L2f19 survey]


'''Readings:'''  
'''Readings:'''  
* [https://books.google.com/books?id=2IIlOf_n43UC&lpg=PP1&pg=PP1#v=onepage&q&f=false Six Degrees, Preface and Chapter 1]
 


'''Class Schedule:'''
'''Class Schedule:'''
* Network simulation activity
 
* Start work on [[Communication and Social Networks (Spring 2020)/Homework 1|Homework 1]]


== Week 2: Small worlds and scale-free networks  ==
== Week 2: Small worlds and scale-free networks  ==


[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/small_worlds_week2/ Slides]


January 21
January 26


'''Assignment Due:'''  
'''Assignment Due:'''  
* [[Communication and Social Networks (Spring 2020)/Homework 1|Homework 1]]
 


'''Readings (before class):'''  
'''Readings (before class):'''  
* Six Degrees, Chapter 2
* Travers, J. and Milgram, S. (1969). [https://www.jstor.org/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://doi.org/10.1126/science.1081058 An Experimental Study of Search in Global Social Networks]. ''Science'', 301(5634), 827.


'''Class Schedule:'''
'''Class Schedule:'''
* Complex systems and networks
* Individual and collective behavior
** Go through [https://ncase.me/polygons/ Parable of the Polygons] by Nicky Case
* Small worlds




January 23
 
January 28


'''Assignment Due:'''  
'''Assignment Due:'''  


'''Readings:'''  
'''Readings:'''  
* Six Degrees, Chapter 3
 


'''Class Schedule:'''
'''Class Schedule:'''
* In class activity: [[Communication and Social Networks (Spring 2020)/Six Degrees of Wikipedia Activity|Six Degrees of Wikipedia]]
* Begin [[Communication and Social Networks (Spring 2020)/Social Search Assignment|Homework 2]]


== Week 3: Social network data and analysis ==
== Week 3: Social network data and analysis ==


[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/network_types_week3/ Slides]


January 28
February 2


'''Assignment Due:'''
'''Assignment Due:'''
* [[Communication and Social Networks (Spring 2020)/Social Search Assignment|Homework 2]]


'''Readings:'''  
'''Readings:'''  
* James M. Cook, [http://www.umasocialmedia.com/socialnetworks/wp-content/uploads/2016/08/WhatIsASocialNetwork.pdf What is a Social Network?]


'''Class Schedule:'''
'''Class Schedule:'''
* Using R for network analysis and visualization
* Start work on [[Communication and Social Networks (Spring 2020)/Extended Family Assignment|Homework 3]]




January 30
February 4


'''Assignment Due:'''
'''Assignment Due:'''
* Finish [[Communication and Social Networks (Spring 2020)/Extended Family Assignment|Homework 3]]
* Install R and RStudio on your computer if you want to use your computer instead of lab computers. [https://techvidvan.com/tutorials/install-r/ This tutorial] should help you to succeed.


'''Readings:'''  
'''Readings:'''  


'''Class Schedule:'''
'''Class Schedule:'''
* Work on [https://www.datacamp.com/courses/free-introduction-to-r Introduction to R], chapters 1-3


== Week 4: Continuing introduction to R ==
== Week 4: Continuing introduction to R ==


[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/learning_r_week_4/ Slides]


February 4
February 9


'''Assignment Due:'''
'''Assignment Due:'''
* Turn in your [[Self Assessment Reflection]] on Brightspace
* Finish [https://www.datacamp.com/courses/free-introduction-to-r Introduction to R], chapters 1-3




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'''Class Schedule:'''
'''Class Schedule:'''
* 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://www.datacamp.com/courses/free-introduction-to-r Introduction to R], chapters 4-5




February 6
February 11


'''Assignment Due:'''
'''Assignment Due:'''
* Finish [https://www.datacamp.com/courses/free-introduction-to-r Introduction to R], chapters 4-5




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'''Class Schedule:'''
'''Class Schedule:'''
* 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!


== Week 5: Density, centrality, and power ==
== Week 5: Density, centrality, and power ==


[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/centrality_week_5/ Slides]


February 11
February 16


'''Assignment Due:'''  
'''Assignment Due:'''  
* Finish Network Analysis in R, Chapter 1
* Turn in your best network visualization




'''Readings:'''
'''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].


'''Class Schedule:'''
'''Class Schedule:'''




February 13
February 18


'''Assignment Due:'''
'''Assignment Due:'''


'''Readings:'''
'''Readings:'''
* Holliday, Audrey, Campbell, & Moore, (2016). [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4898141/ Identifying well-connected opinion leaders for informal health promotion]


'''Class Schedule:'''
'''Class Schedule:'''
* Guest lecture by [https://cla.purdue.edu/directory/profiles/seungyoon-lee.html Seungyoon Lee]


== Week 6: Ego networks and mid-term ==
== Week 6: Ego networks and mid-term ==


[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/ego_nets_week_6/ Slides]


February 18
February 23


'''Assignment Due:'''  
'''Assignment Due:'''  


'''Readings:'''  
'''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). Core Discussion Networks of Americans. American Sociological Review, 52(1), 122–131. https://doi.org/10.2307/2095397


'''Class Schedule:'''
'''Class Schedule:'''
* Introduce ego networks
* Review for mid-term




February 20
February 25


'''In-class midterm exam'''


== Week 7: Social Capital, structural holes, and weak ties ==
== Week 7: Social Capital, structural holes, and weak ties ==
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[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/social_capital_week7/ Slides]
[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/social_capital_week7/ Slides]


February 25
March 2


'''Assignment Due:'''  
'''Assignment Due:'''  
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February 27
March 4


'''Assignment Due:'''  
'''Assignment Due:'''  
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[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/network_visualization_week8/ Slides]
[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/network_visualization_week8/ Slides]


March 3
March 9


'''Assignment Due:'''
'''Assignment Due:'''
* Turn in your [[Self Assessment Reflection]] on Brightspace
* Turn in your [[Self Assessment Reflection]] on Brightspace
* Troubled Lands reflection on Brightspace
 


'''Readings:'''  
'''Readings:'''  
* Freeman, L. C. (2000). [https://www.cmu.edu/joss/content/articles/volume1/Freeman.html Visualizing social networks]. Journal of social structure, 1(1), 4.
 
* Skim [https://kateto.net/network-visualization Static and dynamic network visualization with R] by Katya Ognyanova


'''Class Schedule:'''
'''Class Schedule:'''
* Finish discussion about social capital
* Guest lecture from [https://ryanjgallagher.github.io/ Ryan J. Gallagher]
* Introduce more advanced visualization methods in R
* Begin working through Chapters 2 and 3 [https://campus.datacamp.com/courses/network-analysis-in-r Network Analysis in R]




March 5
March 11


'''Assignment Due:'''  
'''Assignment Due:'''  


* Finish Chapters 2 and 3 of [https://campus.datacamp.com/courses/network-analysis-in-r Network Analysis in R]
 


'''Readings:'''  
'''Readings:'''  
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'''Class Schedule:'''
'''Class Schedule:'''
* 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/master/activities/network_visualization_examples_and_assignment.Rmd THIS LINK], save it, and open it in RStudio.


== Week 9: Tie formation and decay ==
== Week 9: Tie formation and decay ==


[https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/tie_formation_week_9/ Slides]


March 10
March 16 - READING DAY


'''Assignment Due:'''  
'''Assignment Due:'''  
* Summary and questions for Dr. Feld
* NONE
 
'''Readings:'''


* Feld, S. L. (1981). [https://www.jstor.org/stable/2778746 The focused organization of social ties]. American Journal of Sociology, 86(5), 1015–1035.
March 18
* Feld, S., Knighton, D., and McGail, A. (forthcoming). [https://purdue.brightspace.com/d2l/le/content/7389/viewContent/519954/View Reflections On 'The Focused Organization of Social Ties' And Its Implications For Bonding and Bridging]. In Personal Networks: Frontiers of Ego-Network Analysis. Edited by Mario Small, Ned Smith, Brea Perry, and Bernice Pescosolido. Oxford University Press.
 
'''Class Schedule:'''
* Guest lecture by Scott Feld
 
March 13


'''Assignment Due:'''  
'''Assignment Due:'''  
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'''Readings:'''  
'''Readings:'''  
* Monge, P. R., & Contractor, N. S. (2003). [https://purdue.brightspace.com/d2l/le/content/7389/Home Theories of communication networks]. Oxford, UK: Oxford University Press. (pp. 298--314) - On Brightspace under Content > Readings




'''Class Schedule:'''
'''Class Schedule:'''
* Review tie formation and decay
* Revisit R and network visualizations


== March 17, 19: SPRING BREAK ==


'''Spring Break: No Class'''
== Week 10: Social influence and diffusion ==


Have a great Spring Break!
March 23


= Online Schedule =
'''Assignment Due:'''


From now on, we will be moving to an online learning format. While I would love to do a video chat version of the class, I know that members of the class are now in different time zones, with different responsibilities and stresses. In order to allow the class to fit into your schedule, we are going to make all assignments asynchronous.
'''Readings:'''


The tentative plan is to have two things due every week: an assignment plus a video response on our [https://flipgrid.com/com411 Flipgrid page]. These will both be due by Friday (although I encourage you to stay engaged on FlipGrid and post videos as you work on things).
'''Class Schedule:'''
 
=== Slack ===


We're also going to be using Slack to communicate - please [https://join.slack.com/t/com114-2020/shared_invite/zt-d8tya9ma-7LQ7vJ8Safk3GH9XJscATQ Join our Slack channel] and ask your questions there.


 
March 25
=== Office Hours ===
 
I will hold virtual office hours Tuesdays and Thursdays from 1-2 pm at [https://meet.jit.si/JeremyOffice https://meet.jit.si/JeremyOffice]
 
== Week 10: Social influence and diffusion ==
 
March 27
 
'''Weekly lecture:'''
* [https://jeremydfoote.com/teaching/2020-spring/comm_and_soc_networks/diffusion_week_10/ 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).


'''Assignment Due:'''  
'''Assignment Due:'''  
* [[Communication and Social Networks (Spring 2020)/Dutch School Data Visualization challenge|Dutch School Data Visualization
Challenge]]
* Do [http://ncase.me/crowds/ The Wisdom or Madness of Crowds Simulation] and discuss on Flipgrid.


'''Readings:'''  
'''Readings:'''  
* Chapter 4, "[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.
* 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.
* [Optional] Centola, D., & Macy, M. (2007). [https://doi.org/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). Social contagion theory: Examining dynamic social networks and human behavior. Statistics in Medicine, 32, 556–577.


'''Other Resources:'''
'''Class Schedule:'''
* [https://youtu.be/d3C2r7gPfBU Great video about homophily in networks]
 
* [https://youtu.be/D9XF0QOzWM0 Duncan Watts on Common Sense]
* [https://github.com/jdfoote/Communication-and-Social-Networks/raw/master/activities/school_data_example.Rmd Example with code for the Dutch School assignment]
* [https://www.youtube.com/watch?v=prCmVEUTxQE Video explaining my example]


== Week 11: Cliques, clans, and groups in networks ==
== Week 11: Cliques, clans, and groups in networks ==


April 3
March 30


'''Weekly lecture:'''
'''Weekly lecture:'''
* [https://youtu.be/6cIe5qSRoSE Groups and communities]; Also goes over the assignment (no slides)


'''Assignment Due:'''
'''Assignment Due:'''
* [https://github.com/jdfoote/Communication-and-Social-Networks/raw/master/activities/groups_in_networks.Rmd Finding and visualizing groups in networks] (Right-click, save, and open in RStudio). I go over the document in the YouTube video.
* Flipgrid response


'''Readings:'''
'''Readings:'''
* Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. [https://faculty.ucr.edu/~hanneman/nettext/C11_Cliques.html Chapter 11: Cliques and sub-groups]


'''Other Resources:'''
April 1


'''Assignment Due:'''
'''Readings:'''
'''Class Schedule:'''


== Week 12: Networks in organizations ==
== Week 12: Networks in organizations ==


April 10
April 6
 
'''Weekly Lecture:'''
* [https://youtu.be/mOtVC0N-ItA Networks in Organizations lecture]
* [https://youtu.be/MzA12DkQGBw Answering questions about R]


'''Assignment Due:'''
'''Assignment Due:'''
* Turn in your [[Self Assessment Reflection]] on Brightspace
* One paragraph summary of Krackhardt reading + 1 question about the reading
* Keep working on [https://github.com/jdfoote/Communication-and-Social-Networks/raw/master/activities/groups_in_networks.Rmd Groups in networks]; enhance your visualization of the Dutch school data by including community detection of some kind.


'''Readings:'''
'''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.
* (SKIM) Katz, N., Lazer, D., Arrow, H., & Contractor, N. (2004). [http://journals.sagepub.com/doi/10.1177/1046496404264941 Network theory and small groups]. Small Group Research, 35(3), 307–332.


== Week 13: The dark side of networks ==
== Week 13: The dark side of networks ==


April 17
April 13


[https://jeremydfoote.com/teaching/2020/comm_and_soc_networks/dark_side_week_13/#/ Slides]
READING DAY
 
 
April 15


'''Assignment Due:'''
'''Assignment Due:'''
* One paragraph summary of each reading + 1 question about each reading
* Talk about readings/concepts on FlipGrid
* Watch [https://youtu.be/sNR39Z9Tm3M this week's lecture]
* Keep working on the [[Communication_and_Social_Networks_(Spring_2020)/Final_project | final project]]


'''Readings:'''
'''Readings:'''
* Krebs, V. E. (2002). Mapping networks of terrorist cells. Connections, 24(3), 43–52.
* Kleinberg, J. (2007). The wireless epidemic. Nature, 449(7160), 287–288. https://doi.org/10.1038/449287a


== Week 14: Networks and technology ==
== Week 14: Networks and technology ==


April 24
April 20


[https://jeremydfoote.com/teaching/2020/comm_and_soc_networks/tech_and_networks_week_14 Slides]
'''Assignment Due:'''


'''Assignment Due:'''
* Watch [https://youtu.be/_cqjrGErPjA this week's lecture]
* Turn in reading summary on Brightspace


'''Readings:'''  
'''Readings:'''  
* Kleinberg, J. (2012). [https://doi.org/10.1007/978-3-642-29952-0_8 The Convergence of Social and Technological Networks]. In M. Agrawal, S. B. Cooper, & A. Li (Eds.), Theory and Applications of Models of Computation.


== Week 15: Networks and collaboration ==
== Week 15: Networks and collaboration ==


May 1
April 27


'''Assignment Due:'''  
'''Assignment Due:'''  
* Watch [https://youtu.be/xKzOrIHpnmI this week's lecture] ([https://jeremydfoote.com/teaching/2020/comm_and_soc_networks/networks_and_collaboration_week_15/ Slides])
 
* Turn in reading summary on Brightspace


'''Readings:'''  
'''Readings:'''  
* 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://doi.org/10.2307/1562247 Coase’s Penguin, or, Linux and "The Nature of the Firm."] The Yale Law Journal, 112(3), 369.


== Week 16: Finals week  ==
== Week 16: Finals week  ==
Line 544: Line 435:
'''Assignment Due:'''
'''Assignment Due:'''
* [[Communication and Social Networks (Spring 2020)/Final project|Final Project]] - Due Wednesday, May 6
* [[Communication and Social Networks (Spring 2020)/Final project|Final Project]] - Due Wednesday, May 6
* Turn in your [[Final self reflection]] on Brightspace - Due Friday, May 8
* Turn in your [[Final self reflection]] on Brightspace


= Administrative Notes =
= Administrative Notes =
Line 586: Line 477:


If you or someone you know is feeling overwhelmed, depressed, and/or in need of mental health support, services are available. For help, such individuals should contact Counseling and Psychological Services (CAPS) at 765-494-6995 during and after hours, on weekends and holidays, or by going to the CAPS office of the second floor of the Purdue University Student Health Center (PUSH) during business hours.
If you or someone you know is feeling overwhelmed, depressed, and/or in need of mental health support, services are available. For help, such individuals should contact Counseling and Psychological Services (CAPS) at 765-494-6995 during and after hours, on weekends and holidays, or by going to the CAPS office of the second floor of the Purdue University Student Health Center (PUSH) during business hours.
== Acknowledgements ==
I reached out to a number of network scholars for guidance with this syllabus. This version is based most strongly on the course taught by [https://www.cla.purdue.edu/directory/profiles/seungyoon-lee.html Seungyoon Lee], but I also received syllabi, materials, or ideas from [https://commstudies.utexas.edu/faculty/joshua-b-barbour Josh Barbour], [http://brooke-welles.squarespace.com/ Brooke Foucault-Welles], [http://www.katypearce.net/ Katy Pearce], and [https://dimenet.asc.upenn.edu/people/sgonzalezbailon/ Sandra González-Bailón].
I also drew from online resources, including James Cook's wonderful (and freely available) [http://www.umasocialmedia.com/socialnetworks/ social networks course] and Matt Salganik's [http://www.princeton.edu/~mjs3/soc204_s2017/ course materials].
-->

Revision as of 23:40, 18 December 2020

Course Information

COM 495/6/7: Turning Data into Insight and Stories
Location:
Class Hours: Tuesdays and Thursdays; 10:30-11:45am

Instructor

Instructor: Jeremy Foote
Email: jdfoote@purdue.edu
Office Hours: Thursdays; 3:00-5:00pm and by appointment


Course Overview and Learning Objectives

We are increasingly surrounded by data, and those with the technical skills to analyze it are highly sought after. Even more valuable are those who can not only identify insights from data, but can communicate and persuade with those insights. This course will focus on both developing data skills and crafting persuasive data stories.

Students who complete this course will be able to:

  1. Understand the role of narrative in interpreting and producing data analyses
  2. Competently import, process, and prepare data from analysis in the R programming language
  3. Critically analyze data visualizations and presentations, and recognize poor or misleading visualizations
  4. Produce beautiful, well-designed data visualizations in R using ggplot2
  5. Craft compelling data presentations

Required resources and texts

Laptop

This is a data analysis class and you will need access to a decent computer. 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.


Readings

  • Other readings: Other readings will be made available on Brightspace.


Course logistics

Note About This Syllabus

This is my first time teaching this course and this syllabus will be a dynamic document. 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:

  1. 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.
  2. Closely monitor the class 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.
  3. I will ask the class for voluntary anonymous feedback frequently. Please let me know what is working and what can be improved.

Class 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 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.

The Thursday meetings will be more like a lab. Some of these sessions will include synchronous activities but they will often be more of a co-working time, where you can work synchronously on assignments and I can be available to answer questions.

Office Hours

I will also hold office hours Thursday afternoons on Discord. 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 (e.g., on Discord). This policy lets me have time to help more students, but it's also a useful strategy. Often just trying to explain your code can help you to recognize where you've gone wrong.

I will also keep an eye on Discord during normal business hours. 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 jdfoote@purdue.edu. I try hard to maintain a boundary between work and home and I typically respond only on weekdays during business hours.

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.

This also includes doing the readings and watching the videos. 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.

You will also be required to submit 1-2 discussion questions on Discord before our Tuesday sessions.

Homework/Labs

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 based on learning and developing proficiency in visualizing data in R.

Exams

There will be one in-class exam. It will assess your understanding of core concepts around storytelling and visualization.


Final Project

The main outcome of this course will be your final project, which will be a data presentation, either as a website or a slide deck + presentation. A detailed description of the project is at this link.

There will be a number of intermediate assignments through the semester to help you to identify a dataset, explore the data for insights, and get and give feedback on visualizations and story elements.


Grades

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.

The university still requires grades, so you will be leading the evaluation of your work. This will be completed with me in four stages, at the end of weeks 4, 8, 12, and 16. In each stage, you will use 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.

We will use the following rubric in our assessment:

  • 20%: class participation, including attendance and participation in discussions and group work
  • 20%: Labs and homework assignments
  • 25%: Exam
  • 35%: Final Project

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.

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

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 data storytelling, 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.

B: Reflects strong work. Work at this level will be of consistently high quality. Students reaching this level of achievement will:

  • Be more safe or consistent than the work described above.
  • Ask meaningful questions of peers and engage them in fruitful discussion.
  • Exceed requirements, but in fairly straightforward ways - e.g., an additional post in discussion every week.
  • Compose complete and sufficiently detailed reflections.
  • Complete many of the homework assignments.

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.

D/F: These are reserved for cases in which students do not complete work or participate. Students may also be impeding the ability of others to learn.

Extra Credit for Participating in Research Studies

The Brian Lamb School of Communication uses an online program that expedites the process of recruiting, signing up, and granting extra credit to students for participating in research studies. The program is called the Research Participation System, and it provides an easy online method for you to sign up for research studies, to keep track of the studies you have completed, and to view how many credits you have earned for each study. You can access the system online at any time, from any computer with a standard web browser. By participating in studies done within the Brian Lamb School of Communication, you can learn first hand how a study is conducted, you can contribute to the advancement of the field, and you can improve your grade by earning extra credit.

  • You earn a ½ percent credit for every half-hour that you participate in a study. The maximum extra credit that you can earn for this course is 3%, which will be added to your total course points
  • If you sign up to participate in a study and fail to show up without canceling your appointment in advance (up to 2 hours before the study), you can be restricted from signing up for any studies for 30 days. You may quickly cancel your appointment online using the Research Participation System.
  • 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/.

Schedule

NOTE This section will be modified throughout the course to meet the class's needs. Check back in weekly.


Week 1: Introduction to Stories

January 19

Assignment Due:

  • None

Readings (before class):

  • None

Class Schedule:

  • Class overview and expectations — We'll walk through this syllabus.


January 21

Assignment Due:

  • Read the entire syllabus (this document)
  • Sign up for Discord and introduce yourself
  • Take this very brief survey

Readings:


Class Schedule:


Week 2: Small worlds and scale-free networks

January 26

Assignment Due:


Readings (before class):

Class Schedule:


January 28

Assignment Due:

Readings:


Class Schedule:

Week 3: Social network data and analysis

February 2

Assignment Due:

Readings:

Class Schedule:


February 4

Assignment Due:

Readings:

Class Schedule:

Week 4: Continuing introduction to R

February 9

Assignment Due:


Readings:


Class Schedule:


February 11

Assignment Due:


Readings:


Class Schedule:

Week 5: Density, centrality, and power

February 16

Assignment Due:


Readings:

Class Schedule:


February 18

Assignment Due:

Readings:

Class Schedule:

Week 6: Ego networks and mid-term

February 23

Assignment Due:

Readings:

Class Schedule:


February 25


Week 7: Social Capital, structural holes, and weak ties

Slides

March 2

Assignment Due:

Readings:

  • Granovetter, M. S. (1973). The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360–1380. https://doi.org/10.1086/225469
  • (Optional) Bourdieu, P. (1986). The forms of capital. In J. Richardson (Ed.) Handbook of Theory and Research for the Sociology of Education (New York, Greenwood), 241-258.

Class Schedule:


March 4

Assignment Due:

Readings:

Class Schedule:

  • Troubled Lands Activity


Week 8: More advanced network visualizations

Slides

March 9

Assignment Due:


Readings:


Class Schedule:


March 11

Assignment Due:


Readings:


Class Schedule:

Week 9: Tie formation and decay

March 16 - READING DAY

Assignment Due:

  • NONE

March 18

Assignment Due:


Readings:


Class Schedule:


Week 10: Social influence and diffusion

March 23

Assignment Due:

Readings:

Class Schedule:


March 25

Assignment Due:

Readings:

Class Schedule:


Week 11: Cliques, clans, and groups in networks

March 30

Weekly lecture:

Assignment Due:

Readings:

April 1

Assignment Due:

Readings:

Class Schedule:

Week 12: Networks in organizations

April 6

Assignment Due:

Readings:

Week 13: The dark side of networks

April 13

READING DAY


April 15

Assignment Due:

Readings:

Week 14: Networks and technology

April 20

Assignment Due:


Readings:

Week 15: Networks and collaboration

April 27

Assignment Due:


Readings:

Week 16: Finals week

Assignment Due:

Administrative Notes

Attendance Policy

Attendance is very important and it will be difficult to make up for any classes that are missed. It is expected that students communicate well in advance to faculty so that arrangements can be made for making up the work that was missed. It is the your responsibility to seek out support from classmates for notes, handouts, and other information.


Electronic Devices

I love technology and I study how technology can help us to collaborate and create. However, the research is increasingly clear that in a classroom setting technology can easily become more of a distraction than an aid. Cell phones fall clearly into this category. Unless you have a specific and vital need to be accessible by phone, please silence your phone and keep it put away.

Laptops can also be distracting, to you and to others. I strongly suggest that you take notes using pen and paper. Taking notes on a laptop is permitted but please refrain from using your laptop from non-class purposes (email, Facebook, shopping, etc.). Please close any applications which might be distracting.


Incomplete

A grade of incomplete (I) will be given only in unusual circumstances. The request must describe the circumstances, along with a proposed timeline for completing the course work. Submitting a request does not ensure that an incomplete grade will be granted. If granted, you will be required to fill out and sign an “Incomplete Contract” form that will be turned in with the course grades. Any requests made after the course is completed will not be considered for an incomplete grade.


Academic Integrity

While I encourage collaboration, I expect that any work that you submit is your own. Basic guidelines for Purdue students are outlined here but I expect you to be exemplary members of the academic community. Please get in touch if you have any questions or concerns.

Nondiscrimination

I strongly support Purdue's policy of nondiscrimination (below). If you feel like any member of our classroom--including me--is not living up to these principles, then please come and talk to me about it.

Purdue University is committed to maintaining a community which recognizes and values the inherent worth and dignity of every person; fosters tolerance, sensitivity, understanding, and mutual respect among its members; and encourages each individual to strive to reach his or her own potential. In pursuit of its goal of academic excellence, the University seeks to develop and nurture diversity. The University believes that diversity among its many members strengthens the institution, stimulates creativity, promotes the exchange of ideas, and enriches campus life.

Students with Disabilities

Purdue University strives to make learning experiences as accessible as possible. If you anticipate or experience physical or academic barriers based on disability, you are welcome to let me know so that we can discuss options. You are also encouraged to contact the Disability Resource Center at: drc@purdue.edu or by phone: 765-494-1247.

Emergency Preparation

In the event of a major campus emergency, I will update the requirements and deadlines as needed.

Mental Health

If you or someone you know is feeling overwhelmed, depressed, and/or in need of mental health support, services are available. For help, such individuals should contact Counseling and Psychological Services (CAPS) at 765-494-6995 during and after hours, on weekends and holidays, or by going to the CAPS office of the second floor of the Purdue University Student Health Center (PUSH) during business hours.