Editing Intro to Programming and Data Science (Summer 2020)
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= Course Information = | = Course Information = | ||
:'''COM | :'''COM 574: Introduction to Programming and Data Science''' | ||
:'''Location:''' https://meet.jit.si/COM674 | :'''Location:''' https://meet.jit.si/COM674 | ||
:'''Class Hours:''' M-F, | :'''Class Hours:''' M-F, 1-3pm | ||
== Instructor == | == Instructor == | ||
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* Required text: '''[https://www.py4e.com/book Python for Everybody]''' by Charles R. Severance. The book is [https://creativecommons.org/licenses/by/3.0/us/ freely licensed] and available online for free. You can also buy the book if you prefer a hard copy. | * Required text: '''[https://www.py4e.com/book Python for Everybody]''' by Charles R. Severance. The book is [https://creativecommons.org/licenses/by/3.0/us/ freely licensed] and available online for free. You can also buy the book if you prefer a hard copy. | ||
I will list required chapters in the | I will list required chapters in the weekly notes below. In general, you should expect to spend far more time working on programming tasks than reading. Much like math or other technical courses, this course will build on itself every week. You should make every effort to cover the reading and exercise material every week in preparation for the next week. | ||
* Other readings: Throughout the | * Other readings: Throughout the year we will read and discuss examples of computational social science that I find particularly well done or interesting. Many are available through the Purdue library. I will put the rest on Brightspace. If you come across additional examples that you think the class would benefit from, please suggest them to me. | ||
* Optional readings: Matthew Salganik's book 'Bit by Bit: Social Research in the Digital Age' is a wonderful introduction to computational social science. We will not be discussing it in class but I highly recommend it. | * Optional readings: Matthew Salganik's book 'Bit by Bit: Social Research in the Digital Age' is a wonderful introduction to computational social science. We will not be discussing it in class but I highly recommend it. | ||
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# 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 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. | ||
# 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 == | == Office hours and email == | ||
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= Assignments = | = Assignments = | ||
The main outcome of this course will be a research project exploring a social science question using Python, and the bulk of your grade will be based on that project. I prefer that you do projects on your own but it may be possible to work as a small team (maximum 3 people). Team projects are expected to be more ambitious than individual projects. Preliminary assignments will help you to develop your idea and to get feedback from me and others. | |||
There will also be weekly programming assignments that I will ask you to hand in but which will only be graded as complete/incomplete. I will randomly sample from the assignments to make sure that people are understanding the topics and I will randomly choose students to share their responses to exercises as an extra way to incentivize you to complete them. | |||
== Research project == | == Research project == | ||
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As a demonstration of your learning in this course, you will design and carry out a quantitative research project, start to finish. This means you will all: | As a demonstration of your learning in this course, you will design and carry out a quantitative research project, start to finish. This means you will all: | ||
* '''Design and describe a plan for a study''' — The study you design should involve quantitative analysis and should be something you can complete at least a first pass on during this | * '''Design and describe a plan for a study''' — The study you design should involve quantitative analysis and should be something you can complete at least a first pass on during this semester. | ||
* '''Find a dataset''' — You should | * '''Find a dataset''' — You should quickly identify a dataset you will use to complete this project. | ||
* ''' | * '''Report and interpret your findings''' — You will do this in both a short paper and a short presentation. | ||
* '''Ensure that your work is replicable''' — You will need to provide code and data for your analysis in a way that makes your work replicable by other researchers. | * '''Ensure that your work is replicable''' — You will need to provide code and data for your analysis in a way that makes your work replicable by other researchers. | ||
''I strongly urge you'' to produce a project that will further your academic career outside of the class. There are many ways that this can happen. Some obvious options are to prepare a project that you can submit for publication, that you can use as pilot analysis that you can report in a grant or thesis proposal, and/or that fulfills a degree requirement | ''I strongly urge you'' to produce a project that will further your academic career outside of the class. There are many ways that this can happen. Some obvious options are to prepare a project that you can submit for publication, that you can use as pilot analysis that you can report in a grant or thesis proposal, and/or that fulfills a degree requirement. | ||
There are several intermediate milestones and deadlines to help you accomplish a successful research project. Unless otherwise noted, all deliverables should be submitted via Brightspace. | There are several intermediate milestones and deadlines to help you accomplish a successful research project. Unless otherwise noted, all deliverables should be submitted via Brightspace. | ||
=== Project | === Project plan and dataset identification === | ||
;Due date: | ;Due date: January 28, 2020 | ||
;Maximum length: 500 words (~1-2 pages) | ;Maximum length: 500 words (~1-2 pages) | ||
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* An abstract of the proposed study including the topic, research question, theoretical motivation, object(s) of study, and anticipated research contribution. | * An abstract of the proposed study including the topic, research question, theoretical motivation, object(s) of study, and anticipated research contribution. | ||
* An identification of the dataset you will use and a description of the columns or type of data it will include. If you do not currently have access to these data, explain why and when you will. | * An identification of the dataset you will use and a description of the columns or type of data it will include. If you do not currently have access to these data, explain why and when you will. | ||
* A short (several sentences) description of how the project will fit into your career trajectory. | * A short (several sentences?) description of how the project will fit into your career trajectory. | ||
=== Project planning document === | === Project planning document === | ||
;Due date: | ;Due date: Thursday, March 10, 2020 | ||
;Maximum length: ~ | ;Maximum length: ~5 pages | ||
The project planning document is a basic shell/outline of an empirical quantitative research paper. The planning document should focus around three big questions: | The project planning document is a basic shell/outline of an empirical quantitative research paper. The planning document should focus around three big questions: | ||
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One approach that I have found helpful is outlined [[CommunityData:Planning document|on this wiki page]]. | One approach that I have found helpful is outlined [[CommunityData:Planning document|on this wiki page]]. | ||
=== Project presentation and | === Project presentation and paper === | ||
; | ;Paper due date: May 5, 2020 | ||
;Maximum length: | ;Maximum length: 4500 words (~18 pages) | ||
;Presentation due date: | ;Presentation due date: April 28, 2020 | ||
;Maximum length: 8 minutes | ;Maximum length: 8 minutes | ||
==== The | ==== The paper ==== | ||
Ideally, I expect you to produce a high quality short research paper that you might revise and submit for publication. I do not expect the paper to be ready for publication, but it should contain polished drafts of all the necessary components of a scholarly quantitative empirical research study. In terms of the structure, please see the page on the [[structure of a quantitative empirical research paper]]. | |||
As noted above, you should also provide data, code, and any documentation sufficient to enable the replication of all analysis and visualizations. If that is not possible/appropriate for some reason, please talk to me so that we can find another solution. | |||
Because the emphasis in this class is on methods and because I'm not an expert in each of your fields, I'm happy to assume that your paper, proposal, or thesis chapter has already established the relevance and significance of your study and has a comprehensive literature review, well-grounded conceptual approach, and compelling reason why this research is important. As a result, you need not focus on these elements of the work in your written submission. Instead, feel free to start with a brief summary of the purpose and importance of this research followed by an introduction of your research questions or hypotheses. If you provide more detail, that's fine, but I won't give you detailed feedback on these parts and they will not figure prominently in my assessment of the work. | Because the emphasis in this class is on methods and because I'm not an expert in each of your fields, I'm happy to assume that your paper, proposal, or thesis chapter has already established the relevance and significance of your study and has a comprehensive literature review, well-grounded conceptual approach, and compelling reason why this research is important. As a result, you need not focus on these elements of the work in your written submission. Instead, feel free to start with a brief summary of the purpose and importance of this research followed by an introduction of your research questions or hypotheses. If you provide more detail, that's fine, but I won't give you detailed feedback on these parts and they will not figure prominently in my assessment of the work. | ||
I do not have strong preferences about the style or formatting guidelines you follow for the paper and its bibliography. However, ''your paper must follow a standard format'' (e.g., [https://cscw.acm.org/2019/submit-papers.html ACM SIGCHI CSCW format] or [https://www.apastyle.org/index APA 6th edition] ([https://templates.office.com/en-us/APA-style-report-6th-edition-TM03982351 Word] and [https://www.overleaf.com/latex/templates/sample-apa-paper/fswjbwygndyq LaTeX] templates)) that is applicable for a peer-reviewed journal or conference proceedings in which you aim to publish the work (they all have formatting or submission guidelines published online and you should follow them). This includes the references. I also strongly recommend that you use reference management software to handle your bibliographic sources. | |||
I am also open to projects that are in the form of a Jupyter notebook, but I expect the same sorts of content to be present. | |||
==== The presentation ==== | ==== The presentation ==== | ||
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The presentation will provide an opportunity to share a brief summary of your project and findings with the other members of the class. However, don't treat it as a comprehensive overview of your paper: I would rather you tell a subset of the story well than the whole story in a rushed fashion. For instance, you can give a completely successful presentation by describing the motivation and walking through one plot in your paper. Since you will all give other research presentations throughout your career, I strongly encourage you to take the opportunity to refine your academic presentation skills. | The presentation will provide an opportunity to share a brief summary of your project and findings with the other members of the class. However, don't treat it as a comprehensive overview of your paper: I would rather you tell a subset of the story well than the whole story in a rushed fashion. For instance, you can give a completely successful presentation by describing the motivation and walking through one plot in your paper. Since you will all give other research presentations throughout your career, I strongly encourage you to take the opportunity to refine your academic presentation skills. | ||
All presentations will need to be ''a maximum of 8 minutes long'' with additional 2-3 minutes for questions and answers. Concisely communicating an idea in the time allotted is an important skill in its own right. | |||
== | == Participation == | ||
The course relies heavily on participation. The material we're going to be covering is difficult and we're going to be covering it quickly. It is going to be very difficult to make up any missed classes. Attendance will be the most important part of participation and missing more than 1 class is going to make it extremely difficult to excel in our class. | |||
Nearly every week, we will begin by discussing challenges and problem sets. Please speak up and engage in this part of the class as well as asking questions anytime there is anything confusing. If you are feel confused about a new Python concept, it's highly unlikely that you are the only one. If there is anything I can do to help you participate in class, please let me know in the anonymous feedback. | |||
In general, my teaching style is more conversational than a formal lecture. I prefer that students feel they can "politely interrupt" at any time to seek clarification or make a well-informed point, and we keep the class small to encourage this. | |||
== Weekly Coding Challenges == | |||
I will | Most weeks I will give you all a set of weekly coding challenges before the end of class that will involve writing code or adding to code that I've given you. These coding challenges will be turned in on Brightspace but will not be graded. I encourage you to work together on these challenges but to make sure that you understand the concepts yourself. | ||
I will share my solutions to each of the coding challenges in the subsequent class or via email. As you will see over the course of the semester, there are many possible solutions to many programming problems and my own approaches will often be different than yours. That's completely fine! Coding is a creative act! | |||
You are welcome to discuss the exercises on our Brightspace discussion board but please do not share answers to challenges more than 24 hours before they are due. After that, you are welcome and encouraged to share your solutions and/or to discuss different approaches. We will discuss a few of the exercises during class and I will randomly choose a few students to explain their solutions. | |||
== Reflection papers == | == Reflection papers == | ||
As discussed in more detail [[#Grades|below]], | As discussed in more detail [[#Grades|below]], four times during the course I will ask you to respond to a set of reflection questions. These questions are intended to help you to think about what you have learned and accomplished and to craft goals for the remainder of the course. They are also an important way for me to gather feedback about how the course is going so that I can adjust. | ||
= Grades = | = Grades = | ||
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= Schedule = | = Schedule = | ||
'''NOTE''' | '''NOTE''' This section will be modified throughout the course to meet the class's needs. Check back in often. | ||
== Day 1: | == Day 1: Introductions and getting started (May 18) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
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'''Required Readings:''' | '''Required Readings:''' | ||
* | * None | ||
''' | '''Class Schedule:''' | ||
* Class overview and expectations — We'll walk through this syllabus. | * Class overview and expectations — We'll walk through this syllabus. | ||
* [[ | * [[Intro to Programming and Data Science (Summer 2020)/Day_1_Exercise|Day 1 Exercise]] — You'll install software including the Python programming language and run through a series of exercises. | ||
* [ | * [[Intro to Programming and Data Science (Summer 2020)/Day_1_Tutorial|Day 1 Tutorial]] — You'll work through a self-guided tutorial introducing you to some basic programming concepts. | ||
'''By the end of class you will:''' | '''By the end of class you will:''' | ||
* Have a working python environment on your personal laptop. | * Have a working python environment on your personal laptop. | ||
* Have written your first program in the python language. | * Have written your first program in the python language. | ||
== Day 2: | |||
== Day 2: Computational thinking (May 19) == | |||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* Finish Day 1 exercises and tutorials | * Finish Day 1 exercises and tutorials | ||
* Fill out this [https:// | * Fill out this [https://forms.gle/FUjcYZsQKq1ecVax6 short survey] | ||
'''Readings (before class):''' | '''Readings (before class):''' | ||
* Python for Everybody, chapters 1- | * Python for Everybody, chapters 1-2 | ||
* Bit By bit, [https://www.bitbybitbook.com/en/1st-ed/introduction/ Introduction] | * Bit By bit, [https://www.bitbybitbook.com/en/1st-ed/introduction/ Introduction] | ||
''' | '''Class Schedule:''' | ||
'''Code Challenge:''' | '''Code Challenge:''' | ||
* [[Intro to Programming and Data Science (Summer 2020)/Day_2_Coding_Challenges|Day 2 Coding Challenge]] | * [[Intro to Programming and Data Science (Summer 2020)/Day_2_Coding_Challenges|Day 2 Coding Challenge]] | ||
== Day 3: | == Day 3: Conditionals and Functions (May 20) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* Final project | * Final project idea (turn in on Brightspace). | ||
* Finish [[Intro to Programming and Data Science (Summer 2020)/Day_2_Coding_Challenges|Day 2 Coding Challenge]] (turn in on Brightspace) | * Finish [[Intro to Programming and Data Science (Summer 2020)/Day_2_Coding_Challenges|Day 2 Coding Challenge]] (turn in on Brightspace) | ||
'''Readings:''' | '''Readings:''' | ||
* Python for Everybody | * Python for Everybody, chapters 3-4 | ||
* Foote, J., Shaw, A., & Hill, B.M. (2017). [https://jeremydfoote.com/files/foote_computational_2017.pdf Computational analysis of social media scholarship]. In Burgess, J., Poell, T., Marwick, A. (Eds.), The Sage Handbook of Social Media. Sage. | * Foote, J., Shaw, A., & Hill, B.M. (2017). [https://jeremydfoote.com/files/foote_computational_2017.pdf Computational analysis of social media scholarship]. In Burgess, J., Poell, T., Marwick, A. (Eds.), The Sage Handbook of Social Media. Sage. | ||
'''Agenda:''' | '''Agenda:''' | ||
* | * Discuss reading | ||
* Go over last day's assignment | * Go over last day's assignment | ||
* Introduce | * Introduce baby names project | ||
'''Coding Challenge''' | '''Coding Challenge''' | ||
* [[Intro to Programming and Data Science (Summer 2020)/Day 3 Coding Challenges|Day 3 Coding Challenges]] | * [[Intro to Programming and Data Science (Summer 2020)/Day 3 Coding Challenges|Day 3 Coding Challenges]] | ||
== Day 4: | == Day 4: Iteration, strings, and lists (May 21) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* [[Intro to Programming and Data Science (Summer 2020)/Day 3 Coding Challenges|Day 3 Coding Challenges]] | * [[Intro to Programming and Data Science (Summer 2020)/Day 3 Coding Challenges|Day 3 Coding Challenges]] | ||
'''Readings:''' | '''Readings:''' | ||
* Python for Everybody | |||
chapters_to_read = [5, 6, 8] | |||
* Nelson, Laura K. 2017. "[https://doi.org/10.1177%2F0049124117729703 Computational Grounded Theory: A Methodological Framework]." Sociological Methods and Research. | * Nelson, Laura K. 2017. "[https://doi.org/10.1177%2F0049124117729703 Computational Grounded Theory: A Methodological Framework]." Sociological Methods and Research. | ||
'''Agenda:''' | '''Agenda:''' | ||
* | * [[Intro to Programming and Data Science (Summer 2020)/Day 4 Coding Challenges|Day 4 Coding Challenges]] | ||
== Day 5: | == Day 5: Reading and writing files (May 22) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
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'''Readings:''' | '''Readings:''' | ||
* Margolin, D. B., Hannak, A., & Weber, I. (2018). [https://doi.org/10.1080/10584609.2017.1334018 Political Fact-Checking on Twitter: When Do Corrections Have an Effect?] Political Communication, 35(2), 196–219. | * Margolin, D. B., Hannak, A., & Weber, I. (2018). [https://doi.org/10.1080/10584609.2017.1334018 Political Fact-Checking on Twitter: When Do Corrections Have an Effect?] Political Communication, 35(2), 196–219. | ||
book = open('Python for Everybody', 'r') | |||
for chapter in book: | |||
if chapter = '7': | |||
read(chapter) | |||
book.close() | |||
'''Agenda:''' | '''Agenda:''' | ||
* | * Go over last day's assignment. | ||
* Spend time on [[Intro to Programming and Data Science (Summer 2020)/Day 5 Coding Challenges|Day 5 Coding Challenges]] | |||
* [ | |||
== Day 6: | == Day 6: Dictionaries (May 26) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
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'''Readings:''' | '''Readings:''' | ||
* Benefield, G. A., Shen, C., & Leavitt, A. (2016). [https://doi.org/10.1145/2818048.2819935 Virtual Team Networks: How Group Social Capital Affects Team Success in a Massively Multiplayer Online Game]. Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 679–690. | * Benefield, G. A., Shen, C., & Leavitt, A. (2016). [https://doi.org/10.1145/2818048.2819935 Virtual Team Networks: How Group Social Capital Affects Team Success in a Massively Multiplayer Online Game]. Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 679–690. | ||
** Discussant: | ** Discussant: | ||
* [https://www.youtube.com/watch?v=HW29067qVWk Intro to Jupyter Notebooks video] | |||
* Python for Everybody, chapters 9 and 10 | |||
'''Agenda:''' | '''Agenda:''' | ||
* | * Introduction to Jupyter notebooks | ||
* [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/ | * Dictionaries | ||
* Tuples | |||
* Network analysis | |||
* Begin work on [https://campus.datacamp.com/courses/intermediate-python-for-data-science DataCamp Intermediate Python], Chapters 1-3 | |||
* Start [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/blob/master/resources/exercises/week_6_exercises.ipynb Day 6 Coding Challenges] | |||
== Day 7: Dataframes and visualization | == Day 7: Dataframes and visualization (May 27) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* Finish Day 6 Coding Challenges | * Finish Day 6 Coding Challenges | ||
'''Readings:''' | '''Readings:''' | ||
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'''Agenda:''' | '''Agenda:''' | ||
* | * Introduction to data frames | ||
* [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/ | * We will be discussing this data set: https://hub.mph.in.gov/dataset/aries-crash-data-2007-2017/resource/cc90589c-72d8-4d92-a5fe-73254b555c73 | ||
* [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/blob/master/resources/exercises/week_7_exercises.ipynb Day 7 Coding Challenges] | |||
== Day 8: | == Day 8: Dataframes and visualizations (continued) (May 28) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* Second [[Self_Assessment_Reflection|self-assessment reflection]] is due. | |||
* Finish [https://campus.datacamp.com/courses/intermediate-python-for-data-science DataCamp Intermediate Python], Chapters 1-3 | |||
* Turn in Day 7 Coding Challenges | * Turn in Day 7 Coding Challenges | ||
'''Readings:''' | '''Readings:''' | ||
* Kieran Healy and James Moody (2014). “[https://doi.org/10.1146/annurev-soc-071312-145551 Data Visualization in Sociology].” American Review of Sociology. 40: 105-28. | * Kieran Healy and James Moody (2014). “[https://doi.org/10.1146/annurev-soc-071312-145551 Data Visualization in Sociology].” American Review of Sociology. 40: 105-28. | ||
** Discussant: | ** Discussant: | ||
'''Agenda:''' | '''Agenda:''' | ||
* Introduce the [https://2.python-requests.org/en/master/ requests] library | * Introduce the [https://2.python-requests.org/en/master/ requests] library | ||
* Discuss the main kinds of online data gathering: downloading, scraping, and APIs. | * Discuss the main kinds of online data gathering: downloading, scraping, and APIs. | ||
* [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/ | * [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/blob/master/resources/exercises/week_8_intro.ipynb Intro to APIs Notebook] | ||
* [ | * Spend time on [[Intro to Programming and Data Science (Summer 2020)/Day 8 Coding Challenges|Day 8 Coding Challenges]]. | ||
== Day 9: Collecting | == Day 9: Collecting data with APIs (May 29) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
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* First [[Self_Assessment_Reflection | self-assessment reflection]] is due (on Brightspace). | * First [[Self_Assessment_Reflection | self-assessment reflection]] is due (on Brightspace). | ||
* Project Planning Document Due | * Project Planning Document Due | ||
* Finish API Notebook | |||
* Start on Day 8 coding challenges (at least get the example code to run) | |||
'''Readings:''' | '''Readings:''' | ||
* Python for Everybody, Chapter 13 | * Python for Everybody, Chapter 13 | ||
* Vitak, J., Shilton, K., & Ashktorab, Z. (2016). [https://doi.org/10.1145/2818048.2820078 Beyond the Belmont Principles: Ethical Challenges, Practices, and Beliefs in the Online Data Research Community]. Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 941–953. | * Vitak, J., Shilton, K., & Ashktorab, Z. (2016). [https://doi.org/10.1145/2818048.2820078 Beyond the Belmont Principles: Ethical Challenges, Practices, and Beliefs in the Online Data Research Community]. Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 941–953. | ||
* (Optional) Williams, M. L., Burnap, P., & Sloan, L. (2017). [https://doi.org/10.1177/0038038517708140 Towards an Ethical Framework for Publishing Twitter Data in Social Research: Taking into Account Users’ Views, Online Context and Algorithmic Estimation]: Sociology. | * (Optional) Williams, M. L., Burnap, P., & Sloan, L. (2017). [https://doi.org/10.1177/0038038517708140 Towards an Ethical Framework for Publishing Twitter Data in Social Research: Taking into Account Users’ Views, Online Context and Algorithmic Estimation]: Sociology. | ||
* (Optional) Salganik, M. [https://www.bitbybitbook.com/en/1st-ed/ethics/ Ethics] chapter from Bit By Bit. | * (Optional) Salganik, M. [https://www.bitbybitbook.com/en/1st-ed/ethics/ Ethics] chapter from Bit By Bit. | ||
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'''Agenda:''' | '''Agenda:''' | ||
* | * Start [[Intro to Programming and Data Science (Summer 2020)/Twitter Assignment|Twitter API Assignment]] | ||
== March 17: SPRING BREAK == | |||
'''Spring Break: No Class''' | |||
Have a great Spring Break! | |||
== Day 10: | == Day 10: Cleaning data and operationalization (June 1) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* [[Intro to Programming and Data Science (Summer 2020)/ | * [[Intro to Programming and Data Science (Summer 2020)/Twitter Assignment|Twitter API Assignment]] | ||
* [[Intro to Programming and Data Science (Summer 2020)/Day | * As much of [[Intro to Programming and Data Science (Summer 2020)/Day 8 Coding Challenges|Day 8 Coding Challenges]] as you can get through | ||
'''Readings:''' | '''Readings:''' | ||
* Robert K. Merton. 1948. [https://www-jstor-org.ezproxy.lib.purdue.edu/stable/2087142?sid=primo&origin=crossref&seq=1#metadata_info_tab_contents The Bearing of Empirical Research Upon the Development of Social Theory]. American Sociological Review 13(5): 505-515. | |||
* Christopher A. Bail et al. 2018. [https://doi.org/10.1073/pnas.1804840115 Exposure to opposing views on social media can increase political polarization]. PNAS 115(37): 9216-9221 | * Christopher A. Bail et al. 2018. [https://doi.org/10.1073/pnas.1804840115 Exposure to opposing views on social media can increase political polarization]. PNAS 115(37): 9216-9221 | ||
** Discussant: | ** Discussant: | ||
'''Agenda:''' | '''Agenda:''' | ||
'''Resources:''' | '''Resources:''' | ||
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* [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/blob/master/resources/solutions/Twitter_answers.ipynb My answers to the Day 8 problems] | * [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/blob/master/resources/solutions/Twitter_answers.ipynb My answers to the Day 8 problems] | ||
== Day 11: Introduction to computational text analysis (June 2) == | |||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* [ | * [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/blob/master/resources/exercises/week_11_challenges.ipynb Day 11 Programming challenges] | ||
'''Readings:''' | '''Readings:''' | ||
* Sara Klingenstein, Tim Hitchcock, and Simon DeDeo. 2014. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4084475/ The civilizing process in London’s Old Baily]. Proceedings of the National Academy of Sciences 111(26): 9419-9424. | * Sara Klingenstein, Tim Hitchcock, and Simon DeDeo. 2014. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4084475/ The civilizing process in London’s Old Baily]. Proceedings of the National Academy of Sciences 111(26): 9419-9424. | ||
''' | '''Agenda:''' | ||
* [https:// | * [https://youtu.be/YYyfSc4CACY Lecture + intro to challenges] | ||
== Day 12: | == Day 12: Storing code and data (June 3) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* | * Third self-assessment reflection is due. | ||
* Put your Twitter project on Github and email me the URL | |||
'''Readings:''' | '''Readings:''' | ||
* DellaPosta, D., Shi, Y., & Macy, M. (2015). [https://doi.org/10.1086/681254 Why Do Liberals Drink Lattes]? American Journal of Sociology, 120(5), 1473–1511. | * DellaPosta, D., Shi, Y., & Macy, M. (2015). [https://doi.org/10.1086/681254 Why Do Liberals Drink Lattes]? American Journal of Sociology, 120(5), 1473–1511. | ||
** Discussant: | ** Discussant: | ||
'''Agenda:''' | '''Agenda:''' | ||
* | * We will learn about using the version control system Git and the Git hosting site Github | ||
'''Resources:''' | '''Resources:''' | ||
* [https://www.youtube.com/watch?v=SWYqp7iY_Tc Git & GitHub Crash Course For Beginners] - YouTube video (not by me) introducing Git and Github | * [https://www.youtube.com/watch?v=SWYqp7iY_Tc Git & GitHub Crash Course For Beginners] - YouTube video (not by me) introducing Git and Github | ||
* [https://learngitbranching.js.org/ Interactive git branching tutorial] | * [https://learngitbranching.js.org/ Interactive git branching tutorial] | ||
* [https://youtu.be/-_mjC3lAKL4 Data management] - My video | |||
* [ | |||
== Day 13: Statistical summaries and tests (June 4) == | == Day 13: Statistical summaries and tests (June 4) == | ||
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'''Assignment Due:''' | '''Assignment Due:''' | ||
* | * If you would like, try to apply some statistical tests to your API data | ||
'''Readings:''' | '''Readings:''' | ||
* Tan, C. (2018). [https://aaai.org/ocs/index.php/ICWSM/ICWSM18/paper/view/17811 Tracing community genealogy: How new communities emerge from the old]. Proceedings of the Twelfth International Conference on Web and Social Media (ICWSM ’18), 395–404. | * Tan, C. (2018). [https://aaai.org/ocs/index.php/ICWSM/ICWSM18/paper/view/17811 Tracing community genealogy: How new communities emerge from the old]. Proceedings of the Twelfth International Conference on Web and Social Media (ICWSM ’18), 395–404. | ||
'''Agenda:''' | '''Agenda:''' | ||
* [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/ | * [https://github.com/jdfoote/Intro-to-Programming-and-Data-Science/blob/master/resources/exercises/week-13-challenges.ipynb Day 13 Notebook] | ||
* [https://youtu.be/j8e8JPWAHr8 Video explanation of notebook | * [https://youtu.be/j8e8JPWAHr8 Video explanation of notebook] | ||
== Day 14: Screen scraping (June 5) == | == Day 14: Screen scraping (June 5) == | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* | * Response to reading on FlipGrid | ||
'''Readings:''' | '''Readings:''' | ||
* Shaw, A., & Hill, B. M. (2014). [https://doi.org/10.1111/jcom.12082 Laboratories of oligarchy? How the iron law extends to peer production]. Journal of Communication, 64(2), 215–238. | * Shaw, A., & Hill, B. M. (2014). [https://doi.org/10.1111/jcom.12082 Laboratories of oligarchy? How the iron law extends to peer production]. Journal of Communication, 64(2), 215–238. | ||
** Discussant: | ** Discussant: | ||
* [https://towardsdatascience.com/ethics-in-web-scraping-b96b18136f01 Ethics in Web Scraping] by James Densmore | * [https://towardsdatascience.com/ethics-in-web-scraping-b96b18136f01 Ethics in Web Scraping] by James Densmore | ||
'''Agenda:''' | '''Agenda:''' | ||
* If you are interested in doing web scraping, then look at this [https://github.com/CU-ITSS/Web-Data-Scraping-S2019 incredible mini-course on the topic]. It is all done with Jupyter Notebooks and you have all of the prerequisite knowledge to understand it. | * If you are interested in doing web scraping, then look at this [https://github.com/CU-ITSS/Web-Data-Scraping-S2019 incredible mini-course on the topic]. It is all done with Jupyter Notebooks and you have all of the prerequisite knowledge to understand it. | ||
* [https://youtu.be/daUuC-PMZc4 Very brief lecture on web scraping | * [https://youtu.be/daUuC-PMZc4 Very brief lecture on web scraping]. | ||
== Day 15-17: Work on final project (June 8-10) == | == Day 15-17: Work on final project (June 8-10) == | ||
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'''Agenda:''' | '''Agenda:''' | ||
* I will be available to answer questions and provide help | * I will be available to answer questions and provide help | ||
== Day 18: Final project presentation (June 11) == | == Day 18: Final project presentation (June 11) == | ||
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'''Assignment Due:''' | '''Assignment Due:''' | ||
* Final project presentations | * Final project presentations | ||
* Prepare a presentation and post it on | * Prepare a presentation and post it on FlipGrid | ||
'''Readings:''' | '''Readings:''' | ||
Line 515: | Line 471: | ||
'''Assignment Due:''' | '''Assignment Due:''' | ||
* Final paper due | * Final paper due | ||
* | * Self reflection due | ||
= Administrative Notes = | = Administrative Notes = |