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# Project Proposal (10 points) | ||
# Final Paper (40 points) | ||
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**Produce a research question and proposal for your term project using a computational social science research design** | ||
**Turn in a formal research paper that uses advanced computational methods to answer a research question by Wednesday, June 12 at 11:59pm. The body of the paper should be no more than 20 pages (1.5 spaced). You may place as much information as you like in an appendix or technical appendix.** | ||
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## Elements of a project proposal | ||
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1. Clearly state a research question | ||
* Maybe give a few citations (not a full literature review) | ||
* Give a little information about why it is interesting | ||
* Give a little information about what your contribution will be | ||
2. Describe how you will answer that question | ||
* What data will you use? | ||
* Maybe give a preliminary figure/plot/table | ||
* What theory will you use to interpret the data? | ||
* What analyses and computational tools will you use? | ||
3. What do you think your answer might be? | ||
* What are the potential channels and alternatives? | ||
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## Proposal format | ||
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1. You should prepare a [5 minute quasi-Ignite-style presentation](http:https://www.ignitetalks.io/) using slides | ||
* Exactly **10 slides, auto-advancing every 30 seconds** | ||
* Use any software you want to generate the slides **as long as you include a PDF version** | ||
* Here is a [LaTeX slides template](https://github.com/UC-MACSS/persp-research-econ_Spr19/blob/master/templates/LaTeXslides_template.tex) you can use if you wish. | ||
2. Push your slides to your project repository on your GitHub fork in the `Proposal` folder no later than 11:59pm, Tuesday, April 9. | ||
3. You will present your proposal with slides in class on Wednesday, April 10. | ||
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## Things to watch out for | ||
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* State your research question clearly | ||
* Usually a narrower scope is better | ||
* Title should refer to a question | ||
* Make sure to use a computationally-enhanced research design | ||
* This could involve computational elements for data collection or statistical learning methods | ||
* This could involve running a digital survey or experiment or simulation | ||
* What you should not prepare - a basic OLS/logistic regression model reevaluating a commonly used observational data set. Do something more computationally cutting edge. | ||
* **Make sure you can get the data** | ||
* If you have a title slide, know that we will spend 30 seconds there | ||
* Manage your time during the presentation | ||
* Don't spend too much time on the literature | ||
* Answer questions but don't get derailed | ||
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## How to come up with a good project | ||
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* What topic areas are you interested in? | ||
* Read the most current articles. | ||
* Extend one of those papers in a small way. | ||
* New data | ||
* New population | ||
* Question about different part of the data | ||
* New/better methods | ||
* Talk to faculty. | ||
## Grading rubric | ||
1. Did you use appropriate advanced computational methods (10 points) | ||
2. Clarity of research question and convincingness of answer. (10 points) | ||
3. Effective use of visualizations and tables. (10 points) | ||
* Visualizations and tables should stand on their own. | ||
4. Overall paper organization (10 points) | ||
* Did you follow the paper writing advice for each of your sections as given in the course lectures, notes, examples, and slides. | ||
* Structure/flow | ||
* Parsimony and efficiency of language |
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