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| * Class overview and expectations — We'll walk through this syllabus. | | * Class overview and expectations — We'll walk through this syllabus. |
| * Make assignments for topic exploration | | * Make assignments for topic exploration |
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| '''Slides:'''
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| [https://jeremydfoote.com/computational_communication_resources/welcome_slides/lecture/welcome.html#/welcome-to-com-682 Welcome slides]
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| == Week 2: Reproducible Research I (May 23) == | | == Week 2: Reproducible Research I (May 23) == |
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| * Paper: Gentzkow M, Shapiro JM. Code and Data for the Social Sciences: A Practitioner's Guide; 2014. https://web.stanford.edu/~gentzkow/research/CodeAndData.pdf. | | * Paper: Gentzkow M, Shapiro JM. Code and Data for the Social Sciences: A Practitioner's Guide; 2014. https://web.stanford.edu/~gentzkow/research/CodeAndData.pdf. |
| * Video: [https://www.youtube.com/watch?v=4rBX6r5emgQ Reproducible Research: Concepts and Ideas]. Roger Peng. YouTube | | * Video: [https://www.youtube.com/watch?v=4rBX6r5emgQ Reproducible Research: Concepts and Ideas]. Roger Peng. YouTube |
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| '''Slides:'''
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| * [https://jeremydfoote.com/computational_communication_resources/reproducible_research/lecture/reproducible_research.html Week 2 and 3 slides]
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| * [https://purdue.brightspace.com/d2l/le/content/798129/viewContent/13239600/View Video of class meeting]
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| '''Resources:''' | | '''Resources:''' |
| * Blog post: [http://datasci.kitzes.com/lessons/python/reproducible_workflow.html Reproducible Workflows] by Justin Kitzes | | * Blog post: [http://datasci.kitzes.com/lessons/python/reproducible_workflow.html Reproducible Workflows] by Justin Kitzes |
| * [https://www.youtube.com/watch?v=r9PWnEmz_tc Introduction to Snakemake Tutorial (video)]
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| * [https://lachlandeer.github.io/snakemake-econ-r-tutorial/index.html An Introduction to Snakemake for social science]
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| * [https://www.youtube.com/watch?v=zqQM66uAig0 LaTeX introduction (video)]
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| * [https://www.overleaf.com/learn/latex/Knitr knitr introduction]
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| '''Slides:'''
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| * [https://jeremydfoote.com/computational_communication_resources/reproducible_research/lecture/reproducible_research.html Week 2 and 3 slides]
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| * [https://purdue.brightspace.com/d2l/le/content/798129/viewContent/13254014/View Video of class meeting]
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| === Reproducible analyses and papers === | | === Reproducible analyses and papers === |
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| * Make figure creation part of your workflow, have documents point to your figures directory | | * Make figure creation part of your workflow, have documents point to your figures directory |
| * Use citation management software that integrates with your document (use [https://www.zotero.org/ Zotero]) | | * Use citation management software that integrates with your document (use [https://www.zotero.org/ Zotero]) |
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| === Sharing === | | === Sharing === |
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| *** [https://snakemake.github.io/ Snakemake] | | *** [https://snakemake.github.io/ Snakemake] |
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| | | == Week 4: Computational text analysis: entity extraction, topic models (June 6) == |
| == Week 4: Computational text analysis: Introduction and Key Concepts (June 6) == | |
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| '''Resources:''' | | '''Resources:''' |
| Text As Data: A New Framework for Machine Learning and the Social Sciences (2022). Justin Grimmer, Margaret E. Roberts, and Brandon M. Stewart.
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| Read chapters 1-7
| | == Week 5: Computational text analysis: word embedding models (June 13) == |
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| == Week 5: Computational text analysis: Some "traditional" approaches (June 13) == | |
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| === Topic modeling ===
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| === Embeddings ===
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| '''Resources:''' | | '''Resources:''' |
| * [https://huggingface.co/blog/getting-started-with-embeddings Getting started with embeddings (Huggingface)]
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| === Classification ===
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| === Semantic networks ===
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| * [https://www.youtube.com/playlist?list=PLeo1K3hjS3uuvuAXhYjV2lMEShq2UYSwX NLP Tutorial Playlist Python (YouTube videos)]
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| == Week 6: Computational text analysis: using LLMs for research (June 20) == | | == Week 6: Computational text analysis: using LLMs for research (June 20) == |
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| '''Due:'''
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| * Final project proposal (details on Brightspace)
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| '''Resources:''' | | '''Resources:''' |
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| Intro to LLMs:
| | '''Agenda:''' |
| * [https://mark-riedl.medium.com/a-very-gentle-introduction-to-large-language-models-without-the-hype-5f67941fa59e Mark Riedl. A very gentle introduction to Large Language Models without the hype] | | * Discuss how things are working and a plan for the rest of the course. |
| * [https://www.youtube.com/watch?v=bSvTVREwSNw How ChatGPT Works Technically | ChatGPT Architecture (YouTube)]
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| * [https://amatriain.net/blog/transformer-models-an-introduction-and-catalog-2d1e9039f376/ Transformer Models: An introduction and catalog]
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| * [https://www.youtube.com/watch?v=iR2O2GPbB0E What are Large Language Models (LLMs)?]
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| Reflections on LLMs for research:
| | == Week 7: Share and discuss works-in-progress (June 27) == |
| * [https://arxiv.org/abs/2305.03514 Ziems, C., Held, W., Shaikh, O., Chen, J., Zhang, Z., & Yang, D. (2023). Can Large Language Models Transform Computational Social Science?. arXiv preprint arXiv:2305.03514.]
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| Papers using LLMs:
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| * [https://arxiv.org/abs/2304.03442 Park, J. S., O'Brien, J. C., Cai, C. J., Morris, M. R., Liang, P., & Bernstein, M. S. (2023). Generative agents: Interactive simulacra of human behavior. arXiv preprint arXiv:2304.03442.]
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| == Week 7: Share and discuss works-in-progress (June 27) ==
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| '''Assignment Due:''' [[Self_Assessment_Reflection | self-assessment reflection]] | | '''Assignment Due:''' [[Self_Assessment_Reflection | self-assessment reflection]] |
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| '''Topic Presentations:''' | | '''Resources:''' |
| * Juan Pablo (JP) Loaiza-Ramírez
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| *
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| '''Work-in-progress Presentations:'''
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| * Juan Pablo (JP) Loaiza-Ramírez
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| * Christina Walker
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| == Week 8: No class - July 4 == | | == Week 8: No class - July 4 == |
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| == Week 9: Share and discuss works-in-progress (July 11) == | | == Week 9: Share and discuss works-in-progress (July 11) == |
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| '''Topic Presentations:''' | | '''Students:''' |
| * Elizabeth Thompson
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| * Ryan Funkhouser
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| '''Work-in-progress Presentations:'''
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| * Dyuti Jha
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| == Week 10: Share and discuss works-in-progress (July 18) == | | == Week 10: Share and discuss works-in-progress (July 18) == |
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| '''Topic Presentations:''' | | '''Students:''' |
| * Christina Walker
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| * Hazel Chiu
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| '''Work-in-progress Presentations:'''
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| * Elizabeth Thompson
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| == Week 11: Share and discuss works-in-progress (July 25) == | | == Week 11: Share and discuss works-in-progress (July 25) == |
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| Visit from [https://sites.google.com/view/billrand/ Bill Rand], an expert in agent-based moedeling. | | Visit from [https://sites.google.com/view/billrand/ Bill Rand], an expert in agent-based moedeling. |
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| '''Topic Presentations:''' | | '''Students:''' |
| * Dyuti Jha
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| '''Work-in-progress Presentations:'''
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| * Hazel Chiu
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| == Week 12: Share and discuss works-in-progress (August 1) == | | == Week 12: Share and discuss works-in-progress (August 1) == |
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| '''Topic Presentations:''' | | '''Students:''' |
| * Muqing Liu
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| *
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| '''Work-in-progress Presentations:'''
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| * Ryan Funkhouser
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| * Muqing Liu
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| '''Assignment Due:''' | | '''Assignment Due:''' |
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| == Visualization in Python == | | == Visualization in Python == |
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| ===Resources added by Ryan===
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| '''Refresher/Basic resources'''
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| * Quick video overview: https://www.youtube.com/watch?v=a9UrKTVEeZA
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| * Longer, but still simple, video course outlining visualization techniques: https://www.simplilearn.com/tutorials/python-tutorial/data-visualization-in-python
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| * And of course, don't forget that one of the greatest resources for getting input on how to change visualizations is ChatGPT: https://chat.openai.com/
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| '''Understanding which visualization libraries to learn/use'''
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| * A useful academic article suggesting Matplotlib, Seaborn, and Plotly as the best: - https://ieeexplore.ieee.org/abstract/document/8757088?casa_token=REAm2SOC93MAAAAA:fCJHaTYgHA8FXZMbVEdZcevcXKsNJBBvB83F5HGgSEh504YPfROjnI08K1f2CJ1b6ZDVhhxF
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| * An excellent article on Medium about what use case scenarios are best for each of Matplotlib, Seaborn, and Plotly: https://medium.com/mlearning-ai/comparing-python-libraries-for-visualization-b2eb6c862542#:~:text=Matplotlib%20is%20a%20great%20choice,choice%20for%20creating%20interactive%20visualizations.
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| '''Matplotlib'''
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| * Excellent general overview: https://towardsdatascience.com/introduction-to-data-visualization-in-python-89a54c97fbed
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| * Great, more in-depth guide on how to really take visualizations to the next level: https://towardsdatascience.com/5-steps-to-build-beautiful-bar-charts-with-python-3691d434117a
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| * Documentation: https://matplotlib.org/stable/index.html
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| '''Seaborn'''
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| * Great overview of Seaborn: https://medium.com/insight-data/data-visualization-in-python-advanced-functionality-in-seaborn-20d217f1a9a6
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| * Third-party documentation-style site that helps make it really easy to figure out how to do each kind of visualization: https://www.geeksforgeeks.org/python-seaborn-tutorial/
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| * Documentation: https://seaborn.pydata.org/
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| '''Plotly'''
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| * Excellent quick overview of what Plotly can do and how to use it: https://towardsdatascience.com/the-next-level-of-data-visualization-in-python-dd6e99039d5e
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| * Third-party documentation-style site that helps make it really easy to figure out how to do each kind of visualization: https://www.geeksforgeeks.org/python-plotly-tutorial/
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| * Documentation: https://plotly.com/python/
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| '''Visualization for Exploratory Data Analysis'''
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| * Academic article that goes over objectives and processes for EDA using visualizations: https://www.researchgate.net/profile/Dr-Subhendu-Pani/publication/337146539_IJITEE/links/5dc70b124585151435fb427e/IJITEE.pdf
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| * Great article that shows how visualizations are really useful for EDA in even more NLP scenarios. For example, what are the distributions of sentiments?: - https://medium.com/towards-data-science/a-complete-exploratory-data-analysis-and-visualization-for-text-data-29fb1b96fb6a
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| * EDA applied to Machine Learning contexts: https://medium.com/open-machine-learning-course/open-machine-learning-course-topic-1-exploratory-data-analysis-with-pandas-de57880f1a68 and visualizations applied to machine learning contexts: https://medium.com/open-machine-learning-course/open-machine-learning-course-topic-2-visual-data-analysis-in-python-846b989675cd
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| * A gentle introduction to EDA: https://towardsdatascience.com/a-gentle-introduction-to-exploratory-data-analysis-f11d843b8184
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| == Advanced Pandas == | | == Advanced Pandas == |
| [https://pandas.pydata.org/pandas-docs/stable/index.html '''Pandas Documentation''']
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| [https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf '''Pandas Cheatsheet''']
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| '''Tutorials:'''
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| * [https://www.packtpub.com/product/pandas-1x-cookbook-second-edition/9781839213106 Pandas Cookbook]
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| * [https://tomaugspurger.net/posts/modern-1-intro/ Modern Pandas]
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| * [https://www.youtube.com/playlist?list=PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS Video Series of Tutorials]
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| * [https://wesmckinney.com/book/ Python for Data Analysis]
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| * [https://realpython.com/pandas-project-gradebook/ Make a Gradebook with Pandas]
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| * [https://jakevdp.github.io/PythonDataScienceHandbook/ Python Data Science Handbook]
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| '''GPT & Pandas:'''
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| * [https://www.sharpsightlabs.com/blog/gpt-writes-bad-pandas-code/ GPT Writes Horrible Pandas Code]
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| * [https://github.com/rvanasa/pandas-gpt Package to have GPT Write Good Pandas Code]
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| '''Extra:'''
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| [https://towardsdatascience.com/one-word-of-code-to-stop-using-pandas-so-slowly-793e0a81343c Make Pandas Run Faster with Swifter]
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| '''Class Tutorial:'''
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| '''[https://drive.google.com/file/d/162nO8u2Sr3bPOqoq8KLLhKR8OhmosGjJ/view?usp=sharing Jupyter Notebook]'''
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| == Agent-based modeling == | | == Agent-based modeling == |
| | | Juan Pablo (JP) Loaiza-Ramírez |
| '''Resources added by Juan Pablo (JP) Loaiza-Ramírez'''
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| The following resources are listed in order of importance. Consider them as a "gentle" introduction to agent-based modeling.
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| '''Best papers overall'''
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| * [https://doi.org/10.1016/j.ijresmar.2011.04.002 Rand, W., & Rust, R. T. (2011). Agent-based modeling in marketing: Guidelines for rigor. International Journal of Research in Marketing, 28(3), 181–193. https://doi.org/10.1016/j.ijresmar.2011.04.002]
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| * [https://doi.org/10.1287/mnsc.2017.2877 Smith, E. B., & Rand, W. (2018). Simulating macro-level effects from micro-level observations. Management Science, 64(11), 5405–5421. https://doi.org/10.1287/mnsc.2017.2877]
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| * [https://doi.org/10.1080/19312458.2021.1986478 Waldherr, A., Hilbert, M., & González-Bailón, S. (2021). Worlds of agents: Prospects of agent-based modeling for communication research. Communication Methods and Measures, 15(4), 243–254. https://doi.org/10.1080/19312458.2021.1986478]
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| * [https://ijoc.org/index.php/ijoc/article/view/10588 Waldherr, A., & Wettstein, M. (2019). Bridging the gaps: Using agent-based modeling to reconcile data and theory in computational communication science. International Journal of Communication, 13, 3976–3999. https://ijoc.org/index.php/ijoc/article/view/10588]
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| * [http://www.jstor.org/stable/3069238 Macy, M. W., & Willer, R. (2002). From Factors to Actors: Computational Sociology and Agent-Based Modeling. Annual Review of Sociology, 28, 143–166.]
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| '''Seminal papers'''
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| * [https://www.jstor.org/stable/2117868 Arthur, W. B. (1994). Inductive Reasoning and Bounded Rationality. The American Economic Review, 84(2), 406–411. http://www.jstor.org/stable/2117868]
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| * [https://onlinelibrary.wiley.com/doi/10.1002/%28SICI%291099-0526%28199711/12%293%3A2%3C16%3A%3AAID-CPLX4%3E3.0.CO%3B2-K Axelrod, R. (1997). Advancing the art of simulation in the social sciences. Complexity, 3(2), 16–22. https://doi.org/10.1002/(SICI)1099-0526(199711/12)3:2<16::AID-CPLX4>3.0.CO;2-K]
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| * [https://doi.org/10.1007/BF01299065 Axtell, R., Axelrod, R., Epstein, J. M., & Cohen, M. D. (1996). Aligning simulation models: A case study and results. In Computational and Mathematical Organization Theory (Vol. 1, Issue 2, pp. 123–141). Springer Science and Business Media LLC. https://doi.org/10.1007/bf01299065]
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| * [https://doi.org/10.1073/pnas.082080899 Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences, 99, 7280–7287. https://doi.org/10.1073/pnas.082080899]
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| * [https://doi.org/10.1002/cplx.6130010503 Casti, J. L. (1996). Seeing the light at El Farol: A look at the most important problem in complex systems theory. Complexity, 1(5), 7–10. https://doi.org/10.1002/cplx.6130010503]
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| * [https://doi.org/10.1016/j.ecolmodel.2006.04.023 Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S. K., Huse, G., Huth, A., Jepsen, J. U., Jørgensen, C., Mooij, W. M., Müller, B., Pe’er, G., Piou, C., Railsback, S. F., Robbins, A. M., … DeAngelis, D. L. (2006). A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198(1–2), 115–126. https://doi.org/10.1016/j.ecolmodel.2006.04.023]
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| * [https://www.jstor.org/stable/1823701 Schelling, T. C. (1969). Models of Segregation. The American Economic Review, 59(2), 488–493. http://www.jstor.org/stable/1823701]
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| '''Examples of agent-based models in communication and other research fields'''
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| * [https://doi.org/10.1086/681254 DellaPosta, D., Shi, Y., & Macy, M. (2015). Why Do Liberals Drink Lattes? American Journal of Sociology, 120(5), 1473–1511. https://doi.org/10.1086/681254]
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| * [https://doi.org/10.1016/j.ecolecon.2022.107651 Foramitti, J. (2023). A framework for agent-based models of human needs and ecological limits. Ecological Economics, 204, 107651. https://doi.org/10.1016/j.ecolecon.2022.107651]
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| * [https://doi.org/10.1142/S1793962319500375 Forero, D. S., Ceballos, Y. F., & Torres, G. S. (2019). Simulation of consumers decision-making process using agent-based model approach. International Journal of Modeling, Simulation, and Scientific Computing, 10(06), 1950037. https://doi.org/10.1142/S1793962319500375]
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| * [https://doi.org/10.1007/s10614-021-10158-x Kato, J. S., & Sbicca, A. (2022). Bounded rationality, group formation and the emergence of trust: An agent-based economic model. Computational Economics, 60(2), 571–599. https://doi.org/10.1007/s10614-021-10158-x]
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| * [https://doi.org/10.24084/repqj08.367 Lopez Rodriguez, I., & Hernández Tejera, M. (2010). Agent-based services for building markets in distributed energy environments. Renewable Energy and Power Quality Journal, 1(08), 482–487. https://doi.org/10.24084/repqj08.367]
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| * [https://doi.org/10.1371/journal.pone.0031043 Luan, S., Katsikopoulos, K. V., & Reimer, T. (2012). When does diversity trump ability (and vice versa) in group decision making? A simulation study. PLoS ONE, 7(2). https://doi.org/10.1371/journal.pone.0031043]
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| * [https://doi.org/10.1016/j.solener.2019.08.040 Mittal, A., Krejci, C. C., Dorneich, M. C., & Fickes, D. (2019). An agent-based approach to modeling zero energy communities. Solar Energy, 191, 193–204. https://doi.org/10.1016/j.solener.2019.08.040]
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| * [https://doi.org/10.1177/0093650219856510 Sohn, D. (2022). Spiral of silence in the social media era: A simulation approach to the interplay between social networks and mass media. Communication Research, 49(1), 139–166. https://doi.org/10.1177/0093650219856510]
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| * [https://doi.org/10.1111/jcom.12288 Song, H., & Boomgaarden, H. G. (2017). Dynamic spirals put to test: An agent-based model of reinforcing spirals between selective exposure, interpersonal networks, and attitude polarization. Journal of Communication, 67(2), 256–281. https://doi.org/10.1111/jcom.12288]
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| '''YouTube Playlists'''
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| * [https://www.youtube.com/playlist?list=PLD4TWcPfbZO9HmaSutF_R2Y2RmiNDxvaP KaVe 101 - Agent Based Modeling with Python]
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| * [https://www.youtube.com/playlist?list=PLF0b3ThojznRKYcrw8moYMUUJK2Ra8Hwl Agent-Based Modeling (NetLogo)]
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| '''GitHub Repositories'''
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| * [https://github.com/topics/agent-based-modeling Different frameworks for agent-based-modeling, including mesa, agentpy, among others]
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| * [https://github.com/azvoleff/pyabm pyabm - Another agent-based modeling toolkit]
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| '''Online courses'''
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| * [https://www.publichealth.columbia.edu/research/population-health-methods/agent-based-modeling#Overview Agent-Based Modeling - Columbia University Irving Medical Center (General overview)]
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| * [https://www.coursera.org/learn/modeling-simulation-natural-processes#syllabus Simulation and modeling of natural processes - University of Geneva (Coursera)]
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| * [https://www.complexityexplorer.org/courses/171-introduction-to-agent-based-modeling Introduction to Agent-Based Modeling - Santa Fe Institute]
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| * [https://www.udemy.com/course/2020-intro-to-agent-based-modeling-simulation-ai-in-netlogo/ 2022 Intro to Agent-Based Modeling Simulation AI in NetLogo - Udemy]
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| '''Tutorials'''
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| * [https://www.complexityexplorer.org/courses/172-agent-based-models-with-python-an-introduction-to-mesa Agent-Based Models with Python: An Introduction to Mesa - Santa Fe Institute]
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| == SQL == | | == SQL == |
| Muqing Liu
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| Introduction to SQL:
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| General introduction to SQL https://www.khanacademy.org/computing/computer-programming/sql
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| Relational model and the foundation of SQL https://dl.acm.org/doi/10.1145/362384.362685
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| Principles and rules for relational database management systems https://www.dcs.warwick.ac.uk/~hugh/TTM/
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| Textbook Guidance to write SQL:
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| "The complete idiot's guide to SQL" Steven Holzner This is a beginner-friendly guide introduces SQL concepts and commands. https://www.amazon.com/Complete-Idiots-Guide-SQL/dp/1615641092
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| "SQL and Relational Theory: How to write accurate SQL code" C.J. Date
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| This book provides a comprehensive guide to understand SQL and relational theory https://www.amazon.com/SQL-Relational-Theory-Write-Accurate/dp/1449316409
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| "SQL pocket guide" Jonathan Gennick
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| This book is a handy reference for SQL syntax and command https://www.amazon.com/SQL-Pocket-Guide-Usage/dp/1449394094
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| Online courses:
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| SQL for beginners https://www.udemy.com/course/sql-for-beginners/
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| This beginner-friendly course covers database design, querying with SQL, data manipulation, and database management.
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| SQL essential training https://www.linkedin.com/learning/sql-essential-training/
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| This course covers basic SQL commands and querying techniques.
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| The complete SQL bootcamp https://www.udemy.com/course/the-complete-sql-bootcamp/
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| This course covers both SQL fundamentals and advanced concepts. It also includes real-world projects and hands-on exercises.
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| SQL for data science https://www.coursera.org/learn/sql-for-data-science
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| This course is designed for data science professionals to use SQL for data manipulation and analysis. It covers SQL queries, joins, and aggregations for data science tasks.
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| Advanced SQL for query tuning https://www.pluralsight.com/courses/advanced-sql-query-tuning
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| This course is for intermediate to advanced SQL users looking to optimize their SQL queries and improve database performance.
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| SQL tutorial videos:
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| MySQL tutorial for beginners https://www.youtube.com/watch?v=7S_tz1z_5bA
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| SQL Tutorial - Full Database Course for Beginners: https://www.youtube.com/watch?v=HXV3zeQKqGY
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| SQL Advanced Tutorial|Advanced SQL Tutorial With Examples https: //www.youtube.com/watch?v=M-55BmjOuXY
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|
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| The use of SQL in data science:
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| A Comparative Analysis on different aspects of Database Management System https://www.researchgate.net/publication/352178674_A_Comparative_Analysis_on_different_aspects_of_Database_Management_System
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| This paper compared different database management system for handling big data storage and processing tasks.
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| Twitter Sentiment Analysis Approaches: A Survey https://www.learntechlib.org/p/217980/
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| Analysis of Healthcare Data using SQL https://www.linkedin.com/pulse/analysis-healthcare-data-using-sql-kristopher-bosch/
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| SQL for Stock Market Analysis https://medium.datadriveninvestor.com/sql-for-stock-market-analysis-f2145031e125
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|
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|
| == Command line == | | == Command line == |
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| == Large language models==
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|
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| Resources posted by Dyuti
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|
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| -[https://www.techtarget.com/searchenterpriseai/definition/languagemodeling#:~:text=Importance%20of%20language%20modeling&text=It%20is%20the%20reason%20that,other%20to%20a%20limited%20extent What is a language model and why do we need it?]
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|
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| - [https://medium.com/analytics-vidhya/a-comprehensive-guide-to-build-your-own-language-model-in-python-5141b3917d6d A comprehensive guide to build your own language model]
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|
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| LLMs and Research:
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|
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| Large Language Models and Underrepresented Languages [https://arxiv.org/ftp/arxiv/papers/2007/2007.05872.pdf Paper]
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|
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| -Social Biases:
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|
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| -[http://proceedings.mlr.press/v139/liang21a.html Towards Understanding and Mitigating Social Biases in Language Models]
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|
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| - [https://medium.com/@arpitnarain/unmasking-bias-assessing-fairness-in-large-language-models-a722624e4483 Unmasking Bias —Assessing Fairness in Large Language Models]
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|
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| - [https://aclanthology.org/2022.bigscience-1.6.pdf Pipelines for Social Bias Testing of Large Language Models]
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|
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| - [https://huggingface.co/blog/evaluating-llm-bias#evaluating-language-model-bias-with-%F0%9F%A4%97-evaluate Evaluating Language Model Bias with 🤗 Evaluate ]
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|
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| Mitigating Bias:
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|
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| - [https://www.aneesmerchant.com/personal-musings/large-language-models-and-bias-an-unresolved-issue#:~:text=Bias%20in%20LLMs%20can%20manifest,these%20models%20are%20trained%20on. LLM and Biases]
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|
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|
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| - [https://news.mit.edu/2023/large-language-models-are-biased-can-logic-help-save-them-0303 logic aware models- MIT]
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|
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| LLM and Research:
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|
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| - [https://proceedings.mlr.press/v202/aher23a/aher23a.pdf Using LLMs to Simulate Multiple Humans and Replicate Human Subject Studies] (I am a little dicey about the ethics of it? Would like to hear what everyone else thinks)
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| == Cluster / large-scale computing == | | == Cluster / large-scale computing == |
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| Elizabeth: Topic presentation and additional resources
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|
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| - Google intro documentation: https://cloud.google.com/architecture/using-clusters-for-large-scale-technical-computing
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|
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| - An cool example tutorial of how UCLA uses a cluster: https://github.com/chris-german/Hoffman2Tutorials
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|
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| - Link for Purdue RCAC: https://www.rcac.purdue.edu/compute
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|
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| - A workshop summary on reproducibility and large-scale computing: https://arxiv.org/ftp/arxiv/papers/1412/1412.5557.pdf
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|
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| - Basics of high performance computing: https://hbctraining.github.io/Intro-to-shell-flipped/lessons/08_HPC_intro_and_terms.html
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|
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| - RedHat and HPC: https://www.redhat.com/en/products/high-performance-computing
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|
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| -
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| == Network analysis == | | == Network analysis == |
| * [https://youtu.be/flwcAf1_1RU Network Analysis Introduction Video]
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| Resources added by Hazel
| | * [https://youtu.be/flwcAf1_1RU Network Analysis] |
|
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| NetworkX
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| * [https://towardsdatascience.com/network-analysis-d734cd7270f8 What is Network Analysis]
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| * [https://www.researchgate.net/publication/236407765_Exploring_Network_Structure_Dynamics_and_Function_Using_NetworkX Exploring Network Structure, Dynamics, and Function Using NetworkX]
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| * [https://youtu.be/VetBkjcm9Go Crash Course of NetworkX on Youtube]
| |
| *[https://trenton3983.github.io/files/projects/2020-05-21_intro_to_network_analysis_in_python/2020-05-21_intro_to_network_analysis_in_python.html Python Notebook Introduction of NetworkX]
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|
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| Applications of NetworkX in academic research
| |
| *[https://doi.org/10.1080/13683500.2020.1777950 Valeri, M., & Baggio, R. (2020). Italian tourism intermediaries: A social network analysis exploration. Current Issues in Tourism, 24(9), 1270–1283.]
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| *[https://doi.org/10.1016/j.gloenvcha.2015.03.006 Williams, H. T. P., McMurray, J. R., Kurz, T., & Hugo Lambert, F. (2015). Network analysis reveals open forums and Echo Chambers in social media discussions of climate change. Global Environmental Change, 32, 126–138.]
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|
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| iGraph
| |
| *[https://towardsdatascience.com/newbies-guide-to-python-igraph-4e51689c35b4 Newbies Guide to Python-igraph]
| |
| *[https://www.cs.rhul.ac.uk/home/tamas/development/igraph/tutorial/tutorial.html iGraph Tutorial]
| |
| *[https://www.youtube.com/watch?v=DuTROLV1760 iGraph with R Video Tutorial]
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|
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| Application of iGraph in academic research
| |
| *[https://doi.org/10.1016/j.socnet.2015.07.003 González-Bailón, S., & Wang, N. (2016). Networked discontent: The anatomy of protest campaigns in social media. Social Networks, 44, 95–104]
| |
| *[https://doi.org/10.1187/cbe.13-08-0162 Grunspan, D. Z., Wiggins, B. L., & Goodreau, S. M. (2014). Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research. CBE—Life Sciences Education, 13(2), 167–178]
| |
| *[https://doi.org/10.1080/01292986.2018.1453849 Kokil Jaidka, Saifuddin Ahmed, Marko Skoric & Martin Hilbert (2019) Predicting elections from social media: a three-country, three-method comparative study, Asian Journal of Communication, 29:3, 252-273]
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|
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|
| == Object-oriented programming == | | == Object-oriented programming == |
Line 651: |
Line 338: |
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|
| * [https://www.youtube.com/watch?v=K8L6KVGG-7o Regular Expressions] | | * [https://www.youtube.com/watch?v=K8L6KVGG-7o Regular Expressions] |
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| = Administrative Notes = | | = Administrative Notes = |