Spam Four Ways: Making Sense of Text Data

Author:

Horton Nicholas J.1,Chao Jie2ORCID,Finzer William2,Palmer Phebe1

Affiliation:

1. Amherst College

2. Concord Consortium

Publisher

Informa UK Limited

Subject

General Medicine

Reference5 articles.

1. CATALST (Change Agents for Teaching and Learning Statistics) Group. 2009. Creating a spam filter, https://serc.carleton.edu/sp/cause/mea/examples/example3.html.

2. CODAP (Common Online Data Access Platform). 2022, https://codap.concord.org.

3. Concord Consortium. 2021. Narrative modeling using StoryQ, https://concord.org/our-work/research-projects/storyq.

4. Data Science in R

5. Spamlaws.com. 2022. Spamlaws: How to stop scams and fraud, www.spamlaws.com.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Emerging trends in statistics education;ZDM – Mathematics Education;2023-07-01

2. How learners produce data from text in classifying clickbait;Teaching Statistics;2023-05-06

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