Submission group 8: rtweetlytics

Submitting Author Name: Mahsa Sarafrazi Submitting Author Github Handle: !--author1-->@mahsasarafrazi<!--end-author1-- Other Package Authors Github handles: (comma separated, delete if none) Amir Shojakhani: @amirshoja, Shiva Shankar Jena: @shivajena, Mahmood Rahman: @mahm00d27 Repository: https://github.com/UBC-MDS/rtweetlytics Version submitted: Standard Submission type: Standard Reviewers: Xiaohan Chen, James Kim, Brandon Lam, Zihan Zhou Archive: TBD Version accepted: TBD Language: en

Paste the full DESCRIPTION file inside a code block below:

Package: rtweetlytics
Title: Analyzing the tweets for specific keyword
Version: 0.0.0.9000
Authors@R: 
    person(given = "Amir Shojakhani, Shiva Shankar Jena ,Mahmood Rahman, MAhsa Sarafrazi",
           family = "MDS UBC",
           role = c("aut", "cre"),
           email = "ma.sarafrazi@gmail.com",
           comment = c(ORCID = "YOUR-ORCID-ID"))
Description: This package would retrieve tweets on a required topic and time frame, store them, performs data cleaning, data analysis, and plotting.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.1
Config/testthat/edition: 3
Imports: 
    httr,
    dplyr,
    jsonlite,
    testthat,
    lubridate,
    stringr,
    plyr,
    sentimentr
Depends: 
    tidyverse

Scope

Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):
- [X] data retrieval
- [X] data extraction
- [X] data munging
- [ ] data deposition
- [ ] workflow automation
- [ ] version control
- [ ] citation management and bibliometrics
- [ ] scientific software wrappers
- [ ] field and lab reproducibility tools
- [ ] database software bindings
- [ ] geospatial data
- [X] text analysis
Explain how and why the package falls under these categories (briefly, 1-2 sentences): The package rtweetlytics is a package intended to give insight about a topic on Twitter through some functions. The intention is that a user with little knowledge about data science can quickly call a function to analyze how the topics and trends are on Twitter. Internally, the package uses the official Twitter API, stores the data as a .json and .csv file, perform data cleaning, data analysis, and plotting.
Who is the target audience and what are scientific applications of this package? Any data professionals at the entry-level would like to conduct a quick exploratory data analysis on Twitter.
Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?
from Twitter API and token to plotting, all the procedures that a person should accomplish to get the result, now combine in one package
(If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?
If you made a pre-submission inquiry, please paste the link to the corresponding issue, forum post, or another discussion, or @tag the editor you contacted.
Explain reasons for any pkgcheck items which your package is unable to pass.

Technical checks

Confirm each of the following by checking the box.

[X] I have read the guide for authors and rOpenSci packaging guide.

This package:

[X] does not violate the Terms of Service of any service it interacts with.
[X] has a CRAN and OSI accepted license.
[x] contains a README with instructions for installing the development version.
[X] includes documentation with examples for all functions, created with roxygen2.
[ ] contains a vignette with examples of its essential functions and uses.
[X] has a test suite.
[ ] has continuous integration, including reporting of test coverage using services such as Travis CI, Coveralls, and/or CodeCov.

Publication options

[ ] Do you intend for this package to go on CRAN?
[ ] Do you intend for this package to go on Bioconductor?
[ ] Do you wish to submit an Applications Article about your package to Methods in Ecology and Evolution? If so:

MEE Options

Code of conduct

[X] I agree to abide by rOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

Briefly describe any working relationship you have (had) with the package authors.
[x] As the reviewer I confirm that there are no conflicts of interest for me to review this work (if you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

[x] A statement of need: clearly stating problems the software is designed to solve and its target audience in README
[x] Installation instructions: for the development version of package and any non-standard dependencies in README
[x] Vignette(s): demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all exported functions
[x] Examples: (that run successfully locally) for all exported functions
[x] Community guidelines: including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

Functionality

[x] Installation: Installation succeeds as documented.
[ ] Functionality: Any functional claims of the software been confirmed.
[ ] Performance: Any performance claims of the software been confirmed.
[x] Automated tests: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[ ] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines.

Estimated hours spent reviewing: 1.5 hours

[ ] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

Review Comments

You may consider adding the codecov badge.
There is room to do more tests on the code as the code coverage is currently at 45%. It would be great if you are able to test more edge cases to make your package more robust against user error.
You may consider adding more details in the Roxygen2 of the functions, there are no examples for the functions.
Only function get_store() works for me, seems there is namespace issue with other 3 functions.
Example & usage is easy to follow, you may also consider adding links / tutorials on how to generate the personal ‘bearer token’ for the get_store() function.
You may describe where your packages fit into the R ecosystem (are there any other R packages that have the same/similar functionality) in the readme.

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

Briefly describe any working relationship you have (had) with the package authors.
[x] As the reviewer I confirm that there are no conflicts of interest for me to review this work (if you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

[x] A statement of need: clearly stating problems the software is designed to solve and its target audience in README
[x] Installation instructions: for the development version of package and any non-standard dependencies in README
[x] Vignette(s): demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all exported functions
[x] Examples: (that run successfully locally) for all exported functions
[x] Community guidelines: including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

Functionality

[x] Installation: Installation succeeds as documented.
[x] Functionality: Any functional claims of the software been confirmed.
[ ] Performance: Any performance claims of the software been confirmed.
[x] Automated tests: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[x] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines.

Estimated hours spent reviewing: 1h

[ ] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

Review Comments

Nice work! I think your R package's docs are more organized than the python one, demonstrating the improvement through the course. And this package is very useful!!
The test for plot functions is insufficient.
Tests files may have unified names.
Examples for each function in the R/function_name.R need to be supplemented.
In the table of your readme file's function part, you can also add your parameter's name in the input column, I am a little confused when I read this part.
Is any similar existing package? And what is your advantage compared to that? A relevant explanation will be great!

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

Briefly describe any working relationship you have (had) with the package authors.
[x] As the reviewer I confirm that there are no conflicts of interest for me to review this work (if you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

[x] A statement of need: clearly stating problems the software is designed to solve and its target audience in README
[x] Installation instructions: for the development version of package and any non-standard dependencies in README
[x] Vignette(s): demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all exported functions
[x] Examples: (that run successfully locally) for all exported functions
[x] Community guidelines: including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

Functionality

[x] Installation: Installation succeeds as documented.
[ ] Functionality: Any functional claims of the software been confirmed.
[ ] Performance: Any performance claims of the software been confirmed.
[x] Automated tests: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[x] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines.

Estimated hours spent reviewing: 1 hr

[x] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

Review Comments

Again, great job on this amazing package! I can see that lots of work put into the scripts and the tests to make this happen.
The documentation on usage now contains an example data and detailed walk through on how to use the package. Great job!
Functions are now better organized in a table, which is easy to follow.
I am having the same error issue as ming0701 has noted above.
I liked the resulting visuals from python package so perhaps you could further develop this R package as well in the future.
I see that more tests can be written for plotting function, checking the input, output and etc.

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

Briefly describe any working relationship you have (had) with the package authors.
[x] As the reviewer I confirm that there are no conflicts of interest for me to review this work (if you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

[x] A statement of need: clearly stating problems the software is designed to solve and its target audience in README
[x] Installation instructions: for the development version of package and any non-standard dependencies in README
[x] Vignette(s): demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all exported functions
[x] Examples: (that run successfully locally) for all exported functions
[x] Community guidelines: including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

Functionality

[x] Installation: Installation succeeds as documented.
[x] Functionality: Any functional claims of the software been confirmed.
[ ] Performance: Any performance claims of the software been confirmed.
[x] Automated tests: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[x] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines.

Estimated hours spent reviewing: 1h

[ ] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

Review Comments

Amazing work! The package works as expected and as described. I love how the name conveys the benefit of being able to generate plots quickly. The peer reviewers above me provided detailed feedback that I agree with. In addition, I noted some minor revisions, as follows.

Since this package is built on the dplyr package and the ggplot2 package, you need to reference them in the reference section of the README.
In the pkgdown.yaml. It's necessary to test Window and macOS to ensure your package is compatible with other systems.
It will be better to add more explaining comments in the code block of the function.(In particular explotting.R) Maybe explaining more about the function, then the user can have a better understanding about this work.
You can also add the names of your parameters in the input field in the table in the function section of your readme file. Users can use your packages more easily.
Same error like James and Ming0701 above, clean_tweets need be fixed

Aside from the minor issues mentioned above, the package has been so comprehensive and easy to use overall. I really appreciate that you can use this package to make data visualization easier for non-technical people. Thanks!

UBC-MDS / software-review-2022