Submitting Author: Michael W. Kearney (@mkearney)
Repository: https://github.com/mkearney/rtweet
Version submitted: v0.6.9
Editor: @sckott
Reviewer 1: @andrewheiss
Reviewer 2: @briatte
Archive: TBD
Version accepted: TBD

• Paste the full DESCRIPTION file inside a code block below:

Package: rtweet
Type: Package
Version: 0.6.9
Title: Collecting Twitter Data
Authors@R: c(
    person("Michael W.", "Kearney", ,
    email = "[email protected]", role = c("aut", "cre"),
    comment = c(ORCID = "0000-0002-0730-4694"))
    ## add contributor template (middle name/initial optional)
    #person("First Middle", "Last", ,
    #email = "[email protected]", role = c("ctb"))
    )
Description: An implementation of calls designed to collect and
    organize Twitter data via Twitter's REST and stream Application
    Program Interfaces (API), which can be found at the following URL:
    <https://developer.twitter.com/en/docs>.
Depends:
    R (>= 3.1.0)
Imports:
    httr (>= 1.3.0),
    jsonlite (>= 0.9.22),
    magrittr (>= 1.5.0),
    tibble (>= 1.3.4),
    utils,
    progress,
    Rcpp,
    httpuv
License: MIT + file LICENSE
URL: https://CRAN.R-project.org/package=rtweet
BugReports: https://github.com/mkearney/rtweet/issues
Encoding: UTF-8
Suggests:
    ggplot2,
    knitr,
    magick,
    openssl,
    readr,
    rmarkdown,
    testthat (>= 2.1.0),
    webshot,
    covr,
    igraph
VignetteBuilder: knitr
LazyData: yes
RoxygenNote: 6.1.1
LinkingTo: 
    Rcpp

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.):

  • data retrieval
  • data extraction
  • database access
  • data munging
  • data deposition
  • reproducibility
  • geospatial data
  • text analysis

• Explain how and why the package falls under these categories (briefly, 1-2 sentences):

Data retrieval because the package allows users to easily request and import data from Twitter's REST and stream APIs.

Data munging because significant work is done to convert JSON objects returned by Twitter's APIs into tabular data frames.

• Who is the target audience and what are scientific applications of this package?

The target audience is researchers. The scientific applications span a range of topics. Here's is the relevant excerpt from paper.md

Although rtweet provides some coverage to user context-behaviors (e.g.,
posting statuses, liking tweets, following users, etc.), the primary audience
for the package to date has been researchers. Accordingly, rtweet has been
featured in numerous popular press [e.g.,
@bajak2019democrats; @machlis2019r; @riley2019twitter] and academic publications
[e.g.,
@bossetta2018simulated; @bradley2019major; @buscema2018media;
@erlandsen2018twitter; @gitto2019brand; @kearney2019analyzing;
@kearney2018analyzing; @li2018sentiment; @lutkenhaus2019tailoring;
@lutkenhaus2019mapping; @molyneux2018media; @tsoi2018can; @unsihuay2018topic;
@valls2017urban; @wu2018finding].

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

To date no other package interfaces with both REST and stream APIs. The twitteR package is most similar, but it has entered a stage of deprecation (I've agreed to carry the torch, so to speak). So, not only does twitteR not reflect some recent changes to Twitter's API (most notably the introduction of 'extended tweet' mod–the new 280 character limit), but it lacks active maintenance thanks–in part–to rtweet filling the void.

• If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted.

#193

Technical checks

Confirm each of the following by checking the box. This package:

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

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• Do you intend for this package to go on CRAN?
• Do you wish to automatically submit to the Journal of Open Source Software? If so:

• Do you wish to submit an Applications Article about your package to Methods in Ecology and Evolution? If so:

Code of conduct

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