R Observatory: Metrics for WeatherSentiment version 1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

WeatherSentiment

1.0Package record

Comprehensive Analysis of Tweet Sentiments and Weather Data

0packages depend

2.3Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Leila Marvian MashhadCRAN page ↗

A comprehensive suite of functions for processing, analyzing, and visualizing textual data from tweets is offered. Users can clean tweets, analyze their sentiments, visualize data, and examine the correlation between sentiments and environmental data such as weather conditions. Main features include text processing, sentiment analysis, data visualization, correlation analysis, and synthetic data generation. Text processing involves cleaning and preparing tweets by removing textual noise and irrelevant words. Sentiment analysis extracts and accurately analyzes sentiments from tweet texts using advanced algorithms. Data visualization creates various charts like word clouds and sentiment polarity graphs for visual representation of data. Correlation analysis examines and calculates the correlation between tweet sentiments and environmental variables such as weather conditions. Additionally, random tweets can be generated for testing and evaluating the performance of analyses, empowering users to effectively analyze and interpret 'Twitter' data for research and commercial purposes.

Install

R (CRAN)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("WeatherSentiment", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-weathersentiment

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-WeatherSentiment

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-WeatherSentiment

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 2.5 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-09-08
ERROR12 OK, 1 ERROR2026-09-07
OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09

Show 2 earlier changesHide 2 earlier changes

ERROR12 OK, 1 ERROR2026-06-08
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.0

READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION

Help pages: 6
Examples that run: 100%6 run in a plain check
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 0%

How these are measured

Downloads

2.3K

CRAN downloads in the past year

Rank #21,919 · ~6/day · ~189/mo

Releases R versions

Daily download trend is not available in this view yet.

22730 days

61090 days

2.3K1 year

Compare downloads with other packages →

Also on68 r2u

How downloads are counted

Dependencies

Declared dependencies

11 external dependencies (excludes base and recommended)

Installing WeatherSentiment adds 118 packages (56 with compiled code, 85 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (4)

R >= 4.1.0tidyverse wordcloud sentimentr

Imports (6)

tidytext ggplot2 stringr data.table RColorBrewer tidyr

LinkingTo (0)

none

Suggests (2)

dplyr syuzhet

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (4)

Leila Marvian Mashhad

Author, Maintainer since 1.0 (2024)

Mohammad Arashi

Author

Andriette Bekker

Author

Priyanka Nagar

Author

Releases (1)

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
1.0Latest
record
2024-08-19 · current release
R
R 4.4.0 released · 2024-04-24

Package metadata

First published: 2024-08-19
Total releases: 1 / 2 yrs
License: GPL-3 OSI
Minimum R: ≥ 4.1.0
Download size: 5.6 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("WeatherSentiment")

Format

Marvian Mashhad, L., Arashi, M., Bekker, A., & Nagar, P. (2024). WeatherSentiment: Comprehensive Analysis of Tweet Sentiments and Weather Data (Version 1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.WeatherSentiment

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for WeatherSentiment version 1.0 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →