Package: opitools 2.0.0
opitools: Analyzing the Opinions in a Big Text Document
Designed for performing impact analysis of opinions in a digital text document (DTD). The package allows a user to assess the extent to which a theme or subject within a document impacts the overall opinion expressed in the document. The package can be applied to a wide range of opinion-based DTD, including commentaries on social media platforms (such as 'Facebook', 'Twitter' and 'Youtube'), online products reviews, and so on. The utility of 'opitools' was originally demonstrated in Adepeju and Jimoh (2021) <doi:10.31235/osf.io/c32qh> in the assessment of COVID-19 impacts on neighbourhood policing using Twitter data. Further examples can be found in the vignette of the package.
Authors:
opitools_2.0.0.tar.gz
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opitools_2.0.0.tgz(r-4.4-any)opitools_2.0.0.tgz(r-4.3-any)
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opitools.pdf |opitools.html✨
opitools/json (API)
| # Install 'opitools' in R: |
| install.packages('opitools', repos = c('https://manalytics.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/manalytics/opitools/issues
- covid_theme - Keywords relating to COVID-19 pandemics
- debate_dtd - Comments on a video of a political debate.
- osd_data - Observed sentiment document (OSD).
- policing_dtd - Twitter posts on police/policing
- refreshment_theme - Keywords relating to facilities at train stations
- reviews_dtd - Customer reviews from tripadvisor website
- signage_theme - Keywords relating to signages at train stations
- tweets - Fake Twitter posts on police/policing 2
Last updated 2 years agofrom:3905a62026. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 12 2024 |
| R-4.5-win | NOTE | Nov 12 2024 |
| R-4.5-linux | NOTE | Nov 12 2024 |
| R-4.4-win | NOTE | Nov 12 2024 |
| R-4.4-mac | NOTE | Nov 12 2024 |
| R-4.3-win | NOTE | Nov 12 2024 |
| R-4.3-mac | NOTE | Nov 12 2024 |
Exports:opi_impactopi_scoreopi_simword_distribword_imp
Dependencies:base64encBHbslibcachemclicolorspacecowplotcpp11digestdplyrevaluatefansifarverfastmapfontawesomeforcatsfsgenericsggplot2glueGPArotationgridExtragtablehighrhtmltoolshtmlwidgetsisobandjaneaustenrjquerylibjsonliteknitrlabelinglatticelifecyclelikertmagrittrMASSMatrixmemoisemgcvmimemnormtmunsellnlmeNLPpillarpkgconfigplyrpsychpurrrR6rappdirsRColorBrewerRcppreshape2rlangrmarkdownsassscalesslamSnowballCstringistringrtibbletidyrtidyselecttidytexttinytextmtokenizersutf8vctrsviridisLitewithrwordcloud2xfunxml2xtableyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| keywords relating to COVID-19 pandemics | covid_theme |
| Comments on a video of a political debate. | debate_dtd |
| Statistical assessment of impacts of a specified theme from a DTD. | opi_impact |
| Opinion score of a digital text document (DTD) | opi_score |
| Simulates the opinion expectation distribution of a digital text document. | opi_sim |
| Observed sentiment document (OSD). | osd_data |
| Twitter posts on police/policing | policing_dtd |
| Keywords relating to facilities at train stations | refreshment_theme |
| Customer reviews from tripadvisor website | reviews_dtd |
| Keywords relating to signages at train stations | signage_theme |
| Fake Twitter posts on police/policing 2 | tweets |
| Words Distribution | word_distrib |
| Importance of words (terms) embedded in a text document | word_imp |
