{ "_id": "6ab4fa7c3d719c1f8409809b", "Package": "tidyEmoji", "Type": "Package", "Title": "Discover, Count, Categorise, Score, Translate and Relate Emoji\nin Text", "Version": "0.5.0", "Authors@R": "c(person(given = \"Youzhi\",\nfamily = \"Yu\",\nrole = c(\"aut\", \"cre\"),\nemail = \"yuyouzhi666@icloud.com\"))", "Description": "A tidy toolkit for working with the emoji in any text\ncolumn, such as social-media posts, product reviews, chat logs\nor survey responses. Unicode is awkward to handle and not every\ncode point is an emoji, which makes emoji statistics fiddly to\nobtain. 'tidyEmoji' extracts, counts, categorises,\nsentiment-scores and emotion-scores emoji, converts them to and\nfrom text (for accessibility and NLP preprocessing), searches\nthe emoji catalogue, maps emoji co-occurrence and sequences\n(graph-ready edge lists and n-grams), measures where and how\ndensely emoji are used, and builds document-by-emoji feature\ntables for machine learning, with grapheme-aware detection (so\nskin-tone and multi-person sequences stay intact), returning\ntidy data frames that slot straight into a 'tidyverse'\nworkflow. It also quantifies how much annotators disagreed\nabout an emoji (interpretation risk), extracts the words around\neach emoji, tracks emoji use over time, measures text-emoji\nsentiment mismatch, and applies explicit emoji-preprocessing\npolicies for language-model pipelines. The bundled emoji\nsentiment lexicon is from the Emoji Sentiment Ranking of Kralj\nNovak et al. (2015) ,\nreleased under CC BY-SA 4.0; the emotion lexicon is from\nEmoTag1200 of Shoeb & de Melo (2020)\n, released under\nthe MIT licence.", "License": "GPL (>= 3)", "URL": "https://pursuitofdatascience.github.io/tidyEmoji/,\nhttps://github.com/PursuitOfDataScience/tidyEmoji", "BugReports": "https://github.com/PursuitOfDataScience/tidyEmoji/issues", "Encoding": "UTF-8", "Language": "en-GB", "LazyData": "true", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "Config/testthat/edition": "3", "VignetteBuilder": "knitr", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://pursuitofdatascience.r-universe.dev", "Date/Publication": "2026-09-24 09:02:42 UTC", "RemoteUrl": "https://github.com/pursuitofdatascience/tidyemoji", "RemoteRef": "HEAD", "RemoteSha": "f388843a08b9e72a27ac676d16df22a8c9e202eb", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-24 10:18:52 UTC", "User": "root" }, "Author": "Youzhi Yu [aut, cre]", "Maintainer": "Youzhi Yu ", "_user": "pursuitofdatascience", "_type": "src", "_file": "tidyEmoji_0.5.0.tar.gz", "_fileid": "https://r2.ropensci.org/05706ee7870e04710a6b2cb7f3dba1bd66f0f2a55f530fe6984a964f8d262ad7", "_filesize": 1735644, "_sha256": "05706ee7870e04710a6b2cb7f3dba1bd66f0f2a55f530fe6984a964f8d262ad7", "_expires": "2027-01-02T10:24:58.000Z", "_created": "2026-09-24T10:18:52.000Z", "_published": "2026-09-24T10:25:00.490Z", "_jobs": [ { "job": 107590419291, "time": 280, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "10801868905" }, { "job": 107590419216, "time": 271, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "10802671970" }, { "job": 107590419447, "time": 209, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "10802468006" }, { "job": 107590419224, "time": 238, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "10802174321" }, { "job": 107589025941, "time": 264, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "10802576602" }, { "job": 107590419492, "time": 129, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "10801709091" }, { "job": 107590419223, "time": 269, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "10803080000" }, { "job": 107590420398, "time": 258, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "10802433308" }, { "job": 107590419245, "time": 218, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "10802810217" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/pursuitofdatascience/actions/runs/35986082591", "_status": "success", "_upstream": "https://github.com/pursuitofdatascience/tidyemoji", "_commit": { "id": "f388843a08b9e72a27ac676d16df22a8c9e202eb", "author": "Youzhi Yu ", "committer": "Youzhi Yu ", "message": "Detect roxygen sources by their files, not by the directory\n\nThe coverage job runs the tests from a copy in which ../../R exists and\nholds the installed lazy-load database. The new list-item scan saw the\ndirectory, found no .R files in it and failed its own non-vacuity check,\nwhich made test-coverage the one red job on 3012c01. It now stands down on\nthe files, as the tolower() scan beside it already does. Reproduced with\nthe job's own covr::package_coverage() call: 1 failure before, 0 after.\n\nThe registered-lexicon fix left the `key` fallback in\n.emoji_lexicon_keys() serving only a table keyed by its code-point column,\nand no test reached it any more, so it has one. Coverage is 99.31%. NEWS's\ncoverage sentence had also gone stale on its thinnest file, which is\nemoji-translate.R at 97.2% rather than emoji-sentiment.R at 94.9%, and the\ncounts cran-comments.md quotes move by the two new assertions.\n\nVerified: covr 99.31% with 0 test failures, as the job runs it;\n`R CMD check --as-cran` 1 WARNING and 3 NOTEs, the four host artefacts, in\nUTF-8 (in-check 16150 pass, 19 skip) and under `LC_ALL=C` (16144 pass);\nR 4.6.0 without its missing Suggests 2 NOTEs, 16146 pass; standalone\nsuites 16269 pass under UTF-8 and 16260 under `LC_ALL=C`, 0 failures; the\n0.5.0 regression file passes on R 4.1.0 and R 4.6.0.\n", "time": 1790240562 }, "_maintainer": { "name": "Youzhi Yu", "email": "yuyouzhi666@icloud.com", "login": "pursuitofdatascience", "description": "CUDA out of memory", "uuid": 54338793 }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "dplyr", "version": ">= 1.1.0", "role": "Imports" }, { "package": "emoji", "version": ">= 16.0.0", "role": "Imports" }, { "package": "lifecycle", "version": ">= 1.0.3", "role": "Imports" }, { "package": "rlang", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "tibble", "role": "Imports" }, { "package": "tidyr", "version": ">= 1.3.0", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.1.5", "role": "Suggests" }, { "package": "spelling", "role": "Suggests" }, { "package": "commonmark", "role": "Suggests" }, { "package": "xml2", "role": "Suggests" }, { "package": "ggplot2", "role": "Suggests" }, { "package": "readr", "version": ">= 2.0.0", "role": "Suggests" }, { "package": "forcats", "role": "Suggests" }, { "package": "stringr", "role": "Suggests" } ], "_owner": "pursuitofdatascience", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-25", "n": 5 }, { "week": "2026-27", "n": 10 }, { "week": "2026-28", "n": 1 }, { "week": "2026-30", "n": 1 }, { "week": "2026-32", "n": 2 }, { "week": "2026-36", "n": 22 }, { "week": "2026-37", "n": 3 }, { "week": "2026-38", "n": 33 }, { "week": "2026-39", "n": 5 } ], "_tags": [ { "name": "v0.2.0", "date": "2026-06-16" }, { "name": "v0.3.0", "date": "2026-07-25" }, { "name": "v0.4.0", "date": "2026-09-17" }, { "name": "v0.5.0", "date": "2026-09-24" } ], "_topics": [ "emoji", "nlp", "tidyverse" ], "_stars": 4, "_contributors": [ { "user": "pursuitofdatascience", "count": 93, "uuid": 54338793 } ], "_userbio": { "uuid": 54338793, "type": "user", "name": "Y. 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"as_emoji_shortcode", "as_emoji_type", "emoji_adoption_lag", "emoji_ambiguity", "emoji_categorize", "emoji_collocations", "emoji_congruence", "emoji_context", "emoji_cooccurrence", "emoji_density", "emoji_dfm", "emoji_emotion", "emoji_emotion_label", "emoji_extract_nest", "emoji_extract_unnest", "emoji_faceness", "emoji_filter", "emoji_flag_ambiguous", "emoji_frequency", "emoji_incongruity", "emoji_incongruity_profile", "emoji_lexicons", "emoji_ngrams", "emoji_pairs", "emoji_position", "emoji_provenance", "emoji_ratio", "emoji_risk", "emoji_sanitize", "emoji_score", "emoji_search", "emoji_seasonality", "emoji_sentiment", "emoji_summary", "emoji_to_text", "emoji_token_cost", "emoji_tokens", "emoji_trend", "emoji_turnover", "emoji_tweets", "emoji_type", "emoji_unicode_releases", "emoji_unicode_version", "emoji_version_profile", "register_emoji_lexicon", "text_to_emoji", "top_n_emojis" ], "_datasets": [ { "name": "category_unicode_crosswalk", "title": "Emoji category to unicode 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"emoji_name", "unicode", "emoji_category", "key" ], "rows": 5761, "table": true, "tojson": true } ], "_help": [ { "page": "as_emoji_name", "title": "Vector helpers: convert emoji to/from names and shortcodes", "topics": [ "as_emoji", "as_emoji_name", "as_emoji_shortcode" ] }, { "page": "as_emoji_type", "title": "Functional type of an emoji glyph", "topics": [ "as_emoji_type" ] }, { "page": "category_unicode_crosswalk", "title": "Emoji category to unicode crosswalk", "topics": [ "category_unicode_crosswalk" ] }, { "page": "emoji_adoption_lag", "title": "How long did this population take to adopt each emoji?", "topics": [ "emoji_adoption_lag" ] }, { "page": "emoji_ambiguity", "title": "How ambiguous is each emoji?", "topics": [ "emoji_ambiguity" ] }, { "page": "emoji_categorize", "title": "Categorise each row by the emoji categories it contains", "topics": [ "emoji_categorize" ] }, { "page": "emoji_collocations", "title": "Which words keep company with which emoji", "topics": [ "emoji_collocations" ] }, { "page": "emoji_congruence", "title": "Text-emoji congruence", "topics": [ "emoji_congruence" ] }, { "page": "emoji_context", "title": "The text around each emoji occurrence", "topics": [ "emoji_context" ] }, { "page": "emoji_cooccurrence", "title": "Emoji co-occurrence counts, with an optional diagonal", "topics": [ "emoji_cooccurrence" ] }, { "page": "emoji_density", "title": "Emoji density per character and per token", "topics": [ "emoji_density" ] }, { "page": "emoji_dfm", "title": "Document-by-emoji feature matrix", "topics": [ "emoji_dfm" ] }, { "page": "emoji_emotion", "title": "Emoji emotion profiles (the 8 Plutchik emotions)", "topics": [ "emoji_emotion" ] }, { "page": "emoji_emotion_label", "title": "The dominant emoji emotion per row", "topics": [ "emoji_emotion_label" ] }, { "page": "emoji_emotion_lexicon", "title": "Emoji emotion lexicon (EmoTag1200)", "topics": [ "emoji_emotion_lexicon" ] }, { "page": "emoji_extract_nest", "title": "Add a list-column of the emoji found in each row", "topics": [ "emoji_extract_nest" ] }, { "page": "emoji_extract_unnest", "title": "Emoji counts per row, in long (tidy) form", "topics": [ "emoji_extract_unnest" ] }, { "page": "emoji_faceness", "title": "How face-heavy is each row's emoji use?", "topics": [ "emoji_faceness" ] }, { "page": "emoji_filter", "title": "Keep only the rows whose text contains emoji", "topics": [ "emoji_filter", "emoji_tweets" ] }, { "page": "emoji_flag_ambiguous", "title": "Which emoji in this corpus are most likely to be misread?", "topics": [ "emoji_flag_ambiguous" ] }, { "page": "emoji_frequency", "title": "Frequency of every emoji in a text column", "topics": [ "emoji_frequency" ] }, { "page": "emoji_incongruity", "title": "Text-emoji sentiment mismatch", "topics": [ "emoji_incongruity" ] }, { "page": "emoji_incongruity_profile", "title": "Which emoji go against the grain of their text?", "topics": [ "emoji_incongruity_profile" ] }, { "page": "emoji_lexicons", "title": "List bundled emoji lexicons", "topics": [ "emoji_lexicons" ] }, { "page": "emoji_ngrams", "title": "Consecutive emoji sequences (n-grams)", "topics": [ "emoji_ngrams" ] }, { "page": "emoji_pairs", "title": "Co-occurring emoji pairs", "topics": [ "emoji_pairs" ] }, { "page": "emoji_position", "title": "Where do emoji sit within each text?", "topics": [ "emoji_position" ] }, { "page": "emoji_provenance", "title": "Versions behind an emoji analysis, in one row", "topics": [ "emoji_provenance" ] }, { "page": "emoji_ratio", "title": "What share of the text is emoji, and is it emoji-only?", "topics": [ "emoji_ratio" ] }, { "page": "emoji_risk", "title": "Interpretation risk per row", "topics": [ "emoji_risk" ] }, { "page": "emoji_sanitize", "title": "Apply an explicit emoji policy to a text column", "topics": [ "emoji_sanitize" ] }, { "page": "emoji_score", "title": "Score emoji in a text column against any lexicon", "topics": [ "emoji_score" ] }, { "page": "emoji_search", "title": 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"topics": [ "emoji_trend" ] }, { "page": "emoji_turnover", "title": "Emoji vocabulary churn between consecutive periods", "topics": [ "emoji_turnover" ] }, { "page": "emoji_type", "title": "Which functional types of emoji does each row use?", "topics": [ "emoji_type" ] }, { "page": "emoji_unicode_crosswalk", "title": "Emoji name, unicode and category crosswalk", "topics": [ "emoji_unicode_crosswalk" ] }, { "page": "emoji_unicode_releases", "title": "Unicode and Unicode Emoji release dates", "topics": [ "emoji_unicode_releases" ] }, { "page": "emoji_unicode_version", "title": "Which Unicode emoji version does this build reflect?", "topics": [ "emoji_unicode_version" ] }, { "page": "emoji_version_profile", "title": "How new is this corpus's emoji repertoire?", "topics": [ "emoji_version_profile" ] }, { "page": "register_emoji_lexicon", "title": "Register a custom emoji lexicon", "topics": [ "register_emoji_lexicon" ] }, { "page": "text_to_emoji", "title": "Replace shortcodes with emoji (emojize)", "topics": [ "text_to_emoji" ] }, { "page": "top_n_emojis", "title": "The most frequent emoji in a text column", "topics": [ "top_n_emojis" ] } ], "_pkglogo": "https://github.com/pursuitofdatascience/tidyemoji/raw/HEAD/man/figures/logo.svg", "_readme": "https://github.com/pursuitofdatascience/tidyemoji/raw/HEAD/README.md", "_rundeps": [ "cli", "cpp11", "dplyr", "emoji", "generics", "glue", "lifecycle", "magrittr", "pillar", "pkgconfig", "purrr", "R6", "rlang", "stringi", "stringr", "tibble", "tidyr", "tidyselect", "utf8", "vctrs", "withr" ], "_vignettes": [ { "source": "introduction.Rmd", "filename": "introduction.html", "title": "Introduction to tidyEmoji", "author": "Youzhi YuUniversity of Chicago", "engine": "knitr::rmarkdown", "headings": [ "Overview", "Example data", "Detecting and summarising emoji", "emoji_summary()", "emoji_filter()", "Extracting emoji", "emoji_extract_nest()", "emoji_extract_unnest()", "emoji_tokens()", "A note on grapheme-aware detection", 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