{ "_id": "6a1f08ffb401979e7341c246", "Package": "conText", "Version": "3.0.1", "Title": "'a la Carte' on Text (ConText) Embedding Regression", "Description": "A fast, flexible and transparent framework to estimate\ncontext-specific word and short document embeddings using the\n'a la carte' embeddings approach developed by Khodak et al.\n(2018) and evaluate hypotheses\nabout covariate effects on embeddings using the regression\nframework developed by Rodriguez et al.\n(2021). New version of the\npackage applies a new estimator to measure the distance between\nword embeddings as described in Green et al. (2025)\n.", "Authors@R": "c(\nperson(\"Pedro L.\", \"Rodriguez\", email = \"pedro.rodriguezsosa@gmail.com\", role = c(\"aut\", \"cph\"), comment = c(ORCID = \"0000-0003-4762-4550\")),\nperson(\"Arthur\", \"Spirling\", email = \"as9934@nyu.edu\", role = \"aut\", comment = c(ORCID = \"0000-0001-9959-1805\")),\nperson(\"Brandon\", \"Stewart\", email = \"bms4@princeton.edu\", role = \"aut\", comment = c(ORCID = \"0000-0002-7657-3089\")),\nperson(\"Christopher\", \"Barrie\", email = \"christopher.barrie@ed.ac.uk\", role = \"ctb\", comment = c(ORCID = \"0000-0002-9156-990X\")),\nperson(\"Sofia\", \"Avila\", email = \"sofiaavila@princeton.edu\", role = c(\"cre\",\"aut\"), comment = c(ORCID = \"0009-0007-8746-6688\"))\n)", "License": "GPL-3", "URL": "https://github.com/prodriguezsosa/conText", "BugReports": "https://github.com/prodriguezsosa/ConText/issues", "Maintainer": "Sofia Avila ", "Encoding": "UTF-8", "LazyData": "true", "VignetteBuilder": "knitr", "Language": "en-US", "RoxygenNote": "7.3.3", "Roxygen": "list(markdown = TRUE)", "Config/testthat/edition": "3", "Config/pak/sysreqs": "libicu-dev libxml2-dev", "Repository": "https://prodriguezsosa.r-universe.dev", "Date/Publication": "2026-04-18 03:54:57 UTC", "RemoteUrl": "https://github.com/prodriguezsosa/context", "RemoteRef": "HEAD", "RemoteSha": "f6e1629d363a306b7aa6d2b97445dc38b4e76ff9", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-18 06:16:25 UTC", "User": "root" }, "Author": "Pedro L. Rodriguez [aut, cph] (ORCID:\n),\nArthur Spirling [aut] (ORCID: ),\nBrandon Stewart [aut] (ORCID: ),\nChristopher Barrie [ctb] (ORCID:\n),\nSofia Avila [cre, aut] (ORCID: )", "MD5sum": "3e815ce433fe85dd5cc1875a944757da", "_user": "prodriguezsosa", "_type": "src", "_file": "conText_3.0.1.tar.gz", "_fileid": "01c15d15a4f00e53a58c0ffb12f48ad3566ea32696b6196455df3442ff9f7d73", "_filesize": 2375791, "_sha256": "01c15d15a4f00e53a58c0ffb12f48ad3566ea32696b6196455df3442ff9f7d73", "_created": "2026-05-18T06:16:25.000Z", "_published": "2026-06-02T16:46:55.226Z", "_distro": "noble", "_jobs": [ { "job": 79124080204, "time": 222, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7050781449" }, { "job": 79124080605, "time": 188, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7050773710" }, { "job": 79124080216, "time": 226, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7050773290" }, { "job": 79124080288, "time": 201, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7050769603" }, { "job": 79124079494, "time": 268, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7050732173" }, { "job": 79124079634, "time": 125, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7364177696" }, { "job": 79124080291, "time": 136, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7050762168" }, { "job": 79124080369, "time": 134, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7050761352" }, { "job": 79124080350, "time": 129, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7050760473" } ], "_buildurl": "https://github.com/r-universe/prodriguezsosa/actions/runs/26016720701", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/prodriguezsosa/context", "_commit": { "id": "f6e1629d363a306b7aa6d2b97445dc38b4e76ff9", "author": "sofiaaj <47996697+sofiaaj@users.noreply.github.com>", "committer": "sofiaaj <47996697+sofiaaj@users.noreply.github.com>", "message": "quickstart typo\n", "time": 1776484497 }, "_maintainer": { "name": "Sofia Avila", "email": "sofiaavila@princeton.edu" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.6.0", "role": "Depends" }, { "package": "dplyr", "role": "Imports" }, { "package": "Matrix", "version": ">= 1.3-2", "role": "Imports" }, { "package": "quanteda", "version": ">= 3.0.0", "role": "Imports" }, { "package": "text2vec", "version": ">= 0.6", "role": "Imports" }, { "package": "reshape2", "version": ">= 1.4.4", "role": "Imports" }, { "package": "fastDummies", "version": ">= 1.6.3", "role": "Imports" }, { "package": "stringr", "version": ">= 1.4.0", "role": "Imports" }, { "package": "tidyr", "version": ">= 1.1.3", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "broom", "role": "Imports" }, { "package": "foreach", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "estimatr", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "tidyselect", "role": "Imports" }, { "package": "SnowballC", "version": ">= 0.7.0", "role": "Suggests" }, { "package": "hunspell", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "formatR", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "doParallel", "role": "Suggests" }, { "package": "data.table", "role": "Suggests" }, { "package": "RcppParallel", "role": "Suggests" } ], "_owner": "prodriguezsosa", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-31", "n": 2 }, { "week": "2025-32", "n": 3 }, { "week": "2025-34", "n": 12 }, { "week": "2026-15", "n": 3 }, { "week": "2026-16", "n": 2 } ], "_tags": [], "_stars": 109, "_contributors": [ { "user": "prodriguezsosa", "count": 134, "uuid": 6556873 }, { "user": "sofiaaj", "count": 39, "uuid": 47996697 }, { "user": "arthurspirling", "count": 13, "uuid": 19141534 }, { "user": "cjbarrie", "count": 8, "uuid": 29574597 }, { "user": "elisawirsching", "count": 2, "uuid": 75432455 }, { "user": "charliecarter", "count": 1, "uuid": 10161310 }, { "user": "davidycliao", "count": 1, "uuid": 35374714 }, { "user": "mlburnham", "count": 1, "uuid": 41241150 } ], "_userbio": { "uuid": 6556873, "type": "user", "name": "Pedro L. Rodríguez", "description": "Research Scientist in Core Data Science at Meta." }, "_downloads": { "count": 641, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/conText" }, "_devurl": "https://github.com/prodriguezsosa/context", "_searchresults": 2368, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/conText.html", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/prodriguezsosa/context", "_realowner": "prodriguezsosa", "_cranurl": true, "_releases": [ { "version": "1.0.0", "date": "2021-10-25" }, { "version": "1.1.0", "date": "2022-04-05" }, { "version": "1.4.2", "date": "2023-01-14" }, { "version": "1.4.3", "date": "2023-02-09" }, { "version": "3.0.0", "date": "2025-09-03" }, { "version": "3.0.1", "date": "2026-04-12" } ], "_exports": [ "bootstrap_contrast", "bootstrap_nns", "compute_contrast", "compute_transform", "conText", "contrast_nns", "cos_sim", "dem", "dem_group", "dem_sample", "embed_target", "feature_sim", "fem", "find_nns", "get_context", "get_cos_sim", "get_grouped_similarity", "get_local_vocab", "get_ncs", "get_nns", "get_nns_ratio", "get_seq_cos_sim", "ncs", "nns", "nns_ratio", "permute_contrast", "plot_nns_ratio", "prototypical_context", "tokens_context" ], "_datasets": [ { "name": "cr_glove_subset", "title": "GloVe subset", "object": "cr_glove_subset", "class": [ "matrix", "array" ], "fields": {}, "rows": 500, "table": true, "tojson": true }, { "name": "cr_sample_corpus", "title": "Congressional Record sample corpus", "object": "cr_sample_corpus", "class": [ "corpus", "character" ], "fields": [], "table": false, "tojson": true }, { "name": "cr_transform", "title": "Transformation matrix", "object": "cr_transform", "class": [ "matrix", "array" ], "fields": {}, "rows": 300, "table": true, "tojson": true } ], "_help": [ { "page": "bootstrap_contrast", "title": "Bootstrap similarity and ratio computations", "topics": [ "bootstrap_contrast" ] }, { "page": "bootstrap_nns", "title": "Bootstrap nearest neighbors", "topics": [ "bootstrap_nns" ] }, { "page": "bootstrap_similarity", "title": "Boostrap similarity vector", "topics": [ "bootstrap_similarity" ] }, { "page": "build_conText", "title": "build a 'conText-class' object", "topics": [ "build_conText" ] }, { "page": "build_dem", "title": "build a 'dem-class' object", "topics": [ "build_dem" ] }, { "page": "build_fem", "title": "build a 'fem-class' object", "topics": [ "build_fem" ] }, { "page": "compute_contrast", "title": "Compute similarity and similarity ratios", "topics": [ "compute_contrast" ] }, { "page": "compute_similarity", "title": "Compute similarity vector (sub-function of bootstrap_similarity)", "topics": [ "compute_similarity" ] }, { "page": "compute_transform", "title": "Compute transformation matrix A", "topics": [ "compute_transform" ] }, { "page": "conText", "title": "Embedding regression", "topics": [ "conText" ] }, { "page": "contrast_nns", "title": "Contrast nearest neighbors", "topics": [ "contrast_nns" ] }, { "page": "cos_sim", "title": "Compute the cosine similarity between one or more ALC embeddings and a set of features.", "topics": [ "cos_sim" ] }, { "page": "cr_glove_subset", "title": "GloVe subset", "topics": [ "cr_glove_subset" ] }, { "page": "cr_sample_corpus", "title": "Congressional Record sample corpus", "topics": [ "cr_sample_corpus" ] }, { "page": "cr_transform", "title": "Transformation matrix", "topics": [ "cr_transform" ] }, { "page": "dem", "title": "Build a document-embedding matrix", "topics": [ "dem" ] }, { "page": "dem_group", "title": "Average document-embeddings in a dem by a grouping variable", "topics": [ "dem_group" ] }, { "page": "dem_sample", "title": "Randomly sample documents from a dem", "topics": [ "dem_sample" ] }, { "page": "embed_target", "title": "Embed target using either: (a) a la carte OR (b) simple (untransformed) averaging of context embeddings", "topics": [ "embed_target" ] }, { "page": "feature_sim", "title": "Given two feature-embedding-matrices, compute \"parallel\" cosine similarities between overlapping features.", "topics": [ "feature_sim" ] }, { "page": "fem", "title": "Create an feature-embedding matrix", "topics": [ "fem" ] }, { "page": "find_cos_sim", "title": "Find cosine similarities between target and candidate words", "topics": [ "find_cos_sim" ] }, { "page": "find_nns", "title": "Return nearest neighbors based on cosine similarity", "topics": [ "find_nns" ] }, { "page": "get_context", "title": "Get context words (words within a symmetric window around the target word/phrase) sorrounding a user defined target.", "topics": [ "get_context" ] }, { "page": "get_cos_sim", "title": "Given a tokenized corpus, compute the cosine similarities of the resulting ALC embeddings and a defined set of features.", "topics": [ "get_cos_sim" ] }, { "page": "get_grouped_similarity", "title": "Get averaged similarity scores between target word(s) and one or two vectors of candidate words.", "topics": [ "get_grouped_similarity" ] }, { "page": "get_local_vocab", "title": "Identify words common to a collection of texts and a set of pretrained embeddings.", "topics": [ "get_local_vocab" ] }, { "page": "get_ncs", "title": "Given a set of tokenized contexts, find the top N nearest contexts.", "topics": [ "get_ncs" ] }, { "page": "get_nns", "title": "Given a tokenized corpus and a set of candidate neighbors, find the top N nearest neighbors.", "topics": [ "get_nns" ] }, { "page": "get_nns_ratio", "title": "Given a corpus and a binary grouping variable, computes the ratio of cosine similarities over the union of their respective N nearest neighbors.", "topics": [ "get_nns_ratio" ] }, { "page": "get_seq_cos_sim", "title": "Calculate cosine similarities between target word and candidates words over sequenced variable using ALC embedding approach", "topics": [ "get_seq_cos_sim" ] }, { "page": "ncs", "title": "Given a set of embeddings and a set of tokenized contexts, find the top N nearest contexts.", "topics": [ "ncs" ] }, { "page": "nns", "title": "Given a set of embeddings and a set of candidate neighbors, find the top N nearest neighbors.", "topics": [ "nns" ] }, { "page": "nns_ratio", "title": "Computes the ratio of cosine similarities for two embeddings over the union of their respective top N nearest neighbors.", "topics": [ "nns_ratio" ] }, { "page": "permute_contrast", "title": "Permute similarity and ratio computations", "topics": [ "permute_contrast" ] }, { "page": "plot_nns_ratio", "title": "Plot output of 'get_nns_ratio()'", "topics": [ "plot_nns_ratio" ] }, { "page": "prototypical_context", "title": "Find most \"prototypical\" contexts.", "topics": [ "prototypical_context" ] }, { "page": "run_ols", "title": "Run OLS", "topics": [ "run_ols" ] }, { "page": "tokens_context", "title": "Get the tokens of contexts sorrounding user defined patterns", "topics": [ "tokens_context" ] } ], "_readme": "https://github.com/prodriguezsosa/context/raw/HEAD/README.md", "_rundeps": [ "backports", "broom", "cli", "codetools", "cpp11", "data.table", "digest", "dplyr", "estimatr", "farver", "fastDummies", "fastmatch", "float", "foreach", "Formula", "generics", "ggplot2", "glue", "gtable", "isoband", "ISOcodes", "iterators", "jsonlite", "labeling", "lattice", "lgr", "lifecycle", "magrittr", "Matrix", "MatrixExtra", "mlapi", "pillar", "pkgconfig", "plyr", "purrr", "quanteda", "R6", "RColorBrewer", "Rcpp", "RcppArmadillo", "RcppEigen", "reshape2", "RhpcBLASctl", "rlang", "rsparse", "S7", "scales", "SnowballC", "stopwords", "stringi", "stringr", "text2vec", "tibble", "tidyr", "tidyselect", "utf8", "vctrs", "viridisLite", "withr", "xml2", "yaml" ], "_vignettes": [ { "source": "quickstart.Rmd", "filename": "quickstart.html", "title": "Quick Start Guide", "engine": "knitr::rmarkdown", "headings": [ "Preliminaries", "Setup", "Installing the package", "Load package", "Data", "Pre-processing", "The building blocks of 'a la carte' embeddings", "1. Build a (tokenized) corpus of contexts", "2. Build a document-feature-matrix", "3. Build a document-embedding-matrix", "4. Average over document embeddings", "5. Comparing group embeddings", "Nearest neighbors", "Cosine similarity", "Nearest neighbors cosine similarity ratio", "Nearest contexts", "Stemming", "Multiple Keywords", "Wrapper functions", "Embedding regression", "Bias correction in earlier versions of package", "From regression coefficients to ALC embeddings", "Local GloVe and transformation matrix", "Estimate GloVe embeddings", "Estimating the transformation matrix", "Other", "Feature embedding matrix", "Embedding full (short) documents" ], "created": "2021-03-06 20:17:23", "modified": "2026-04-18 03:54:57", "commits": 24 } ], "_score": 9.6548462446778, "_indexed": true, "_nocasepkg": "context", "_universes": [ "prodriguezsosa" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "3.0.1", "date": "2026-05-18T06:19:24.000Z", "distro": "noble", "commit": "f6e1629d363a306b7aa6d2b97445dc38b4e76ff9", "fileid": "d3123dde52f9870a82b88f8a04e434ac29d6244696e8d4f7180ad7851fce9be9", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/prodriguezsosa/actions/runs/26016720701" }, { "r": "4.6.0", "os": "linux", "version": "3.0.1", "date": "2026-05-18T06:18:53.000Z", "distro": "noble", "commit": "f6e1629d363a306b7aa6d2b97445dc38b4e76ff9", "fileid": "312141a52a0583eb014a1b353d9613db1067035dbd208e52a36a31cb4630a44e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/prodriguezsosa/actions/runs/26016720701" }, { "r": "4.5.3", "os": "mac", "version": "3.0.1", "date": "2026-05-18T06:19:00.000Z", "commit": "f6e1629d363a306b7aa6d2b97445dc38b4e76ff9", "fileid": "b9cb842233a8fb544a9139ee3706276f55ca0d7c01a21fc5744ffd4e280245df", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/prodriguezsosa/actions/runs/26016720701" }, { "r": "4.6.0", "os": "mac", "version": "3.0.1", "date": "2026-05-18T06:18:39.000Z", "commit": "f6e1629d363a306b7aa6d2b97445dc38b4e76ff9", "fileid": "def163d9a73e0a8ad7aee5862b4770ecfa374c561b15288376dee08c0e59fcea", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/prodriguezsosa/actions/runs/26016720701" }, { "r": "4.7.0", "os": "win", "version": "3.0.1", "date": "2026-05-18T06:17:55.000Z", "commit": "f6e1629d363a306b7aa6d2b97445dc38b4e76ff9", "fileid": "cd32ae9fc6ba24d550a256fde281743b7ebf0c4b36c56098e8bab042f257a5d2", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/prodriguezsosa/actions/runs/26016720701" }, { "r": "4.5.3", "os": "win", "version": "3.0.1", "date": "2026-05-18T06:17:53.000Z", "commit": "f6e1629d363a306b7aa6d2b97445dc38b4e76ff9", "fileid": "8ef35a88e38efcd21629b1a2c26158c08d830a0c4bc389b4825193d732e914b3", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/prodriguezsosa/actions/runs/26016720701" }, { "r": "4.6.0", "os": "win", "version": "3.0.1", "date": "2026-05-18T06:17:51.000Z", "commit": "f6e1629d363a306b7aa6d2b97445dc38b4e76ff9", "fileid": "053b8dfbd56653e31805a6e9babcfb1c342d879cfd10312d491d70c9f5bbb0a5", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/prodriguezsosa/actions/runs/26016720701" }, { "r": "4.6.0", "os": "wasm", "version": "3.0.1", "date": "2026-06-02T16:46:35.000Z", "commit": "f6e1629d363a306b7aa6d2b97445dc38b4e76ff9", "fileid": "78f1530810f5cb2f2b29abe4ac4326b85e7bbcb18a3f57a7ae4e5cda26d6076e", "status": "success", "buildurl": "https://github.com/r-universe/prodriguezsosa/actions/runs/26016720701" } ] }