Changes in version 1.5.2 (2026-04-06) - Add nested_weight to textmodel_lss() and as.textmodel_lss() to perform dictionary-like analysis. - Remove auto_weight from textmodel_lss() and cut from predict(). Changes in version 1.5.1 (2025-12-09) - Support textmodel_wordvector objects from wordvector v0.6.0. Changes in version 1.5.0 (2025-09-12) - Add textmodel_lss.tokens() to use wordvector::textmodel_word2vec() as the underlying engine. - Rename w to k in textmodel_lss.fcm() to make it consistent with other methods. Changes in version 1.4.5 (2025-06-19) - Enable grouping by multiple variables using smooth_lss(). - Fix tests for textplot_*() for upcoming ggplot2. Changes in version 1.4.4 (2025-05-23) - Fix a bug in as.textmodel_lss() when a textmodel_wordvector object is given. - Add sampling to textplot_terms() to improve highlighting of words when the distribution of polarity scores is asymmetric. Changes in version 1.4.3 (2025-04-22) - Improve the handling of textmodel_wordvector objects from the wordvector package in as.textmodel_lss(). - Deprecate auto_weight in textmodel_lss(). - Deprecate textplot_simil(). Changes in version 1.4.2 (2025-01-08) - Add as.textmodel_lss() for objects from the wordvector package. - Reduce dependent packages by moving rsparse, irlba and rsvd to Suggests. - Fix handling of phrasal patterns in textplot_terms(). - Improve objects created by as.textmodel_lss.textmodel_lss(). Changes in version 1.4.1 - Add group to smooth_lss() to smooth LSS scores by group. - Add optimize_lss() as an experimental function. Changes in version 1.4.0 (2024-03-05) - Change the default value to max_highlighted = 1000 in textplot_terms(). - Add ... to customize text labels to textplot_terms(). - Highlight words in different colors when a dictionary is passed to highlighted. - Add mode = "predict" and remove = FALSE to bootstrap_lss(). Changes in version 1.3.2 (2023-12-20) - Fix the error in textplot_terms() when the frequency of terms are zero (#85). Changes in version 1.3.1 (2023-02-26) - Fix the range of scores when cut is used. - Add bootstrap_lss() as an experimental function. Changes in version 1.3.0 (2023-01-22) - Add cut to predict. - Move examples to the new package website: http://koheiw.github.io/LSX. - Rename "rescaling" to "rescale" for simplicity and consistency. - Improve random sampling of words to highlight in textplot_terms() to avoid congestion. Changes in version 1.2.0 (2022-12-04) - Add group_data to textmodel_lss() to simplify the workflow. - Add max_highlighted to textplot_terms() to automatically highlight polarity words. Changes in version 1.1.4 - Update as.textmodel_lss() to avoid errors in textplot_terms() when terms is used. Changes in version 1.1.3 (2022-10-19) - Restore examples for textmodel_lss(). - Defunct char_keyness() that has been deprecated for long. Changes in version 1.1.2 (2022-10-02) - Update examples to pass CRAN tests. Changes in version 1.1.1 (2022-02-26) - Add min_n to predict() to make polarity scores of short documents more stable. Changes in version 1.1.0 (2022-02-24) - Add as.textmodel_lss() for textmodel_lss objects to allow modifying existing models. - Allow terms in textmodel_lss() to be a named numeric vector to give arbitrary weights. Changes in version 1.0.2 (2021-09-18) - Add the auto_weight argument to textmodel_lss() and as.textmodel_lss() to improve the accuracy of scaling. - Remove the group argument from textplot_simil() to simplify the object. - Make as.seedwords() to accept multiple indices for upper and lower. Changes in version 1.0.0 (2021-07-20) - Add max_count to textmodel_lss.fcm() that will be passed to x_max in rsparse::GloVe$new(). - Add max_words to textplot_terms() to avoid overcrowding. - Make textplot_terms() to work with objects from textmodel_lss.fcm(). - Add concatenator to as.seedwords(). Changes in version 0.9.9 (2021-04-19) - Correct how textstat_context() and char_context() computes statistics. - Deprecate char_keyness(). Changes in version 0.9.8 (2021-03-22) - Stop using functions and arguments deprecated in quanteda v3.0.0. Changes in version 0.9.7 (2021-03-08) - Make as.textmodel_lss.matrix() more reliable. - Remove quanteda.textplots from dependencies. Changes in version 0.9.6 (2020-12-17) - Updated to reflect changes in quanteda (creation of quanteda.textstats). Changes in version 0.9.4 (2020-11-02) - Fix char_context() to always return more frequent words in context. - Experimental textplot_factor() has been removed. - as.textmodel_lss() takes a pre-trained word-embedding. Changes in version 0.9.3 - Add textstat_context() and char_context() to replace char_keyness(). - Make the absolute sum of seed weight equal to 1.0 in both upper and lower ends. - textplot_terms() takes glob patterns in character vector or a dictionary object. - char_keyness() no longer raise error when no patter is found in tokens object. - Add engine to smooth_lss() to apply locfit() to large datasets. Changes in version 0.9.2 (2020-09-22) - Updated unit tests for the new versions of stringi and quanteda. Changes in version 0.9.0 (2020-09-09) - Renamed from LSS to LSX for CRAN submission. Changes in version 0.8.7 - Added textplot_terms() to improve visualization of model terms.