Relationship Between Poetic Meter and Meaning in Accentual-Syllabic Verse (data and replication code)

<strong>main.py</strong>: script to train both lda and word2vec models <strong>main.ipynb</strong>: Jupyter Notebook containing all the analyses reported in the paper <strong>pos.ipynb</strong>: clustering based on frequencies of parts-of-speech <strong>corpora</strong>: contains original data for Czech, English, and Dutch poetry in JSON (proprietary German and Russian not included) <pre><code>{ &lt;= Each item in the following lists corresponds to particular poem and holds: 'words': [] &lt;= list of lemmata found in the poem 'pos_tags': [] &lt;= their POS-tags (Positional Morphological Tags for Czech, MyStem for Russian, TreeTagger tagsets for other corpora) 'meters': [[]] &lt;= list of meters found in poem 'years': [] &lt;= year when poem published (year when author born in case of English) 'n_words': [] &lt;= number of words 'n_lines': [] &lt;= number of lines 'authors': [] &lt;= author of the poem 'titles': [] &lt;= title of the poem 'schemes': [] &lt;= line-ending schemes } </code></pre> <strong>dicts</strong>: contains Gensim dictionary files for all 5 corpora <strong>fig</strong>: contains all resulting figures <strong>json</strong> <strong>&gt; metadata:</strong> contains all metadata on poems in particular corpora <pre><code>{ &lt;= Each item in the following lists corresponds to particular poem and holds: 'meters': [[]] &lt;= list of meters found in poem 'years': [] &lt;= year when poem published (year when author born in case of English) 'n_words': [] &lt;= number of words 'n_lines': [] &lt;= number of lines 'authors': [] &lt;= author of the poem 'titles': [] &lt;= title of the poem } </code></pre> <strong>json &gt; topics:</strong> contains topic probabilities in particular poems <pre><code>[ &lt;= each item corresponds to particular poem and comprise 100-dimensional dict { 'topic title': its probability in poem } ] </code></pre> <strong>json &gt; pos:</strong> contains POS relative frequencies in particular poems <pre><code>[ &lt;= each item corresponds to particular poem { 'POS': its frequency } ] </code></pre> <strong>json &gt; w2v:</strong> contains mapping of lemmata and their neighbours in word2vec models <strong>models</strong>: contains pretrained lda and word2vec models (Gensim)