Glossary#
Terms as they are used on the Swiss-AL Platform and in this documentation. Entries are alphabetical; use your browser’s find function or the index to locate a term quickly.
- Absolute frequency#
The raw number of times something occurs in a corpus. Not comparable between corpora of different sizes — see relative frequency.
- Advanced Search#
The search mode that accepts CQP queries, allowing you to combine annotations, match sequences of words, and use regular expressions. See Advanced Search.
- Algorithm#
A systematic sequence of operations used to solve a problem or process data.
- Annotation#
Information added to a text by automatic analysis rather than present in the original — lemma, part of speech, and named entity labels are all annotations. Added by the pipeline.
- Background topic#
A topic that collects high-frequency, general-purpose words rather than representing a distinct theme. Most models produce one or two.
- Basic Search#
The search mode that matches words exactly as written and supports truncation, OR, and part of speech filtering. See Basic Search.
- Category#
A grouping of corpus sources used to break down results. Which categories exist depends on the corpus type.
- Coherence score#
A measure of how semantically similar a topic’s top words are to each other. Used to rank the documents most strongly associated with a topic.
- Collocation#
- Common pairing#
- Co-occurrence#
Words that frequently occur together within a context window. Such recurring combinations can reveal conventional patterns of language use. On the platform, measured with LogDice. See Common Pairings.
- Context window#
A span of n words before and after a search term, within which co-occurrence is counted. Five words either side is the default for both common pairings and word embeddings.
- Corpus#
A structured collection of texts assembled for linguistic analysis. See Corpora.
- Corpus keywords#
Words that occur considerably more frequently in a study corpus than in a reference corpus. Distinct from document keywords. See Keywords.
- Corpus type#
The category a corpus belongs to — organizational, journalistic, parliamentary, project, or demo. The type determines how the corpus sources are subcategorized. See Corpus types.
- Cosine similarity#
A measure of how similar two word vectors are, based on the angle between them rather than the distance between their endpoints. Higher values mean more similar contexts of use.
- CQP#
- Corpus Query Processor#
A query language for searching corpora using complex patterns and annotations, used by Advanced Search.
- Demo corpus#
A subset of an organizational corpus, created for testing and demonstration. The only corpora accessible without registration. See Demo Corpora.
- Distributional hypothesis#
The principle that words occurring in similar contexts tend to have similar meanings. The basis of semantic space methods.
- Document keywords#
Words that occur more frequently in an individual document than in the corpus as a whole, adjusted for text length. Distinct from corpus keywords.
- Field of activity#
A subcategory of organizational corpus sources, such as federation or trade association. Paired with social system.
- Gibbs sampling#
The iterative procedure by which LDA reassigns words to topics until the assignments stabilize.
- KWIC#
- Key Word in Context#
A display format showing each occurrence of a search term with its immediate context, the search term aligned down the centre. See Context of Words.
- LDA#
- Latent Dirichlet Allocation#
The topic model used on the platform. A probabilistic model that treats documents as mixtures of topics and topics as distributions over words.
- Lemma#
The base form of a word, under which it is listed in a dictionary — go for goes and went. Grouping by lemma collects all inflected forms together.
- Lemmatization#
- Log likelihood ratio#
- LLR#
A measure of how confident we can be that a word’s frequency difference between two corpora is not due to chance. Takes corpus size into account. Does not measure the size of the difference.
- Log ratio#
A measure of the size of a frequency difference between two corpora, expressed as the binary logarithm of the ratio of relative frequencies. Each additional point represents a doubling.
- LogDice#
The association measure used for common pairings. Runs to a theoretical maximum of 14, with each point representing a doubling of association strength. Independent of corpus size.
- Media type#
A subcategory of journalistic corpus sources, such as daily/online newspaper or radio/tv. Paired with publisher.
- Metadata#
Information about a text rather than its content — its date, source, title, and categories.
- Moving average#
A smoothing technique that plots the average frequency over a rolling window of days, reducing daily fluctuation so longer trends become visible.
- Named entity#
A token or sequence of tokens referring to a specific person, organization, place, or similar. Annotated automatically and searchable in Advanced Search.
- Nearest neighbour#
The words closest to a given word in a semantic space, meaning those used in the most similar contexts. Not necessarily words with similar meanings.
- OER#
- Open Educational Resources#
Teaching and learning materials published under an open licence that permits reuse and adaptation. See Open Educational Resources.
- ORD#
- Open Research Data#
Scientific research data that is publicly accessible, to promote transparency and reuse.
- Parent corpus#
The corpus a subcorpus was derived from. In a keyword analysis it serves as the reference corpus.
- Part of speech#
- PoS#
The grammatical category of a word, such as noun, verb, or adjective.
- Pipeline#
The sequence of processing steps that extracts, filters, and annotates text before it enters a corpus. See Swiss-AL Pipeline.
- Project#
A workspace container grouping your corpora and analyses. Creating one is required for access to the full corpus collection.
- Publisher#
A subcategory of journalistic corpus sources, identifying who published a text. Paired with media type.
- Quick Search#
The simplest search mode: case-insensitive, matching all forms in a word’s paradigm. See Quick Search.
- Reference corpus#
The corpus a study corpus is compared against in a keyword analysis. For a subcorpus, this is its parent corpus, with the overlapping documents excluded.
- Regular expressions#
- Regex#
A pattern-matching notation for describing sets of strings, available in Advanced Search.
- Relative frequency#
A frequency count normalized by corpus size, allowing comparison between corpora of different sizes. Usually expressed in words per million.
- Semantic space#
- Vector space#
A mathematical representation of word meanings, in which words are positioned according to the contexts they occur in. Words used similarly sit closer together. See Semantic Space.
- Social system#
A subcategory of organizational corpus sources — politics, industry, science, or civil society. Paired with field of activity.
- Source#
A publication, website, or institution that texts in a corpus come from. Subcategorized according to the corpus type.
- STTS#
- Stuttgart-Tübingen Tagset#
The tagset used to annotate part of speech in the German corpora. See Tagsets.
- Study corpus#
The corpus under investigation in a keyword analysis, compared against a reference corpus.
- Subcorpus#
A corpus you build yourself by filtering a larger one by category, time span, source, or keyword. Required for corpus keywords. See Creating subcorpora.
- t-SNE#
A dimensionality reduction technique used to draw high-dimensional data in two or three dimensions. Preserves local neighbourhoods better than global structure, so proximity is more meaningful than distance.
- Tag#
A label attached to a token indicating its word class or grammatical properties.
- Tagset#
The full inventory of tags used for a language. See Tagsets.
- Token#
A single unit of a text — a word, number, or punctuation mark. Corpus size is measured in tokens.
- Topic#
A cluster of words that frequently appear together across a set of documents and together suggest a common theme. See Topics.
- Topic model#
A method for discovering topics in a collection of documents without being told in advance what those topics are.
- Type#
A distinct word form in a corpus, as opposed to each of its occurrences. A text with 100 tokens may contain only 60 types.
- Word embedding#
A word vector learned from a corpus by a model such as word2vec. See Semantic Space.
- Word vector#
A numerical representation of a word in a semantic space, derived from the contexts the word occurs in.
- word2vec#
The algorithm used on the platform to learn word embeddings, implemented via the Python library gensim.
- Words per million#
- WPM#
A relative frequency measure, standardized per 1,000,000 tokens, allowing comparison across corpora of different sizes.
- Workspace#
The Swiss-AL interface: corpus and tool selection on the left, tabbed analysis area in the centre. See Quickstart Guide.