sileod/DiscSense
Automated Semantic Analysis of Discourse Markers
This project helps researchers and linguists understand how common discourse markers like 'therefore', 'personally', or 'sadly' relate to specific semantic meanings in text. It takes a discourse marker and provides a probability that it is associated with a certain sentiment (e.g., negative) or a specific type of discourse (e.g., condition), helping you analyze the nuanced meaning expressed in written language. It's for anyone studying natural language, particularly those interested in pragmatics, sentiment, or discourse analysis.
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Use this if you need to quantify the semantic associations of discourse markers in text, for example, to understand how 'however' influences the likelihood of an opposing argument.
Not ideal if you need to perform real-time, high-throughput semantic analysis on large volumes of diverse text, as this is a research-focused dataset of associations.
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May 30, 2022
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Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/sileod/DiscSense"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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