Sign inGet started
Repository · GitHub

fhamborg/NewsMTSC

Target-dependent sentiment classification in news articles reporting on political events. Includes a high-quality data set of over 11k sentences and a state-of-the-art classification model.

Ownerfhamborg
Stars157
Forks20
Main languagePython
Created8 April 2021
Last updated at source18 July 2025
pythoncudadatasetdeep-learningnews-articlespytorchsentiment-analysissentiment-classificationtext-classificationtsc
Embed this entry
<iframe src="https://silytics.si/embed/item/13f35004-da52-40df-be96-d889259c10ad" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Stars, last 5 days

157 now. Counts as reported by the source, snapshotted daily by Silytics.

More from fhamborg

Silytics shows public metadata from GitHub and links to the original. Information may be incomplete or out of date. Last refreshed 20 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.