German Twitter Titling Corpus
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The German Titling Twitter Corpus consists of 1904 stance-annotated tweets collected in June/July 2018 mentioning 24 German politicians with a doctoral degree. The Addendum contains an additional 296 stance-annotated tweets from each month of 2018 mentioning 10 politicians with a doctoral degree, of whom 6 from a left-leaning political party and 4 from a right-leaning political party' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["annotated corpus","framing","German corpus","naming","sentiment","social media","stance","Twitter"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The German Titling Twitter Corpus consists of 1904 stance-annotated tweets collected in June/July 2018 mentioning 24 German politicians with a doctoral degree. The Addendum contains an additional 296 stance-annotated tweets from each month of 2018 mentioning 10 politicians with a doctoral degree, of whom 6 from a left-leaning political party and 4 from a right-leaning political party' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The German Titling Twitter Corpus consists of 1904 stance-annotated tweets collected in June/July 2018 mentioning 24 German politicians with a doctoral degree. The Addendum contains an additional 296 stance-annotated tweets from each month of 2018 mentioning 10 politicians with a doctoral degree, of whom 6 from a left-leaning political party and 4 from a right-leaning political party
annotated corpus; framing; German corpus; naming; sentiment; social media; stance; Twitter