Age Bias Training and Testing Data
<|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:'Training and testing data annotated by a panel survey sample of older adults (aged 50+) and used to create a basic, maximum entropy bag-of-words sentiment classifier. Testing data is scraped from blog posts discussing aging authored by older adults (see published work: https://doi.org/10.1145/3173574.3173986).Training data is a re-annotated subset of the Sentiment140 training data set containing the strings 'old' and 'young' (see Sentiment140: http://help.sentiment140.com/for-students). For model building, the subset was re-introduce into the full data set, replacing the original annotations' . 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" : ["algorithmic fairness, algorithmic bias, machine learning, ageism, age discrimination"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Training and testing data annotated by a panel survey sample of older adults (aged 50+) and used to create a basic, maximum entropy bag-of-words sentiment classifier. Testing data is scraped from blog posts discussing aging authored by older adults (see published work: https://doi.org/10.1145/3173574.3173986).Training data is a re-annotated subset of the Sentiment140 training data set containing the strings 'old' and 'young' (see Sentiment140: http://help.sentiment140.com/for-students). For model building, the subset was re-introduce into the full data set, replacing the original annotations' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Training and testing data annotated by a panel survey sample of older adults (aged 50+) and used to create a basic, maximum entropy bag-of-words sentiment classifier. Testing data is scraped from blog posts discussing aging authored by older adults (see published work: https://doi.org/10.1145/3173574.3173986).Training data is a re-annotated subset of the Sentiment140 training data set containing the strings 'old' and 'young' (see Sentiment140: http://help.sentiment140.com/for-students). For model building, the subset was re-introduce into the full data set, replacing the original annotations
algorithmic fairness, algorithmic bias, machine learning, ageism, age discrimination