- TextColumn
- Specify the name of the input column that contains text from which to extract sentiments.
- InputLanguage
- [Optional] Specify the language of the input text:
Option Description 'en' (Default) English 'zh_CN' Simplified Chinese 'zh_TW' Traditional Chinese - InputModelFile
- [Optional] Specify the model type and file. The default model type is dictionary. If you omit this syntax element or specify dictionary without dict_file, then you must specify a dictionary table with alias Dict. If you specify both Dict and dict_file, then whenever their words conflict, Dict has higher priority.
The dict_file must be a text file in which each line contains only a sentiment word, a space, and the opinion score of the sentiment word.
If you specify classification input_model_file, then input_model_file must be the name of a model file created and installed on ML Engine by the function SentimentTrainer (ML Engine).
- Accumulate
- [Optional] Specify the names of the input columns to copy to the output table.
- AnalysisType
- [Optional] Specify the level of analysis—whether to analyze each document (the default) or each sentence.
- Priority
- [Optional] Specify the highest priority when returning results:
Option Description 'NONE' (Default) Give all results same priority. 'NEGATIVE_RECALL' Give highest priority to negative results, including those with lower-confidence sentiment classifications (maximizes number of negative results returned). 'NEGATIVE_PRECISION' Give highest priority to negative results with high-confidence sentiment classifications. 'POSITIVE_RECALL' Give highest priority to positive results, including those with lower-confidence sentiment classifications (maximizes number of positive results returned). 'POSITIVE_PRECISION' Give highest priority to positive results with high-confidence sentiment classifications. - OutputType
- [Optional] Specify the kind of results to return:
Option Description 'ALL' (Default) Return all results. 'POSITIVE' Return only results with positive sentiments. 'NEGATIVE' Return only results with negative sentiments.