- TextColumn
- Specifies the name of the input column that contains text from which to extract sentiments.
- Language
- [Optional] Specifies the language of the input text:
- 'en': English (Default)
- 'zh_CN': Simplified Chinese
- 'zh_TW': Traditional Chinese
- Model
- [Optional] Specifies the model type and file. The default model type is
dictionary. If you omit this argument 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 model_file, then model_file must be the name of a model file generated and installed on the database by the function TrainSentimentExtractor.
Before running the function, add the location of dict_file or model_file to the user/session default search path. - Accumulate
- [Optional] Specifies the names of the input columns to copy to the output table.
- Level
- [Optional] Specifies the level of analysis—whether to analyze each document (the default) or each sentence.
- HighPriority
- [Optional] Specifies the highest priority when returning results:
-
'NEGATIVE_RECALL'
Give highest priority to negative results, including those with lower-confidence sentiment classifications (maximizes the 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 the number of positive results returned).
-
'POSITIVE_PRECISION'
Give highest priority to positive results with high-confidence sentiment classifications.
-
'NONE'
Give all results the same priority.
-
'NEGATIVE_RECALL'
- Filter
- [Optional] Specifies the kind of results to return:
-
'ALL' (Default)
Return all results.
-
'POSITIVE'
Return only results with positive sentiments.
-
'NEGATIVE'
Return only results with negative sentiments.
-
'ALL' (Default)