name : start-sentiment-detection-job.rst **To start an asynchronous sentiment analysis job** The following ``start-sentiment-detection-job`` example starts an asynchronous sentiment analysis detection job for all files located at the address specified by the ``--input-data-config`` tag. The S3 bucket folder in this example contains ``SampleMovieReview1.txt``, ``SampleMovieReview2.txt``, and ``SampleMovieReview3.txt``. When the job is complete, the folder, ``output``, is placed at the location specified by the ``--output-data-config`` tag. The folder contains the file, ``output.txt``, which contains the prevailing sentiments for each text file and the pre-trained model's confidence score for each prediction. The Json output is printed on one line per file, but is formatted here for readability. :: aws comprehend start-sentiment-detection-job \ --job-name example-sentiment-detection-job \ --language-code en \ --input-data-config "S3Uri=s3://amzn-s3-demo-bucket/MovieData" \ --output-data-config "S3Uri=s3://amzn-s3-demo-destination-bucket/testfolder/" \ --data-access-role-arn arn:aws:iam::111122223333:role/service-role/AmazonComprehendServiceRole-example-role Contents of ``SampleMovieReview1.txt``:: "The film, AnyMovie2, is fairly predictable and just okay." Contents of ``SampleMovieReview2.txt``:: "AnyMovie2 is the essential sci-fi film that I grew up watching when I was a kid. I highly recommend this movie." Contents of ``SampleMovieReview3.txt``:: "Don't get fooled by the 'awards' for AnyMovie2. All parts of the film were poorly stolen from other modern directors." Output:: { "JobId": "0b5001e25f62ebb40631a9a1a7fde7b3", "JobArn": "arn:aws:comprehend:us-west-2:111122223333:sentiment-detection-job/0b5001e25f62ebb40631a9a1a7fde7b3", "JobStatus": "SUBMITTED" } Contents of ``output.txt`` with line of indents for readability:: { "File": "SampleMovieReview1.txt", "Line": 0, "Sentiment": "MIXED", "SentimentScore": { "Mixed": 0.6591159105300903, "Negative": 0.26492202281951904, "Neutral": 0.035430654883384705, "Positive": 0.04053137078881264 } } { "File": "SampleMovieReview2.txt", "Line": 0, "Sentiment": "POSITIVE", "SentimentScore": { "Mixed": 0.000008718466233403888, "Negative": 0.00006134175055194646, "Neutral": 0.0002941041602753103, "Positive": 0.9996358156204224 } } { "File": "SampleMovieReview3.txt", "Line": 0, "Sentiment": "NEGATIVE", "SentimentScore": { "Mixed": 0.004146667663007975, "Negative": 0.9645107984542847, "Neutral": 0.016559595242142677, "Positive": 0.014782938174903393 } } } For more information, see `Async analysis for Amazon Comprehend insights <https://docs.aws.amazon.com/comprehend/latest/dg/api-async-insights.html>`__ in the *Amazon Comprehend Developer Guide*.