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A News Sentiment Analyzer for tracking developments around COVID-19 pandemic.
Overview
COVID-19 News Headlines Sentiment Analyzer helps businesses to analyze headlines around the pandemic. It helps the users to identify COVID-19 related sentiments based on analysis of news headlines and classify them as positive, negative, neutral and mixed. It determines the sentiment of News headlines by maintaining aspect and polarity associated with COVID-19. This analysis can be used in various scenarios like stock movement predictions, econometric analysis, policy effectiveness and risk analytics.
Highlights
- Highly customized Deep Learning based model for COVID-19 news headlines analysis, trained using State of the Art Transformer model along with COVID-19 specific features augmentation. The dataset was sourced from recent news articles and custom tagged.
- This solution comes with a highly accurate pre-trained model which can be used directly for sentiment analysis. We are also providing, highly customizable training module optimized and tuned for COVID-19 use cases, where new data can be fed, and model can be trained end to end.
- Need customized sentiment analysis solutions? Get in touch!
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Free trial
Try this product free for 30 days according to the free trial terms set by the vendor.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.2xlarge Inference (Batch) Recommended | Model inference on the ml.m5.2xlarge instance type, batch mode | $10.00 |
ml.m5.2xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.2xlarge instance type, real-time mode | $5.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $10.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $10.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $10.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $10.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $10.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $10.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $10.00 |
ml.c4.2xlarge Inference (Batch) | Model inference on the ml.c4.2xlarge instance type, batch mode | $10.00 |
Vendor refund policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
Legal
Vendor terms and conditions
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Content disclaimer
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Bug Fixes and Performance Improvement
Additional details
Inputs
- Summary
Usage Methodology for the algorithm:
- The input has to be a .csv file with the content in a column titled 'sentence'
- The file should follow 'utf-8' encoding.
- The input can have a maximum of 512 words.
General instructions for consuming the service on Sagemaker:
- Access to AWS SageMaker and the model package
- An S3 bucket to specify input/output
- Role for AWS SageMaker to access input/output from S3
Input
Supported content types: text/csv
sample input
SNo-|--------------------sentence-------------------------
- Artist project to combat isolation turns loneliness......
- Grieving from a distance: How COVID-19 changes......
- Dubious screenshot claims Chinese website...
- No charges after car 'cruise night' in Carievale...
- Coronavirus: charities rally to help older ...
Output
Content type: text/csv
sample output
--------------sentence-------------------------------------|- sentiment----- Artist project to combat isolation turns loneliness...... Negative Grieving from a distance: How COVID-19 changes...... Neutral Dubious screenshot claims Chinese website... Negative No charges after car 'cruise night' in Carievale... Positive Coronavirus: charities rally to help older ... Positive
Invoking endpoint
AWS CLI Command
You can invoke endpoint using AWS CLI:
aws sagemaker-runtime invoke-endpoint --endpoint-name $model_name --body fileb://$file_name --content-type 'text/csv' --region us-east-2 output.csvSubstitute the following parameters:
- "model_name" - name of the inference endpoint where the model is deployed
- input.csv - input file to do the inference on
- text/csv - Type of input data
- output.csv - filename where the inference results are written to
Resources
Sample Notebook : https://tinyurl.com/y964pc62 Sample Input : https://tinyurl.com/yaddn5ck Sample Output: https://tinyurl.com/y75nsmcvÂ
- Input MIME type
- text/csv, text/plain
See Input Summary
See Input Summary
Resources
Vendor resources
Support
Vendor support
For any assistance reach out to us at:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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