Text data is everywhere. It's in the books we read, the news we consume, the social media posts we share, and the customer reviews we rely on when making purchasing decisions. This data can be incredibly valuable, but only if we can extract the meaning from it.
Natural language processing (NLP) is a field of computer science and artificial intelligence that deals with the interactions between computers and human (natural) languages. NLP is used to build applications that can automatically interpret and extract meaning from text data.
AWS Comprehend is a fully managed NLP service that makes it easy to extract meaning from text data. In this article, we'll take a look at how to use AWS Comprehend to analyze text data.
Before we can start using AWS Comprehend, we need to set up an AWS account and create an IAM user with permissions to access the service.
Once you have an AWS account, you can create an IAM user with the following policy:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"comprehend:*"
],
"Resource": "*"
}
]
}
With the IAM user in place, we can now create an AWS Comprehend resource. To do this, we'll need to log into the AWS Management Console and navigate to the AWS Comprehend service.
Once we're in the AWS Comprehend console, we can create a new resource. We'll need to provide a name for the resource, select the region, and choose the IAM role that we created earlier.
With the resource created, we're now ready to start using AWS Comprehend.
AWS Comprehend provides us with a number of different ways to analyze text data. In this section, we'll take a look at a few of the most commonly used features.
Sentiment analysis is a way of automatically extracting the sentiment (positive, negative, or neutral) from a piece of text. This can be useful for a variety of applications, such as determining the overall sentiment of a customer review or understanding the sentiment of social media posts.
To perform sentiment analysis with AWS Comprehend, we'll need to provide the text that we want to analyze. We can do this either by directly inputting the text or by providing a URL where the text is located.
Once we've provided the text, AWS Comprehend will analyze it and provide us with the sentiment of the text.
Key phrase extraction is a way of automatically identifying the key phrases in a piece of text. This can be useful for a variety of applications, such as identifying the topics of a customer review or understanding the topics of social media posts.
To perform key phrase extraction with AWS Comprehend, we'll need to provide the text that we want to analyze. We can do this either by directly inputting the text or by providing a URL where the text is located.
Once we've provided the text, AWS Comprehend will analyze it and provide us with the key phrases that it has extracted.
Language detection is a way of automatically identifying the language of a piece of text. This can be useful for a variety of applications, such as identifying the language of a customer review or understanding the language of social media posts.
To perform language detection with AWS Comprehend, we'll need to provide the text that we want to analyze. We can do this either by directly inputting the text or by providing a URL where the text is located.
Once we've provided the text, AWS Comprehend will analyze it and provide us with the language that it has detected.
In this article, we've looked at how to use AWS Comprehend to analyze text data. We've seen how to use AWS Comprehend to perform sentiment analysis, key phrase extraction, and language detection.
While we've only scratched the surface of what's possible with AWS Comprehend, this should be enough to get you started.