Analyzing the Sentiment of Your Blog Comments

StepZen workshop demonstrating how to analyze sentiment of blog comments by connecting the Dev.to API with Google's Natural Language API using GraphQL and custom directives.

Episode Summary

In this StepZen workshop, Anthony Campolo and Lucia demonstrate how to use the StepZen GraphQL studio to connect multiple APIs and perform sentiment analysis on blog comments. They start by exploring the Google Natural Language API to analyze sentiment and classify text. Then they connect the Dev.to API to fetch blog posts and comments. Using StepZen’s custom directives like @rest and @sequence, they show how to combine these APIs to analyze the sentiment of comments on Dev.to articles. The workshop highlights StepZen’s ability to simplify API integration and GraphQL implementation compared to traditional methods. They discuss the power of GraphQL for front-end developers and how StepZen makes it easier to leverage complex data analysis tools without extensive machine learning expertise. The presenters also touch on potential applications, like creating dynamic websites with sentiment analysis features.

Chapters

00:00 - Introduction and Overview

Anthony and Lucia introduce themselves and the StepZen workshop. They briefly discuss the previous workshop on building a custom portfolio website generator. The hosts explain that this session will focus on connecting different APIs, particularly the Dev.to API and Google Cloud Natural Language API, to perform sentiment analysis on blog comments. They emphasize StepZen’s ability to combine multiple schemas into a unified graph and highlight its custom directives for API integration.

02:56 - Google Natural Language API Demonstration

Anthony demonstrates the Google Natural Language API using the StepZen studio. He shows how to analyze sentiment of text phrases, getting polarity scores ranging from -1 (negative) to 1 (positive). They discuss the API’s ability to detect entities in text and classify content into categories. The hosts explain how Google’s sophisticated machine learning algorithms, trained on vast amounts of labeled data, power these natural language processing capabilities. They highlight the potential applications of such technology in various fields.

13:40 - Dev.to API Integration

The hosts move on to integrating the Dev.to API. They demonstrate how to fetch articles and user information using GraphQL queries in the StepZen studio. Anthony explains the @rest directive, which simplifies the process of turning REST API endpoints into GraphQL queries. They compare this approach to traditional GraphQL implementation methods, highlighting StepZen’s efficiency in reducing code complexity and maintenance overhead. The discussion touches on the benefits of GraphQL for front-end developers and its introspective nature for back-end developers.

24:23 - Combining APIs with Custom Directives

Anthony introduces StepZen’s @sequence directive, which allows chaining multiple API calls. They create a new query to get comment sentiment by combining the Dev.to API (to fetch comments) with the Google Natural Language API (to analyze sentiment). The hosts demonstrate how to export schemas from the studio to a local project and explain the project structure. They show how to use the @sequence directive to feed the output of one query as input to another, effectively linking different APIs together.

34:04 - Applications and Conclusion

The hosts discuss potential applications of the demonstrated techniques, such as analyzing sentiment of various content types (tweets, Yelp reviews, GitHub issues). They emphasize how StepZen simplifies complex data analysis for developers without extensive machine learning expertise. Anthony and Lucia suggest combining their projects to create a dynamic blogging platform with sentiment analysis features. They conclude by highlighting the ease of integrating these GraphQL queries into front-end applications and encourage viewers to explore StepZen further.